PineConnectorLibrary "PineConnector"
This library is a comprehensive alert webhook text generator for PineConnector. It contains every possible alert syntax variation from the documentation, along with some debugging functions.
To use it, just import the library (eg. "import ZenAndTheArtOfTrading/PineConnector/1 as pc") and use pc.buy(licenseID) to send an alert off to PineConnector - assuming all your webhooks etc are set up correctly.
View the PineConnector documentation for more information on how to send the commands you're looking to send (all of this library's function names match the documentation).
all()
Usage: pc.buy(pc_id, freq=pc.all())
Returns: "all"
once_per_bar()
Usage: pc.buy(pc_id, freq=pc.once_per_bar())
Returns: "once_per_bar"
once_per_bar_close()
Usage: pc.buy(pc_id, freq=pc.once_per_bar_close())
Returns: "once_per_bar_close"
na0(value)
Checks if given value is either 'na' or 0. Useful for streamlining scripts with float user setting inputs which default values to 0 since na is unavailable as a user input default.
Parameters:
value (float) : The value to check
Returns: True if the given value is 0 or na
getDecimals()
Calculates how many decimals are on the quote price of the current market.
Returns: The current decimal places on the market quote price
truncate(number, decimals)
Truncates the given number. Required params: mumber.
Parameters:
number (float) : Number to truncate
decimals (int) : Decimal places to cut down to
Returns: The input number, but as a string truncated to X decimals
getPipSize(multiplier)
Calculates the pip size of the current market.
Parameters:
multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)
Returns: The pip size for the current market
toWhole(number)
Converts pips into whole numbers. Required params: number.
Parameters:
number (float) : The pip number to convert into a whole number
Returns: The converted number
toPips(number)
Converts whole numbers back into pips. Required params: number.
Parameters:
number (float) : The whole number to convert into pips
Returns: The converted number
debug(txt, tooltip, displayLabel)
Prints to console and generates a debug label with the given text. Required params: txt.
Parameters:
txt (string) : Text to display
tooltip (string) : Tooltip to display (optional)
displayLabel (bool) : Turns on/off chart label (default: off)
Returns: Nothing
order(licenseID, command, symbol, parameters, accfilter, comment, secret, freq, debug)
Generates an alert string. Required params: licenseID, command.
Parameters:
licenseID (string) : Your PC license ID
command (string) : Command to send
symbol (string) : The symbol to trigger this order on
parameters (string) : Other optional parameters to include
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: An alert string with valid PC syntax based on supplied parameters
market_order(licenseID, buy, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a market entry alert with relevant syntax commands. Required params: licenseID, buy, risk.
Parameters:
licenseID (string) : Your PC license ID
buy (bool) : true=buy/long, false=sell/short
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A market order alert string with valid PC syntax based on supplied parameters
buy(licenseID, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a market buy alert with relevant syntax commands. Required params: licenseID, risk.
Parameters:
licenseID (string) : Your PC license ID
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A market order alert string with valid PC syntax based on supplied parameters
sell(licenseID, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a market sell alert with relevant syntax commands. Required params: licenseID, risk.
Parameters:
licenseID (string) : Your PC license ID
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A market order alert string with valid PC syntax based on supplied parameters
closeall(licenseID, comment, secret, freq, debug)
Closes all open trades at market regardless of symbol. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closealleaoff(licenseID, comment, secret, freq, debug)
Closes all open trades at market regardless of symbol, and turns the EA off. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closelong(licenseID, symbol, comment, secret, freq, debug)
Closes all long trades at market for the given symbol. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closeshort(licenseID, symbol, comment, secret, freq, debug)
Closes all open short trades at market for the given symbol. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closelongshort(licenseID, symbol, comment, secret, freq, debug)
Closes all open trades at market for the given symbol. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closelongbuy(licenseID, risk, symbol, comment, secret, freq, debug)
Close all long positions and open a new long at market for the given symbol with given risk/contracts. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
risk (float) : Risk or contracts (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closeshortsell(licenseID, risk, symbol, comment, secret, freq, debug)
Close all short positions and open a new short at market for the given symbol with given risk/contracts. Required params: licenseID, risk.
Parameters:
licenseID (string) : Your PC license ID
risk (float) : Risk or contracts (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
newsltplong(licenseID, sl, tp, symbol, accfilter, comment, secret, freq, debug)
Updates the stop loss and/or take profit of any open long trades on the given symbol with the given values. Required params: licenseID, sl and/or tp.
Parameters:
licenseID (string) : Your PC license ID
sl (float) : Stop loss pips or price (according to EA settings)
tp (float) : Take profit pips or price (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
newsltpshort(licenseID, sl, tp, symbol, accfilter, comment, secret, freq, debug)
Updates the stop loss and/or take profit of any open short trades on the given symbol with the given values. Required params: licenseID, sl and/or tp.
Parameters:
licenseID (string) : Your PC license ID
sl (float) : Stop loss pips or price (according to EA settings)
tp (float) : Take profit pips or price (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closelongpct(licenseID, symbol, comment, secret, freq, debug)
Close a percentage of open long positions (according to EA settings). Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closeshortpct(licenseID, symbol, comment, secret, freq, debug)
Close a percentage of open short positions (according to EA settings). Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closelongvol(licenseID, risk, symbol, comment, secret, freq, debug)
Close all open long contracts on the current symbol until the given risk value is remaining. Required params: licenseID, risk.
Parameters:
licenseID (string) : Your PC license ID
risk (float) : The quantity to leave remaining
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
closeshortvol(licenseID, risk, symbol, comment, secret, freq, debug)
Close all open short contracts on the current symbol until the given risk value is remaining. Required params: licenseID, risk.
Parameters:
licenseID (string) : Your PC license ID
risk (float) : The quantity to leave remaining
symbol (string) : Symbol to act on (defaults to current symbol)
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
limit_order(licenseID, buy, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a limit order alert with relevant syntax commands. Required params: licenseID, buy, price, risk.
Parameters:
licenseID (string) : Your PC license ID
buy (bool) : true=buy/long, false=sell/short
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A limit order alert string with valid PC syntax based on supplied parameters
buylimit(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a buylimit order alert with relevant syntax commands. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A limit order alert string with valid PC syntax based on supplied parameters
selllimit(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a selllimit order alert with relevant syntax commands. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A limit order alert string with valid PC syntax based on supplied parameters
stop_order(licenseID, buy, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a stop order alert with relevant syntax commands. Required params: licenseID, buy, price, risk.
Parameters:
licenseID (string) : Your PC license ID
buy (bool) : true=buy/long, false=sell/short
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
buystop(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a buystop order alert with relevant syntax commands. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
sellstop(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Generates a sellstop order alert with relevant syntax commands. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
cancel_neworder(licenseID, order, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Cancel + place new order template function.
Parameters:
licenseID (string) : Your PC license ID
order (string) : Cancel order type
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
cancellongbuystop(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Cancels all long orders with the specified symbol and places a new buystop order. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
cancellongbuylimit(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Cancels all long orders with the specified symbol and places a new buylimit order. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
cancelshortsellstop(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Cancels all short orders with the specified symbol and places a sellstop order. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
cancelshortselllimit(licenseID, price, risk, sl, tp, betrigger, beoffset, spread, trailtrig, traildist, trailstep, atrtimeframe, atrperiod, atrmultiplier, atrshift, atrtrigger, symbol, accfilter, comment, secret, freq, debug)
Cancels all short orders with the specified symbol and places a selllimit order. Required params: licenseID, price, risk.
Parameters:
licenseID (string) : Your PC license ID
price (float) : Price or pips to set limit order (according to EA settings)
risk (float) : Risk quantity (according to EA settings)
sl (float) : Stop loss distance in pips or price
tp (float) : Take profit distance in pips or price
betrigger (float) : Breakeven will be activated after the position gains this number of pips
beoffset (float) : Offset from entry price. This is the amount of pips you'd like to protect
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips
trailtrig (float) : Trailing stop-loss will be activated after a trade gains this number of pips
traildist (float) : Distance of the trailing stop-loss from current price
trailstep (float) : Moves trailing stop-loss once price moves to favourable by a specified number of pips
atrtimeframe (int) : ATR Trailing Stop timeframe, only updates once per bar close. Options: 1, 5, 15, 30, 60, 240, 1440
atrperiod (int) : ATR averaging period
atrmultiplier (float) : Multiple of ATR to utilise in the new SL computation, default = 1
atrshift (int) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default = 0
atrtrigger (int) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default = 0 (instant)
symbol (string) : The symbol to trigger this order on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment (maximum 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A stop order alert string with valid PC syntax based on supplied parameters
cancellong(licenseID, symbol, accfilter, comment, secret, freq, debug)
Cancels all pending long orders with the specified symbol. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A cancel long alert command
cancelshort(licenseID, symbol, accfilter, comment, secret, freq, debug)
Cancels all pending short orders with the specified symbol. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: A cancel short alert command
newsltpbuystop(licenseID, sl, tp, symbol, accfilter, comment, secret, freq, debug)
Updates the stop loss and/or take profit of any pending buy stop orders on the given symbol. Required params: licenseID, sl and/or tp.
Parameters:
licenseID (string) : Your PC license ID
sl (float) : Stop loss pips or price (according to EA settings)
tp (float) : Take profit pips or price (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
newsltpbuylimit(licenseID, sl, tp, symbol, accfilter, comment, secret, freq, debug)
Updates the stop loss and/or take profit of any pending buy limit orders on the given symbol. Required params: licenseID, sl and/or tp.
Parameters:
licenseID (string) : Your PC license ID
sl (float) : Stop loss pips or price (according to EA settings)
tp (float) : Take profit pips or price (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
newsltpsellstop(licenseID, sl, tp, symbol, accfilter, comment, secret, freq, debug)
Updates the stop loss and/or take profit of any pending sell stop orders on the given symbol. Required params: licenseID, sl and/or tp.
Parameters:
licenseID (string) : Your PC license ID
sl (float) : Stop loss pips or price (according to EA settings)
tp (float) : Take profit pips or price (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
newsltpselllimit(licenseID, sl, tp, symbol, accfilter, comment, secret, freq, debug)
Updates the stop loss and/or take profit of any pending sell limit orders on the given symbol. Required params: licenseID, sl and/or tp.
Parameters:
licenseID (string) : Your PC license ID
sl (float) : Stop loss pips or price (according to EA settings)
tp (float) : Take profit pips or price (according to EA settings)
symbol (string) : Symbol to act on (defaults to current symbol)
accfilter (float) : Optional minimum account balance filter
comment (string) : Optional comment to include (max 20 characters)
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
eaoff(licenseID, secret, freq, debug)
Turns the EA off. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
eaon(licenseID, secret, freq, debug)
Turns the EA on. Required params: licenseID.
Parameters:
licenseID (string) : Your PC license ID
secret (string) : Optional secret key (must be enabled in dashboard)
freq (string) : Alert frequency. Default = "all", options = "once_per_bar", "once_per_bar_close" and "none"
debug (bool) : Turns on/off debug label
Returns: The required alert syntax as a string
Buscar en scripts para "黄金近20年走势"
Scout Regiment - KSI# Scout Regiment - KSI Indicator
## English Documentation
### Overview
Scout Regiment - KSI (Key Stochastic Indicators) is a comprehensive momentum oscillator that combines three powerful technical indicators - RSI, CCI, and Williams %R - into a single, unified display. This multi-indicator approach provides traders with diverse perspectives on market momentum, overbought/oversold conditions, and potential reversal points through advanced divergence detection.
### What is KSI?
KSI stands for "Key Stochastic Indicators" - a composite momentum indicator that:
- Displays multiple oscillators normalized to a 0-100 scale
- Uses standardized bands (20/50/80) for consistent interpretation
- Combines RSI for trend, CCI for cycle, and Williams %R for reversal detection
- Provides enhanced divergence detection specifically for RSI
### Key Features
#### 1. **Triple Oscillator System**
**① RSI (Relative Strength Index)** - Primary Indicator
- **Purpose**: Measures momentum and identifies overbought/oversold conditions
- **Default Length**: 22 periods
- **Display**: Blue line (2px)
- **Key Levels**:
- Above 50: Bullish momentum
- Below 50: Bearish momentum
- Above 80: Overbought
- Below 20: Oversold
- **Special Features**:
- Background color indication (green/red)
- Crossover labels at 50 level
- Full divergence detection (4 types)
**② CCI (Commodity Channel Index)** - Dual Period
- **Purpose**: Identifies cyclical trends and extreme conditions
- **Dual Display**:
- CCI(33): Short-term cycle - Green line (1px)
- CCI(77): Medium-term cycle - Orange line (1px)
- **Default Source**: HLC3 (typical price)
- **Normalized Scale**: Mapped from ±100 to 0-100 for consistency
- **Interpretation**:
- Above 80: Strong upward momentum
- Below 20: Strong downward momentum
- 50 level: Neutral
- Divergence between periods: Trend change warning
**③ Williams %R** - Optional
- **Purpose**: Identifies overbought/oversold extremes
- **Default Length**: 28 periods
- **Display**: Magenta line (2px)
- **Scale**: Inverted and normalized to 0-100
- **Best For**: Short-term reversal signals
- **Default**: Disabled (enable when needed for extra confirmation)
#### 2. **Standardized Band System**
**Three-Level Structure:**
- **Upper Band (80)**: Overbought zone
- Strong momentum area
- Watch for reversal signals
- Divergences here are most reliable
- **Middle Line (50)**: Equilibrium
- Separates bullish/bearish zones
- Crossovers indicate momentum shifts
- Key decision level
- **Lower Band (20)**: Oversold zone
- Weak momentum area
- Look for bounce signals
- Divergences here signal potential reversals
**Band Fill**: Dark background between 20-80 for visual clarity
#### 3. **RSI Visual Enhancements**
**Background Color Indication**
- Green background: RSI above 50 (bullish bias)
- Red background: RSI below 50 (bearish bias)
- Optional display for cleaner charts
- Helps identify overall momentum direction
**Crossover Labels**
- "突破" (Breakout): RSI crosses above 50
- "跌破" (Breakdown): RSI crosses below 50
- Marks momentum shift points
- Can be toggled on/off
#### 4. **Advanced RSI Divergence Detection**
The indicator includes comprehensive divergence detection for RSI only (most reliable oscillator):
**Regular Bullish Divergence (Yellow)**
- **Price**: Lower lows
- **RSI**: Higher lows
- **Signal**: Potential upward reversal
- **Label**: "涨" (Up)
- **Most Common**: Near oversold levels (below 30)
**Regular Bearish Divergence (Blue)**
- **Price**: Higher highs
- **RSI**: Lower highs
- **Signal**: Potential downward reversal
- **Label**: "跌" (Down)
- **Most Common**: Near overbought levels (above 70)
**Hidden Bullish Divergence (Light Yellow)**
- **Price**: Higher lows
- **RSI**: Lower lows
- **Signal**: Uptrend continuation
- **Label**: "隐涨" (Hidden Up)
- **Use**: Add to existing longs
**Hidden Bearish Divergence (Light Blue)**
- **Price**: Lower highs
- **RSI**: Higher highs
- **Signal**: Downtrend continuation
- **Label**: "隐跌" (Hidden Down)
- **Use**: Add to existing shorts
**Divergence Parameters** (Fully Customizable):
- **Right Lookback**: Bars to right of pivot (default: 5)
- **Left Lookback**: Bars to left of pivot (default: 5)
- **Max Range**: Maximum bars between pivots (default: 60)
- **Min Range**: Minimum bars between pivots (default: 5)
### Configuration Settings
#### KSI Display Settings
- **Show RSI**: Toggle RSI indicator
- **Show CCI**: Toggle both CCI lines
- **Show Williams %R**: Toggle Williams %R (optional)
#### RSI Settings
- **RSI Length**: Period for calculation (default: 22)
- **Data Source**: Price source (default: close)
- **Show Background**: Toggle green/red background
- **Show Cross Labels**: Toggle 50-level crossover labels
#### RSI Divergence Settings
- **Right Lookback**: Pivot detection right side
- **Left Lookback**: Pivot detection left side
- **Max Range**: Maximum lookback distance
- **Min Range**: Minimum lookback distance
- **Show Regular Divergence**: Enable regular divergence lines
- **Show Regular Labels**: Enable regular divergence labels
- **Show Hidden Divergence**: Enable hidden divergence lines
- **Show Hidden Labels**: Enable hidden divergence labels
#### CCI Settings
- **CCI Length**: Short-term period (default: 33)
- **CCI Mid Length**: Medium-term period (default: 77)
- **Data Source**: Price calculation (default: HLC3)
- **Show CCI(33)**: Toggle short-term CCI
- **Show CCI(77)**: Toggle medium-term CCI
#### Williams %R Settings
- **Length**: Calculation period (default: 28)
- **Data Source**: Price source (default: close)
### How to Use
#### For Basic Momentum Trading
1. **Enable RSI Only** (primary indicator)
- Focus on 50-level crossovers
- Enable crossover labels for signals
2. **Identify Momentum Direction**
- RSI > 50 = Bullish momentum
- RSI < 50 = Bearish momentum
- Background color confirms direction
3. **Look for Extremes**
- RSI > 80 = Overbought (consider selling)
- RSI < 20 = Oversold (consider buying)
4. **Trade Setup**
- Enter long when RSI crosses above 50 from oversold
- Enter short when RSI crosses below 50 from overbought
#### For Divergence Trading
1. **Enable RSI with Divergence Detection**
- Turn on regular divergence
- Optionally add hidden divergence
2. **Wait for Divergence Signal**
- Yellow label = Bullish divergence
- Blue label = Bearish divergence
3. **Confirm with Price Structure**
- Wait for support/resistance break
- Look for candlestick patterns
- Check volume confirmation
4. **Enter Position**
- Enter after confirmation
- Stop beyond divergence pivot
- Target next key level
#### For Multi-Oscillator Confirmation
1. **Enable All Three Indicators**
- RSI (momentum)
- CCI dual (cycle analysis)
- Williams %R (extremes)
2. **Look for Alignment**
- All above 50 = Strong bullish
- All below 50 = Strong bearish
- Mixed signals = Consolidation
3. **Identify Extremes**
- All indicators > 80 = Extreme overbought
- All indicators < 20 = Extreme oversold
4. **Trade Reversals**
- Enter counter-trend when all aligned at extremes
- Confirm with divergence if available
- Use tight stops
#### For CCI Dual-Period Analysis
1. **Enable Both CCI Lines**
- CCI(33) = Short-term
- CCI(77) = Medium-term
2. **Watch for Crossovers**
- Green crosses above orange = Bullish acceleration
- Green crosses below orange = Bearish acceleration
3. **Analyze Divergence Between Periods**
- Short-term rising, medium falling = Potential reversal
- Both rising together = Strong trend
4. **Trade Accordingly**
- Follow crossover direction
- Exit when lines converge
### Trading Strategies
#### Strategy 1: RSI 50-Level Crossover
**Setup:**
- Enable RSI with background and labels
- Wait for clear trend
- Look for retracement to 50 level
**Entry:**
- Long: "突破" label appears after pullback
- Short: "跌破" label appears after bounce
**Stop Loss:**
- Long: Below recent swing low
- Short: Above recent swing high
**Exit:**
- Opposite crossover label
- Or predetermined target (2:1 risk-reward)
**Best For:** Trend following, clear markets
#### Strategy 2: RSI Divergence Reversal
**Setup:**
- Enable RSI with regular divergence
- Wait for extreme levels (>70 or <30)
- Look for divergence signal
**Entry:**
- Long: Yellow "涨" label at oversold level
- Short: Blue "跌" label at overbought level
**Confirmation:**
- Wait for price to break structure
- Check for volume increase
- Look for candlestick reversal pattern
**Stop Loss:**
- Beyond divergence pivot point
**Exit:**
- Take partial profit at 50 level
- Exit remainder at opposite extreme or divergence
**Best For:** Swing trading, range-bound markets
#### Strategy 3: Triple Oscillator Confluence
**Setup:**
- Enable all three indicators
- Wait for all to reach extreme (>80 or <20)
- Look for alignment
**Entry:**
- Long: All three below 20, first one crosses above 20
- Short: All three above 80, first one crosses below 80
**Confirmation:**
- All indicators must align
- Price at support/resistance
- Volume spike helps
**Stop Loss:**
- Fixed percentage or ATR-based
**Exit:**
- When any indicator crosses 50 level
- Or at predetermined target
**Best For:** High-probability reversals, volatile markets
#### Strategy 4: CCI Dual-Period System
**Setup:**
- Enable both CCI lines only
- Disable RSI and Williams %R for clarity
- Watch for crossovers
**Entry:**
- Long: CCI(33) crosses above CCI(77) below 50 line
- Short: CCI(33) crosses below CCI(77) above 50 line
**Confirmation:**
- Both should be moving in entry direction
- Price breaking key level helps
**Stop Loss:**
- When CCIs cross back in opposite direction
**Exit:**
- Both CCIs enter opposite extreme zone
- Or trailing stop
**Best For:** Catching trend continuations, momentum trading
#### Strategy 5: Hidden Divergence Continuation
**Setup:**
- Enable RSI with hidden divergence
- Confirm existing trend
- Wait for pullback
**Entry:**
- Uptrend: "隐涨" label during pullback
- Downtrend: "隐跌" label during bounce
**Confirmation:**
- Price holds key moving average
- Trend structure intact
**Stop Loss:**
- Beyond pullback extreme
**Exit:**
- Regular divergence appears (reversal warning)
- Or trend structure breaks
**Best For:** Adding to positions, trend trading
### Best Practices
#### Choosing Which Indicators to Display
**For Beginners:**
- Use RSI only
- Enable background color and labels
- Focus on 50-level crossovers
- Simple and effective
**For Intermediate Traders:**
- RSI + Regular Divergence
- Add CCI for confirmation
- Use dual perspectives
- Better accuracy
**For Advanced Traders:**
- All three indicators
- Full divergence detection
- Multi-timeframe analysis
- Maximum information
#### Oscillator Priority
**Primary**: RSI (22)
- Most reliable
- Best divergence detection
- Good for all timeframes
- Use this as your main decision maker
**Secondary**: CCI (33/77)
- Adds cycle analysis
- Great for confirmation
- Dual-period crossovers valuable
- Use to confirm RSI signals
**Tertiary**: Williams %R (28)
- Extreme readings useful
- More volatile
- Best for short-term
- Use sparingly for extra confirmation
#### Timeframe Considerations
**Lower Timeframes (1m-15m):**
- More signals, less reliable
- Use tight divergence parameters
- Focus on RSI crossovers
- Quick entries and exits
**Medium Timeframes (30m-4H):**
- Balanced signal frequency
- Default settings work well
- Best for divergence trading
- Swing trading optimal
**Higher Timeframes (Daily+):**
- Fewer but stronger signals
- Widen divergence ranges
- All indicators more reliable
- Position trading best
#### Divergence Trading Tips
1. **Wait for Confirmation**
- Divergence alone isn't enough
- Need price structure break
- Volume helps validate
2. **Best at Extremes**
- Divergences near 80/20 levels most reliable
- Mid-level divergences often fail
- Combine with support/resistance
3. **Multiple Divergences**
- Second divergence stronger than first
- Third divergence extremely powerful
- Watch for "triple divergence"
4. **Timeframe Alignment**
- Check higher timeframe for direction
- Trade divergences in direction of larger trend
- Counter-trend divergences riskier
### Indicator Combinations
**With Moving Averages:**
- Use EMAs (21/55/144) for trend
- KSI for entry timing
- Enter when both align
**With Volume:**
- Volume confirms breakouts
- Divergence + volume divergence = Stronger
- Low volume at extremes = Reversal likely
**With Support/Resistance:**
- Price levels for targets
- KSI for entry timing
- Divergences at levels = Highest probability
**With Bias Indicator:**
- Bias shows price deviation
- KSI shows momentum
- Both diverging = Strong reversal signal
**With OBV Indicator:**
- OBV shows volume trend
- KSI shows price momentum
- Volume/momentum divergence powerful
### Common Patterns
1. **Bullish Reversal**: All oscillators oversold + RSI bullish divergence
2. **Bearish Reversal**: All oscillators overbought + RSI bearish divergence
3. **Trend Acceleration**: RSI > 50, both CCIs rising, Williams %R not extreme
4. **Weakening Trend**: RSI declining while price rising (pre-divergence warning)
5. **Strong Trend**: All oscillators stay above/below 50 for extended period
6. **Consolidation**: Oscillators crossing 50 frequently without extremes
7. **Exhaustion**: Multiple oscillators at extreme + hidden divergence failure
### Performance Tips
- Start simple: RSI only
- Add indicators gradually as you learn
- Disable unused features for cleaner charts
- Use labels strategically (not always on)
- Test different RSI lengths for your market
- Adjust divergence parameters based on volatility
### Alert Conditions
The indicator includes alerts for:
- RSI crossing above 50
- RSI crossing below 50
- RSI regular bullish divergence
- RSI regular bearish divergence
- RSI hidden bullish divergence
- RSI hidden bearish divergence
---
## 中文说明文档
### 概述
Scout Regiment - KSI（关键随机指标）是一个综合性动量振荡器，将三个强大的技术指标 - RSI、CCI和威廉指标 - 组合到一个统一的显示中。这种多指标方法为交易者提供了市场动量、超买超卖状况和通过高级背离检测发现潜在反转点的多元视角。
### 什么是KSI？
KSI代表"关键随机指标" - 一个综合动量指标：
- 显示多个振荡器，标准化到0-100刻度
- 使用标准化波段（20/50/80）便于一致解读
- 结合RSI用于趋势、CCI用于周期、威廉指标用于反转检测
- 专门为RSI提供增强的背离检测
### 核心功能
#### 1. **三重振荡器系统**
**① RSI（相对强弱指数）** - 主要指标
- **用途**：测量动量并识别超买超卖状况
- **默认长度**：22周期
- **显示**：蓝色线（2像素）
- **关键水平**：
- 50以上：看涨动量
- 50以下：看跌动量
- 80以上：超买
- 20以下：超卖
- **特殊功能**：
- 背景颜色指示（绿色/红色）
- 50水平穿越标签
- 完整背离检测（4种类型）
**② CCI（顺势指标）** - 双周期
- **用途**：识别周期性趋势和极端状况
- **双重显示**：
- CCI(33)：短期周期 - 绿色线（1像素）
- CCI(77)：中期周期 - 橙色线（1像素）
- **默认数据源**：HLC3（典型价格）
- **标准化刻度**：从±100映射到0-100以保持一致性
- **解读**：
- 80以上：强劲上升动量
- 20以下：强劲下降动量
- 50水平：中性
- 周期间背离：趋势变化警告
**③ 威廉指标 %R** - 可选
- **用途**：识别超买超卖极值
- **默认长度**：28周期
- **显示**：洋红色线（2像素）
- **刻度**：反转并标准化到0-100
- **最适合**：短期反转信号
- **默认**：禁用（需要额外确认时启用）
#### 2. **标准化波段系统**
**三层结构：**
- **上轨（80）**：超买区域
- 强动量区域
- 注意反转信号
- 此处的背离最可靠
- **中线（50）**：均衡线
- 分隔看涨/看跌区域
- 穿越表示动量转变
- 关键决策水平
- **下轨（20）**：超卖区域
- 弱动量区域
- 寻找反弹信号
- 此处的背离预示潜在反转
**波段填充**：20-80之间的深色背景，增强视觉清晰度
#### 3. **RSI视觉增强**
**背景颜色指示**
- 绿色背景：RSI在50以上（看涨偏向）
- 红色背景：RSI在50以下（看跌偏向）
- 可选显示，图表更清爽
- 帮助识别整体动量方向
**穿越标签**
- "突破"：RSI向上穿越50
- "跌破"：RSI向下穿越50
- 标记动量转变点
- 可开关
#### 4. **高级RSI背离检测**
指标仅为RSI（最可靠的振荡器）提供全面背离检测：
**常规看涨背离（黄色）**
- **价格**：更低的低点
- **RSI**：更高的低点
- **信号**：潜在向上反转
- **标签**："涨"
- **最常见**：在超卖水平附近（30以下）
**常规看跌背离（蓝色）**
- **价格**：更高的高点
- **RSI**：更低的高点
- **信号**：潜在向下反转
- **标签**："跌"
- **最常见**：在超买水平附近（70以上）
**隐藏看涨背离（浅黄色）**
- **价格**：更高的低点
- **RSI**：更低的低点
- **信号**：上升趋势延续
- **标签**："隐涨"
- **用途**：加仓现有多头
**隐藏看跌背离（浅蓝色）**
- **价格**：更低的高点
- **RSI**：更高的高点
- **信号**：下降趋势延续
- **标签**："隐跌"
- **用途**：加仓现有空头
**背离参数**（完全可自定义）：
- **右侧回溯**：枢轴点右侧K线数（默认：5）
- **左侧回溯**：枢轴点左侧K线数（默认：5）
- **最大范围**：枢轴点之间最大K线数（默认：60）
- **最小范围**：枢轴点之间最小K线数（默认：5）
### 配置设置
#### KSI显示设置
- **显示RSI**：切换RSI指标
- **显示CCI**：切换两条CCI线
- **显示威廉指标 %R**：切换威廉指标（可选）
#### RSI设置
- **RSI长度**：计算周期（默认：22）
- **数据源**：价格源（默认：收盘价）
- **显示背景**：切换绿色/红色背景
- **显示穿越标签**：切换50水平穿越标签
#### RSI背离设置
- **右侧回溯**：枢轴检测右侧
- **左侧回溯**：枢轴检测左侧
- **回溯范围最大值**：最大回溯距离
- **回溯范围最小值**：最小回溯距离
- **显示常规背离**：启用常规背离线
- **显示常规背离标签**：启用常规背离标签
- **显示隐藏背离**：启用隐藏背离线
- **显示隐藏背离标签**：启用隐藏背离标签
#### CCI设置
- **CCI长度**：短期周期（默认：33）
- **CCI中期长度**：中期周期（默认：77）
- **数据源**：价格计算（默认：HLC3）
- **显示CCI(33)**：切换短期CCI
- **显示CCI(77)**：切换中期CCI
#### 威廉指标 %R 设置
- **长度**：计算周期（默认：28）
- **数据源**：价格源（默认：收盘价）
### 使用方法
#### 基础动量交易
1. **仅启用RSI**（主要指标）
- 关注50水平穿越
- 启用穿越标签获取信号
2. **识别动量方向**
- RSI > 50 = 看涨动量
- RSI < 50 = 看跌动量
- 背景颜色确认方向
3. **寻找极值**
- RSI > 80 = 超买（考虑卖出）
- RSI < 20 = 超卖（考虑买入）
4. **交易设置**
- RSI从超卖区向上穿越50时做多
- RSI从超买区向下穿越50时做空
#### 背离交易
1. **启用RSI和背离检测**
- 打开常规背离
- 可选添加隐藏背离
2. **等待背离信号**
- 黄色标签 = 看涨背离
- 蓝色标签 = 看跌背离
3. **用价格结构确认**
- 等待支撑/阻力突破
- 寻找K线形态
- 检查成交量确认
4. **进入仓位**
- 确认后进入
- 止损设在背离枢轴点之外
- 目标下一个关键水平
#### 多振荡器确认
1. **启用全部三个指标**
- RSI（动量）
- CCI双周期（周期分析）
- 威廉指标 %R（极值）
2. **寻找一致性**
- 全部在50以上 = 强劲看涨
- 全部在50以下 = 强劲看跌
- 信号混合 = 盘整
3. **识别极值**
- 所有指标 > 80 = 极度超买
- 所有指标 < 20 = 极度超卖
4. **交易反转**
- 所有指标在极值一致时逆势进入
- 可能的话用背离确认
- 使用紧密止损
#### CCI双周期分析
1. **启用两条CCI线**
- CCI(33) = 短期
- CCI(77) = 中期
2. **观察穿越**
- 绿色线穿越橙色线向上 = 看涨加速
- 绿色线穿越橙色线向下 = 看跌加速
3. **分析周期间背离**
- 短期上升，中期下降 = 潜在反转
- 两者同时上升 = 强趋势
4. **相应交易**
- 跟随穿越方向
- 线条汇合时退出
### 交易策略
#### 策略1：RSI 50水平穿越
**设置：**
- 启用RSI及背景和标签
- 等待明确趋势
- 寻找回调至50水平
**入场：**
- 多头：回调后出现"突破"标签
- 空头：反弹后出现"跌破"标签
**止损：**
- 多头：近期波动低点之下
- 空头：近期波动高点之上
**离场：**
- 出现相反穿越标签
- 或预定目标（2:1风险收益比）
**适合：**趋势跟随、明确市场
#### 策略2：RSI背离反转
**设置：**
- 启用RSI和常规背离
- 等待极端水平（>70或<30）
- 寻找背离信号
**入场：**
- 多头：超卖水平出现黄色"涨"标签
- 空头：超买水平出现蓝色"跌"标签
**确认：**
- 等待价格突破结构
- 检查成交量增加
- 寻找K线反转形态
**止损：**
- 背离枢轴点之外
**离场：**
- 在50水平部分获利
- 其余在相反极值或背离处离场
**适合：**波段交易、震荡市场
#### 策略3：三重振荡器汇合
**设置：**
- 启用全部三个指标
- 等待全部达到极值（>80或<20）
- 寻找一致性
**入场：**
- 多头：三个全部低于20，第一个向上穿越20
- 空头：三个全部高于80，第一个向下穿越80
**确认：**
- 所有指标必须一致
- 价格在支撑/阻力位
- 成交量激增有帮助
**止损：**
- 固定百分比或基于ATR
**离场：**
- 任一指标穿越50水平时
- 或在预定目标
**适合：**高概率反转、波动市场
#### 策略4：CCI双周期系统
**设置：**
- 仅启用两条CCI线
- 禁用RSI和威廉指标以保持清晰
- 观察穿越
**入场：**
- 多头：CCI(33)在50线下方向上穿越CCI(77)
- 空头：CCI(33)在50线上方向下穿越CCI(77)
**确认：**
- 两者都应朝入场方向移动
- 价格突破关键水平有帮助
**止损：**
- CCI反向穿越时
**离场：**
- 两条CCI进入相反极值区域
- 或移动止损
**适合：**捕捉趋势延续、动量交易
#### 策略5：隐藏背离延续
**设置：**
- 启用RSI和隐藏背离
- 确认现有趋势
- 等待回调
**入场：**
- 上升趋势：回调期间出现"隐涨"标签
- 下降趋势：反弹期间出现"隐跌"标签
**确认：**
- 价格守住关键移动平均线
- 趋势结构完整
**止损：**
- 回调极值之外
**离场：**
- 出现常规背离（反转警告）
- 或趋势结构破坏
**适合：**加仓、趋势交易
### 最佳实践
#### 选择显示哪些指标
**新手：**
- 仅使用RSI
- 启用背景颜色和标签
- 关注50水平穿越
- 简单有效
**中级交易者：**
- RSI + 常规背离
- 添加CCI确认
- 使用双重视角
- 更高准确度
**高级交易者：**
- 全部三个指标
- 完整背离检测
- 多时间框架分析
- 信息最大化
#### 振荡器优先级
**主要**：RSI (22)
- 最可靠
- 最佳背离检测
- 适用所有时间框架
- 用作主要决策依据
**次要**：CCI (33/77)
- 添加周期分析
- 确认效果好
- 双周期穿越有价值
- 用于确认RSI信号
**第三**：威廉指标 %R (28)
- 极值读数有用
- 更波动
- 最适合短期
- 谨慎使用以获额外确认
#### 时间框架考虑
**低时间框架（1分钟-15分钟）：**
- 更多信号，可靠性较低
- 使用紧密背离参数
- 关注RSI穿越
- 快速进出
**中等时间框架（30分钟-4小时）：**
- 信号频率平衡
- 默认设置效果好
- 最适合背离交易
- 波段交易最优
**高时间框架（日线+）：**
- 信号较少但更强
- 扩大背离范围
- 所有指标更可靠
- 最适合仓位交易
#### 背离交易技巧
1. **等待确认**
- 仅背离不够
- 需要价格结构突破
- 成交量帮助验证
2. **极值处最佳**
- 80/20水平附近的背离最可靠
- 中间水平背离常失败
- 结合支撑/阻力
3. **多重背离**
- 第二次背离强于第一次
- 第三次背离极其强大
- 注意"三重背离"
4. **时间框架对齐**
- 检查更高时间框架方向
- 顺大趋势方向交易背离
- 逆势背离风险更大
### 指标组合
**与移动平均线配合：**
- 使用EMA（21/55/144）确定趋势
- KSI用于入场时机
- 两者一致时进入
**与成交量配合：**
- 成交量确认突破
- 背离 + 成交量背离 = 更强
- 极值处低成交量 = 可能反转
**与支撑/阻力配合：**
- 价格水平作为目标
- KSI用于入场时机
- 水平处的背离 = 最高概率
**与Bias指标配合：**
- Bias显示价格偏离
- KSI显示动量
- 两者都背离 = 强反转信号
**与OBV指标配合：**
- OBV显示成交量趋势
- KSI显示价格动量
- 成交量/动量背离强大
### 常见形态
1. **看涨反转**：所有振荡器超卖 + RSI看涨背离
2. **看跌反转**：所有振荡器超买 + RSI看跌背离
3. **趋势加速**：RSI > 50，两条CCI上升，威廉指标不极端
4. **趋势减弱**：价格上升时RSI下降（背离前警告）
5. **强趋势**：所有振荡器长时间保持在50上方/下方
6. **盘整**：振荡器频繁穿越50无极值
7. **衰竭**：多个振荡器在极值 + 隐藏背离失败
### 性能提示
- 从简单开始：仅RSI
- 学习时逐渐添加指标
- 禁用未使用功能以保持图表清晰
- 策略性使用标签（不总是开启）
- 为您的市场测试不同RSI长度
- 根据波动性调整背离参数
### 警报条件
指标包含以下警报：
- RSI向上穿越50
- RSI向下穿越50
- RSI常规看涨背离
- RSI常规看跌背离
- RSI隐藏看涨背离
- RSI隐藏看跌背离
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
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EMA Dynamic Crossover Detector with Real-Time Signal TableDescriptionWhat This Indicator Does:This indicator monitors all possible crossovers between four key exponential moving averages (20, 50, 100, and 200 periods) and displays them both visually on the chart and in an organized data table. Unlike standard EMA indicators that only plot the lines, this tool actively detects every crossover event, marks the exact crossover point with a circle, records the precise price level, and maintains a running log of all crossovers during the trading session. It's designed for traders who want comprehensive EMA crossover analysis without manually watching multiple moving average pairs.Key Features:
Four Essential EMAs: Plots 20, 50, 100, and 200-period exponential moving averages with color-coded thin lines for clean chart presentation
Complete Crossover Detection: Monitors all 6 possible EMA pair combinations (20×50, 20×100, 20×200, 50×100, 50×200, 100×200) in both directions
Precise Price Marking: Places colored circles at the exact average price where crossovers occur (not just at candle close)
Real-Time Signal Table: Displays up to 10 most recent crossovers with timestamp, direction, exact price, and signal type
Session Filtering: Only records crossovers during active trading hours (10:00-18:00 Istanbul time) to avoid noise from low-liquidity periods
Automatic Daily Reset: Clears the signal table at the start of each new trading day for fresh analysis
Built-In Alerts: Two alert conditions (bullish and bearish crossovers) that can be configured to send notifications
How It Works:The indicator calculates four exponential moving averages using the standard EMA formula, then continuously monitors for crossover events using Pine Script's ta.crossover() and ta.crossunder() functions:Bullish Crossovers (Green ▲):
When a faster EMA crosses above a slower EMA, indicating potential upward momentum:
20 crosses above 50, 100, or 200
50 crosses above 100 or 200
100 crosses above 200 (Golden Cross when it's the 50×200)
Bearish Crossovers (Red ▼):
When a faster EMA crosses below a slower EMA, indicating potential downward momentum:
20 crosses below 50, 100, or 200
50 crosses below 100 or 200
100 crosses below 200 (Death Cross when it's the 50×200)
Price Calculation:
Instead of marking crossovers at the candle's close price (which might not be where the actual cross occurred), the indicator calculates the average price between the two crossing EMAs, providing a more accurate representation of the crossover point.Signal Table Structure:The table in the top-right corner displays four columns:
Saat (Time): Exact time of crossover in HH:MM format
Yön (Direction): Arrow indicator (▲ green for bullish, ▼ red for bearish)
Fiyat (Price): Calculated average price at the crossover point
Durum (Status): Signal classification ("ALIŞ" for buy signals, "SATIŞ" for sell signals) with color-coded background
The table shows up to 10 most recent crossovers, automatically updating as new signals appear. If no crossovers have occurred during the session within the time filter, it displays "Henüz kesişim yok" (No crossovers yet).EMA Color Coding:
EMA 20 (Aqua/Turquoise): Fastest-reacting, most sensitive to recent price changes
EMA 50 (Green): Short-term trend indicator
EMA 100 (Yellow): Medium-term trend indicator
EMA 200 (Red): Long-term trend baseline, key support/resistance level
How to Use:For Day Traders:
Monitor 20×50 crossovers for quick entry/exit signals within the day
Use the time filter (10:00-18:00) to focus on high-volume trading hours
Check the signal table throughout the session to track momentum shifts
Look for confirmation: if 20 crosses above 50 and price is above EMA 200, bullish bias is stronger
For Swing Traders:
Focus on 50×200 crossovers (Golden Cross/Death Cross) for major trend changes
Use higher timeframes (4H, Daily) for more reliable signals
Wait for price to close above/below the crossover point before entering
Combine with support/resistance levels for better entry timing
For Position Traders:
Monitor 100×200 crossovers on daily/weekly charts for long-term trend changes
Use as confirmation of major market shifts
Don't react to every crossover—wait for sustained movement after the cross
Consider multiple timeframe analysis (if crossovers align on weekly and daily, signal is stronger)
Understanding EMA Hierarchies:The indicator becomes most powerful when you understand EMA relationships:Bullish Hierarchy (Strongest to Weakest):
All EMAs ascending (20 > 50 > 100 > 200): Strong uptrend
20 crosses above 50 while both are above 200: Pullback ending in uptrend
50 crosses above 200 while 20/50 below: Early trend reversal signal
Bearish Hierarchy (Strongest to Weakest):
All EMAs descending (20 < 50 < 100 < 200): Strong downtrend
20 crosses below 50 while both are below 200: Rally ending in downtrend
50 crosses below 200 while 20/50 above: Early trend reversal signal
Trading Strategy Examples:Pullback Entry Strategy:
Identify major trend using EMA 200 (price above = uptrend, below = downtrend)
Wait for pullback (20 crosses below 50 in uptrend, or above 50 in downtrend)
Enter when 20 re-crosses 50 in the trend direction
Place stop below/above the recent swing point
Exit when 20 crosses 50 against the trend again
Golden Cross/Death Cross Strategy:
Wait for 50×200 crossover (appears in the signal table)
Verify: Check if crossover occurs with increasing volume
Entry: Enter in the direction of the cross after a pullback
Stop: Place stop below/above the 200 EMA
Target: Swing high/low or when opposite crossover occurs
Multi-Crossover Confirmation:
Watch for multiple crossovers in the same direction within a short period
Example: 20×50 crossover followed by 20×100 = strengthening momentum
Enter after the second confirmation crossover
More crossovers = stronger signal but also means you're entering later
Time Filter Benefits:The 10:00-18:00 Istanbul time filter prevents recording crossovers during:
Pre-market volatility and gaps
Low-volume overnight sessions (for 24-hour markets)
After-hours erratic movements
Turtle Trader StrategyTurtle Trader Strategy :
Introduction :
This strategy is based on the well known « Turtle Trader Strategy », that has proven itself over the years. It sends long and short signals with pyramid orders of up to 5, meaning that the strategy can trigger up to 5 orders in the same direction. Good risk and money management.
It's important to note that the strategy combines 2 systems working together (S1 and S2). Let’s describe the specific features of this strategy.
1/ Position size :
Position size is very important for turtle traders to manage risk properly. This position sizing strategy adapts to market volatility and to account (gains and losses). It’s based on ATR (Average True Range) which can also be called « N ». Its length is per default 20.
ATR(20) = (previous_atr(20)*19 + actual_true_range)/20
The number of units to buy is :
Unit = 1% * account/(ATR(20)*dollar_per_point)
where account is the actual account value and dollar_per_point is the variation in dollar of the asset with a 1 point move.
Depending on your risk aversion, you can increase the percentage of your account, but turtle traders default to 1%. If you trade contracts, units must be rounded down by default.
There is also an additional rule to reduce the risk if the value of the account falls below the initial capital : in this case and only in this case, account in the unit formula must be replace by :
account = actual_account*actual_account/initial capital
2/ Open a position :
2 systems are working together :
System 1 : Entering a new 20 day breakout
System 2 : Entering a new 55 day breakout
A breakout is a new high or new low. If it’s a new high, we open long position and vice versa if it’s a new low we enter in short position.
We add an additional rule :
System 1 : Breakout is ignored if last long/short position was a winner
System 2 : All signals are taken
This additional rule allows the trader to be in the major trends if the system 1 signal has been skipped. If a signal for system 1 has been skipped, and next candle is also a new 20 day breakout, S1 doesn’t give a signal. We have to wait S2 signal or wait for a candle that doesn’t make a new breakout to reactivate S1.
3/ Pyramid orders :
Turtle Strategy allows us to add extra units to the position if the price moves in our favor. I've configured the strategy to allow up to 5 orders to be added in the same direction. So if the price varies from 0.5*ATR(20) , we add units with the position size formula. Note that the value of account will be replaced by "remaining_account", i.e. the cash remaining in our account after subtracting the value of open positions.
4/ Stop Loss :
We set a stop loss at 1.5*ATR(20) below the entry price for longs and above the entry price for shorts. If pyramid units are added, the stop is increased/decreased by 0.5*ATR(20). Note that if SL is configured for a loss of more than 10%, we set the SL to 10% for the first entry order to avoid big losses. This configuration does not work for pyramid orders as SL moves by 0.5*ATR(20).
5/ Exit signals :
System 1 :
Exit long on a 10 day low
Exit short on a 10 day high
System 2 :
Exit long on a 20 day low
Exit short on a 20 day high
6/ What types of orders are placed ?
To enter in a position, stop orders are placed meaning that we place orders that will be automatically triggered by the signal at the exact breakout price. Stop loss and exit signals are also stop orders. Pyramid orders are market orders which will be triggered at the opening of the next candle to avoid repainting.
PARAMETERS :
Risk % of capital : Percentage used in the position size formula. Default is 1%
ATR period : ATR length used to calculate ATR. Default is 20
Stop ATR : Parameters used to fix stop loss. Default is 1.5 meaning that stop loss will be set at : buy_price - 1.5*ATR(20) for long and buy_price + 1.5*ATR(20) for short. Turtle traders default is 2 but 1.5 is better for cryptocurrency as there is a huge volatility.
S1 Long : System 1 breakout length for long. Default is 20
S2 Long : System 2 breakout length for long. Default is 55
S1 Long Exit : System 1 breakout length to exit long. Default is 10
S2 Long Exit : System 2 breakout length to exit long. Default is 20
S1 Short : System 1 breakout length for short. Default is 15
S2 Short : System 2 breakout length for short. Default is 55
S1 Short Exit : System 1 breakout length to exit short. Default is 7
S2 Short Exit : System 2 breakout length to exit short. Default is 20
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Pyramiding : Number of orders that can be passed in the same direction. Default is 5.
Important : Turtle traders don't trade crypto. For this specific asset type, I modify some parameters such as SL and Short S1 in order to maximize return while limiting drawdown. This strategy is the most optimal on BINANCE:BTCUSD in 1D timeframe with the parameters set per default. If you want to use this strategy for a different crypto please adapt parameters.
NOTE :
It's important to note that the first entry order (long or short) will be the largest. Subsequent pyramid orders will have fewer units than the first order. We've set a maximum SL for the first order of 10%, meaning that you won't lose more than 10% of the value of your first order. However, it is possible to lose more on your pyramid orders, as the SL is increased/decreased by 0.5*ATR(20), which does not secure a loss of more than 10% on your pyramid orders. The risk remains well managed because the value of these orders is less than the value of the first order. Remain vigilant to this small detail and adjust your risk according to your risk aversion.
Enjoy the strategy and don’t forget to take the trade :)
Rollover LTEThis indicator shows where price needs to be and when in order to cause the 20-sma and 50-sma moving averages to change directions. A change in direction requires the slope of a moving average to change from negative to positive or from positive to negative. When a moving average changes direction, it can be said that it has “rolled over” or “rolled up,” with the latter only applying if slope went from negative to positive.
Theory:
In order to solve for the price of the current bar that will cause the moving average to roll up, the slope from the previous bar’s average to the current bar’s average must be set equal to zero which is to say that the averages must be the same.
For the 20-sma, the equation simply stated in words is as follows:
Current MA as a function of current price and previous 19 values = previous MA which is fixed based on previous 20 values
The denominators which are both 20 cancel and the previous 19 values cancel. What’s left is current price on the left side and the value from 20 bars ago on the right.
Current price = value from 20 bars ago
and since the equation was set up for solving for the price of the current bar that will cause the MA to roll over
Rollover price = value from 20 bars ago
This makes plotting rollover price, both current and forecasted, fairly simple, as it’s merely the closing price plotted with an offset to the right the same distance as the moving average length.
Application:
The 20-sma and 50-sma rollover prices are plotted because they are considered to be the two most important moving averages for rollover analysis. Moving average lengths can be modified in the indicator settings. The 20-sma and 20-sma rollover price are both plotted in white and the 50-sma and 50-sma rollover price are both plotted in blue. There are two rollover prices because the 20-sma rollover price is the price that will cause the 20-sma to roll over and the 50-sma rollover price is the price that will cause the 50-sma to roll over. The one that's vertically furthest away from the current price is the one that will cause both to rollover, as should become clearer upon reading the explanation below.
The distance between the current price and the 20-sma rollover price is referred to as the “rollover strength” of the price relative to the 20-sma. A large disparity between the current price and the rollover price suggests bearishness (negative rollover strength) if the rollover price is overhead because price would need to travel all that distance in order to cause the moving average to roll up. If the rollover price and price are converging, as is often the case, a change in moving average and price direction becomes more plausible. The rollover strengths of the 20-sma and 50-sma are added together to calculate the Rollover Strength and if a negative number is the result then the background color of the plot cloud turns red. If the result is positive, it turns green. Rollover Strength is plotted below price as a separate indicator in this publication for reference only and it's not part of this indicator. It does not look much different from momentum indicators. The code is below if anybody wants to try to use it. The important thing is that the distances between the rollover prices and the price action are kept in mind as having shrinking, growing, or neutral bearish and bullish effects on current and forecasted price direction. Trades should not be entered based on cloud colorization changes alone.
If you are about to crash into a wall of the 20-sma rollover price, as is indicated on the chart by the green arrow, you might consider going long so long as the rollover strength, both current and forecasted, of the 50-sma isn’t questionably bearish. This is subject to analysis and interpretation. There was a 20-sma rollover wall as indicated with yellow arrow, but the bearish rollover strength of the 50-sma was growing and forecasted to remain strong for a while at that time so a long entry would have not been suggested by both rollover prices. If you are about to crash into both the 20-sma and 50-sma rollover prices at the same time (not shown on this chart), that’s a good time to place a trade in anticipation of both slopes changing direction. You may, in the case of this chart, see that a 20-sma rollover wall precedes a 50-sma rollover convergence with price and anticipate a cascade which turned out to be the case with this recent NQ rally.
Price exiting the cloud entirely to either the upside or downside has strong implications. When exiting to the downside, the 20-sma and 50-sma have both rolled over and price is below both of them. The same is true for upside exits. Re-entering the cloud after a rally may indicate a reversal is near, especially if the forecasted rollover prices, particularly the 50-sma, agree.
This indicator should be used in conjunction with other technical analysis tools.
Additional Notes:
The original version of this script which will not be published was much heavier, cluttered, and is not as useful. This is the light version, hence the “LTE” suffix.
LTE stands for “long-term evolution” in telecommunications, not “light.”
Bar colorization (red, yellow, and green bars) was added using the MACD Hybrid BSH script which is another script I’ve published.
If you’re not sure what a bar is, it’s the same thing as a candle or a data point on a line chart. Every vertical line showing price action on the chart above is a bar and it is a bar chart.
sma = simple moving average
Rollover Strength Script:
// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © Skipper86
//@version=5
indicator(title="Rollover Strength", shorttitle="Rollover Strength", overlay=false)
source = input.source(close)
length1 = input.int(20, "Length 1", minval=1)
length2 = input.int(50, "Length 2", minval=1)
RolloverPrice1 = source
RolloverPrice2 = source
RolloverStrength1 = source-RolloverPrice1
RolloverStrength2 = source-RolloverPrice2
RolloverStrength = RolloverStrength1 + RolloverStrength2
Color1 = color.rgb(155, 155, 155, 0)
Color2 = color.rgb(0, 0, 200, 0)
Color3 = color.rgb(0, 200, 0, 0)
plot(RolloverStrength, title="Rollover Strength", color=Color3)
hline(0, "Middle Band", color=Color1)
//End of Rollover Strength Script
Keltner Channel Enhanced [DCAUT]█ Keltner Channel Enhanced
📊 ORIGINALITY & INNOVATION
The Keltner Channel Enhanced represents an important advancement over standard Keltner Channel implementations by introducing dual flexibility in moving average selection for both the middle band and ATR calculation. While traditional Keltner Channels typically use EMA for the middle band and RMA (Wilder's smoothing) for ATR, this enhanced version provides access to 25+ moving average algorithms for both components, enabling traders to fine-tune the indicator's behavior to match specific market characteristics and trading approaches.
Key Advancements:
Dual MA Algorithm Flexibility: Independent selection of moving average types for middle band (25+ options) and ATR smoothing (25+ options), allowing optimization of both trend identification and volatility measurement separately
Enhanced Trend Sensitivity: Ability to use faster algorithms (HMA, T3) for middle band while maintaining stable volatility measurement with traditional ATR smoothing, or vice versa for different trading strategies
Adaptive Volatility Measurement: Choice of ATR smoothing algorithm affects channel responsiveness to volatility changes, from highly reactive (SMA, EMA) to smoothly adaptive (RMA, TEMA)
Comprehensive Alert System: Five distinct alert conditions covering breakouts, trend changes, and volatility expansion, enabling automated monitoring without constant chart observation
Multi-Timeframe Compatibility: Works effectively across all timeframes from intraday scalping to long-term position trading, with independent optimization of trend and volatility components
This implementation addresses key limitations of standard Keltner Channels: fixed EMA/RMA combination may not suit all market conditions or trading styles. By decoupling the trend component from volatility measurement and allowing independent algorithm selection, traders can create highly customized configurations for specific instruments and market phases.
📐 MATHEMATICAL FOUNDATION
Keltner Channel Enhanced uses a three-component calculation system that combines a flexible moving average middle band with ATR-based (Average True Range) upper and lower channels, creating volatility-adjusted trend-following bands.
Core Calculation Process:
1. Middle Band (Basis) Calculation:
The basis line is calculated using the selected moving average algorithm applied to the price source over the specified period:
basis = ma(source, length, maType)
Supported algorithms include EMA (standard choice, trend-biased), SMA (balanced and symmetric), HMA (reduced lag), WMA, VWMA, TEMA, T3, KAMA, and 17+ others.
2. Average True Range (ATR) Calculation:
ATR measures market volatility by calculating the average of true ranges over the specified period:
trueRange = max(high - low, abs(high - close ), abs(low - close ))
atrValue = ma(trueRange, atrLength, atrMaType)
ATR smoothing algorithm significantly affects channel behavior, with options including RMA (standard, very smooth), SMA (moderate smoothness), EMA (fast adaptation), TEMA (smooth yet responsive), and others.
3. Channel Calculation:
Upper and lower channels are positioned at specified multiples of ATR from the basis:
upperChannel = basis + (multiplier × atrValue)
lowerChannel = basis - (multiplier × atrValue)
Standard multiplier is 2.0, providing channels that dynamically adjust width based on market volatility.
Keltner Channel vs. Bollinger Bands - Key Differences:
While both indicators create volatility-based channels, they use fundamentally different volatility measures:
Keltner Channel (ATR-based):
Uses Average True Range to measure actual price movement volatility
Incorporates gaps and limit moves through true range calculation
More stable in trending markets, less prone to extreme compression
Better reflects intraday volatility and trading range
Typically fewer band touches, making touches more significant
More suitable for trend-following strategies
Bollinger Bands (Standard Deviation-based):
Uses statistical standard deviation to measure price dispersion
Based on closing prices only, doesn't account for intraday range
Can compress significantly during consolidation (squeeze patterns)
More touches in ranging markets
Better suited for mean-reversion strategies
Provides statistical probability framework (95% within 2 standard deviations)
Algorithm Combination Effects:
The interaction between middle band MA type and ATR MA type creates different indicator characteristics:
Trend-Focused Configuration (Fast MA + Slow ATR): Middle band uses HMA/EMA/T3, ATR uses RMA/TEMA, quick trend changes with stable channel width, suitable for trend-following
Volatility-Focused Configuration (Slow MA + Fast ATR): Middle band uses SMA/WMA, ATR uses EMA/SMA, stable trend with dynamic channel width, suitable for volatility trading
Balanced Configuration (Standard EMA/RMA): Classic Keltner Channel behavior, time-tested combination, suitable for general-purpose trend following
Adaptive Configuration (KAMA + KAMA): Self-adjusting indicator responding to efficiency ratio, suitable for markets with varying trend strength and volatility regimes
📊 COMPREHENSIVE SIGNAL ANALYSIS
Keltner Channel Enhanced provides multiple signal categories optimized for trend-following and breakout strategies.
Channel Position Signals:
Upper Channel Interaction:
Price Touching Upper Channel: Strong bullish momentum, price moving more than typical volatility range suggests, potential continuation signal in established uptrends
Price Breaking Above Upper Channel: Exceptional strength, price exceeding normal volatility expectations, consider adding to long positions or tightening trailing stops
Price Riding Upper Channel: Sustained strong uptrend, characteristic of powerful bull moves, stay with trend and avoid premature profit-taking
Price Rejection at Upper Channel: Momentum exhaustion signal, consider profit-taking on longs or waiting for pullback to middle band for reentry
Lower Channel Interaction:
Price Touching Lower Channel: Strong bearish momentum, price moving more than typical volatility range suggests, potential continuation signal in established downtrends
Price Breaking Below Lower Channel: Exceptional weakness, price exceeding normal volatility expectations, consider adding to short positions or protecting against further downside
Price Riding Lower Channel: Sustained strong downtrend, characteristic of powerful bear moves, stay with trend and avoid premature covering
Price Rejection at Lower Channel: Momentum exhaustion signal, consider covering shorts or waiting for bounce to middle band for reentry
Middle Band (Basis) Signals:
Trend Direction Confirmation:
Price Above Basis: Bullish trend bias, middle band acts as dynamic support in uptrends, consider long positions or holding existing longs
Price Below Basis: Bearish trend bias, middle band acts as dynamic resistance in downtrends, consider short positions or avoiding longs
Price Crossing Above Basis: Potential trend change from bearish to bullish, early signal to establish long positions
Price Crossing Below Basis: Potential trend change from bullish to bearish, early signal to establish short positions or exit longs
Pullback Trading Strategy:
Uptrend Pullback: Price pulls back from upper channel to middle band, finds support, and resumes upward, ideal long entry point
Downtrend Bounce: Price bounces from lower channel to middle band, meets resistance, and resumes downward, ideal short entry point
Basis Test: Strong trends often show price respecting the middle band as support/resistance on pullbacks
Failed Test: Price breaking through middle band against trend direction signals potential reversal
Volatility-Based Signals:
Narrow Channels (Low Volatility):
Consolidation Phase: Channels contract during periods of reduced volatility and directionless price action
Breakout Preparation: Narrow channels often precede significant directional moves as volatility cycles
Trading Approach: Reduce position sizes, wait for breakout confirmation, avoid range-bound strategies within channels
Breakout Direction: Monitor for price breaking decisively outside channel range with expanding width
Wide Channels (High Volatility):
Trending Phase: Channels expand during strong directional moves and increased volatility
Momentum Confirmation: Wide channels confirm genuine trend with substantial volatility backing
Trading Approach: Trend-following strategies excel, wider stops necessary, mean-reversion strategies risky
Exhaustion Signs: Extreme channel width (historical highs) may signal approaching consolidation or reversal
Advanced Pattern Recognition:
Channel Walking Pattern:
Upper Channel Walk: Price consistently touches or exceeds upper channel while staying above basis, very strong uptrend signal, hold longs aggressively
Lower Channel Walk: Price consistently touches or exceeds lower channel while staying below basis, very strong downtrend signal, hold shorts aggressively
Basis Support/Resistance: During channel walks, price typically uses middle band as support/resistance on minor pullbacks
Pattern Break: Price crossing basis during channel walk signals potential trend exhaustion
Squeeze and Release Pattern:
Squeeze Phase: Channels narrow significantly, price consolidates near middle band, volatility contracts
Direction Clues: Watch for price positioning relative to basis during squeeze (above = bullish bias, below = bearish bias)
Release Trigger: Price breaking outside narrow channel range with expanding width confirms breakout
Follow-Through: Measure squeeze height and project from breakout point for initial profit targets
Channel Expansion Pattern:
Breakout Confirmation: Rapid channel widening confirms volatility increase and genuine trend establishment
Entry Timing: Enter positions early in expansion phase before trend becomes overextended
Risk Management: Use channel width to size stops appropriately, wider channels require wider stops
Basis Bounce Pattern:
Clean Bounce: Price touches middle band and immediately reverses, confirms trend strength and entry opportunity
Multiple Bounces: Repeated basis bounces indicate strong, sustainable trend
Bounce Failure: Price penetrating basis signals weakening trend and potential reversal
Divergence Analysis:
Price/Channel Divergence: Price makes new high/low while staying within channel (not reaching outer band), suggests momentum weakening
Width/Price Divergence: Price breaks to new extremes but channel width contracts, suggests move lacks conviction
Reversal Signal: Divergences often precede trend reversals or significant consolidation periods
Multi-Timeframe Analysis:
Keltner Channels work particularly well in multi-timeframe trend-following approaches:
Three-Timeframe Alignment:
Higher Timeframe (Weekly/Daily): Identify major trend direction, note price position relative to basis and channels
Intermediate Timeframe (Daily/4H): Identify pullback opportunities within higher timeframe trend
Lower Timeframe (4H/1H): Time precise entries when price touches middle band or lower channel (in uptrends) with rejection
Optimal Entry Conditions:
Best Long Entries: Higher timeframe in uptrend (price above basis), intermediate timeframe pulls back to basis, lower timeframe shows rejection at middle band or lower channel
Best Short Entries: Higher timeframe in downtrend (price below basis), intermediate timeframe bounces to basis, lower timeframe shows rejection at middle band or upper channel
Risk Management: Use higher timeframe channel width to set position sizing, stops below/above higher timeframe channels
🎯 STRATEGIC APPLICATIONS
Keltner Channel Enhanced excels in trend-following and breakout strategies across different market conditions.
Trend Following Strategy:
Setup Requirements:
Identify established trend with price consistently on one side of basis line
Wait for pullback to middle band (basis) or brief penetration through it
Confirm trend resumption with price rejection at basis and move back toward outer channel
Enter in trend direction with stop beyond basis line
Entry Rules:
Uptrend Entry:
Price pulls back from upper channel to middle band, shows support at basis (bullish candlestick, momentum divergence)
Enter long on rejection/bounce from basis with stop 1-2 ATR below basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Downtrend Entry:
Price bounces from lower channel to middle band, shows resistance at basis (bearish candlestick, momentum divergence)
Enter short on rejection/reversal from basis with stop 1-2 ATR above basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Trend Management:
Trailing Stop: Use basis line as dynamic trailing stop, exit if price closes beyond basis against position
Profit Taking: Take partial profits at opposite channel, move stops to basis
Position Additions: Add to winners on subsequent basis bounces if trend intact
Breakout Strategy:
Setup Requirements:
Identify consolidation period with contracting channel width
Monitor price action near middle band with reduced volatility
Wait for decisive breakout beyond channel range with expanding width
Enter in breakout direction after confirmation
Breakout Confirmation:
Price breaks clearly outside channel (upper for longs, lower for shorts), channel width begins expanding from contracted state
Volume increases significantly on breakout (if using volume analysis)
Price sustains outside channel for multiple bars without immediate reversal
Entry Approaches:
Aggressive: Enter on initial break with stop at opposite channel or basis, use smaller position size
Conservative: Wait for pullback to broken channel level, enter on rejection and resumption, tighter stop
Volatility-Based Position Sizing:
Adjust position sizing based on channel width (ATR-based volatility):
Wide Channels (High ATR): Reduce position size as stops must be wider, calculate position size using ATR-based risk calculation: Risk / (Stop Distance in ATR × ATR Value)
Narrow Channels (Low ATR): Increase position size as stops can be tighter, be cautious of impending volatility expansion
ATR-Based Risk Management: Use ATR-based risk calculations, position size = 0.01 × Capital / (2 × ATR), use multiples of ATR (1-2 ATR) for adaptive stops
Algorithm Selection Guidelines:
Different market conditions benefit from different algorithm combinations:
Strong Trending Markets: Middle band use EMA or HMA, ATR use RMA, capture trends quickly while maintaining stable channel width
Choppy/Ranging Markets: Middle band use SMA or WMA, ATR use SMA or WMA, avoid false trend signals while identifying genuine reversals
Volatile Markets: Middle band and ATR both use KAMA or FRAMA, self-adjusting to changing market conditions reduces manual optimization
Breakout Trading: Middle band use SMA, ATR use EMA or SMA, stable trend with dynamic channels highlights volatility expansion early
Scalping/Day Trading: Middle band use HMA or T3, ATR use EMA or TEMA, both components respond quickly
Position Trading: Middle band use EMA/TEMA/T3, ATR use RMA or TEMA, filter out noise for long-term trend-following
📋 DETAILED PARAMETER CONFIGURATION
Understanding and optimizing parameters is essential for adapting Keltner Channel Enhanced to specific trading approaches.
Source Parameter:
Close (Most Common): Uses closing price, reflects daily settlement, best for end-of-day analysis and position trading, standard choice
HL2 (Median Price): Smooths out closing bias, better represents full daily range in volatile markets, good for swing trading
HLC3 (Typical Price): Gives more weight to close while including full range, popular for intraday applications, slightly more responsive than HL2
OHLC4 (Average Price): Most comprehensive price representation, smoothest option, good for gap-prone markets or highly volatile instruments
Length Parameter:
Controls the lookback period for middle band (basis) calculation:
Short Periods (10-15): Very responsive to price changes, suitable for day trading and scalping, higher false signal rate
Standard Period (20 - Default): Represents approximately one month of trading, good balance between responsiveness and stability, suitable for swing and position trading
Medium Periods (30-50): Smoother trend identification, fewer false signals, better for position trading and longer holding periods
Long Periods (50+): Very smooth, identifies major trends only, minimal false signals but significant lag, suitable for long-term investment
Optimization by Timeframe: 1-15 minute charts use 10-20 period, 30-60 minute charts use 20-30 period, 4-hour to daily charts use 20-40 period, weekly charts use 20-30 weeks.
ATR Length Parameter:
Controls the lookback period for Average True Range calculation, affecting channel width:
Short ATR Periods (5-10): Very responsive to recent volatility changes, standard is 10 (Keltner's original specification), may be too reactive in whipsaw conditions
Standard ATR Period (10 - Default): Chester Keltner's original specification, good balance between responsiveness and stability, most widely used
Medium ATR Periods (14-20): Smoother channel width, ATR 14 aligns with Wilder's original ATR specification, good for position trading
Long ATR Periods (20+): Very smooth channel width, suitable for long-term trend-following
Length vs. ATR Length Relationship: Equal values (20/20) provide balanced responsiveness, longer ATR (20/14) gives more stable channel width, shorter ATR (20/10) is standard configuration, much shorter ATR (20/5) creates very dynamic channels.
Multiplier Parameter:
Controls channel width by setting ATR multiples:
Lower Values (1.0-1.5): Tighter channels with frequent price touches, more trading signals, higher false signal rate, better for range-bound and mean-reversion strategies
Standard Value (2.0 - Default): Chester Keltner's recommended setting, good balance between signal frequency and reliability, suitable for both trending and ranging strategies
Higher Values (2.5-3.0): Wider channels with less frequent touches, fewer but potentially higher-quality signals, better for strong trending markets
Market-Specific Optimization: High volatility markets (crypto, small-caps) use 2.5-3.0 multiplier, medium volatility markets (major forex, large-caps) use 2.0 multiplier, low volatility markets (bonds, utilities) use 1.5-2.0 multiplier.
MA Type Parameter (Middle Band):
Critical selection that determines trend identification characteristics:
EMA (Exponential Moving Average - Default): Standard Keltner Channel choice, Chester Keltner's original specification, emphasizes recent prices, faster response to trend changes, suitable for all timeframes
SMA (Simple Moving Average): Equal weighting of all data points, no directional bias, slower than EMA, better for ranging markets and mean-reversion
HMA (Hull Moving Average): Minimal lag with smooth output, excellent for fast trend identification, best for day trading and scalping
TEMA (Triple Exponential Moving Average): Advanced smoothing with reduced lag, responsive to trends while filtering noise, suitable for volatile markets
T3 (Tillson T3): Very smooth with minimal lag, excellent for established trend identification, suitable for position trading
KAMA (Kaufman Adaptive Moving Average): Automatically adjusts speed based on market efficiency, slow in ranging markets, fast in trends, suitable for markets with varying conditions
ATR MA Type Parameter:
Determines how Average True Range is smoothed, affecting channel width stability:
RMA (Wilder's Smoothing - Default): J. Welles Wilder's original ATR smoothing method, very smooth, slow to adapt to volatility changes, provides stable channel width
SMA (Simple Moving Average): Equal weighting, moderate smoothness, faster response to volatility changes than RMA, more dynamic channel width
EMA (Exponential Moving Average): Emphasizes recent volatility, quick adaptation to new volatility regimes, very responsive channel width changes
TEMA (Triple Exponential Moving Average): Smooth yet responsive, good balance for varying volatility, suitable for most trading styles
Parameter Combination Strategies:
Conservative Trend-Following: Length 30/ATR Length 20/Multiplier 2.5, MA Type EMA or TEMA/ATR MA Type RMA, smooth trend with stable wide channels, suitable for position trading
Standard Balanced Approach: Length 20/ATR Length 10/Multiplier 2.0, MA Type EMA/ATR MA Type RMA, classic Keltner Channel configuration, suitable for general purpose swing trading
Aggressive Day Trading: Length 10-15/ATR Length 5-7/Multiplier 1.5-2.0, MA Type HMA or EMA/ATR MA Type EMA or SMA, fast trend with dynamic channels, suitable for scalping and day trading
Breakout Specialist: Length 20-30/ATR Length 5-10/Multiplier 2.0, MA Type SMA or WMA/ATR MA Type EMA or SMA, stable trend with responsive channel width
Adaptive All-Conditions: Length 20/ATR Length 10/Multiplier 2.0, MA Type KAMA or FRAMA/ATR MA Type KAMA or TEMA, self-adjusting to market conditions
Offset Parameter:
Controls horizontal positioning of channels on chart. Positive values shift channels to the right (future) for visual projection, negative values shift left (past) for historical analysis, zero (default) aligns with current price bars for real-time signal analysis. Offset affects only visual display, not alert conditions or actual calculations.
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Keltner Channel Enhanced provides improvements over standard implementations while maintaining proven effectiveness.
Response Characteristics:
Standard EMA/RMA Configuration: Moderate trend lag (approximately 0.4 × length periods), smooth and stable channel width from RMA smoothing, good balance for most market conditions
Fast HMA/EMA Configuration: Approximately 60% reduction in trend lag compared to EMA, responsive channel width from EMA ATR smoothing, suitable for quick trend changes and breakouts
Adaptive KAMA/KAMA Configuration: Variable lag based on market efficiency, automatic adjustment to trending vs. ranging conditions, self-optimizing behavior reduces manual intervention
Comparison with Traditional Keltner Channels:
Enhanced Version Advantages:
Dual Algorithm Flexibility: Independent MA selection for trend and volatility vs. fixed EMA/RMA, separate tuning of trend responsiveness and channel stability
Market Adaptation: Choose configurations optimized for specific instruments and conditions, customize for scalping, swing, or position trading preferences
Comprehensive Alerts: Enhanced alert system including channel expansion detection
Traditional Version Advantages:
Simplicity: Fewer parameters, easier to understand and implement
Standardization: Fixed EMA/RMA combination ensures consistency across users
Research Base: Decades of backtesting and research on standard configuration
When to Use Enhanced Version: Trading multiple instruments with different characteristics, switching between trending and ranging markets, employing different strategies, algorithm-based trading systems requiring customization, seeking optimization for specific trading style and timeframe.
When to Use Standard Version: Beginning traders learning Keltner Channel concepts, following published research or trading systems, preferring simplicity and standardization, wanting to avoid optimization and curve-fitting risks.
Performance Across Market Conditions:
Strong Trending Markets: EMA or HMA basis with RMA or TEMA ATR smoothing provides quicker trend identification, pullbacks to basis offer excellent entry opportunities
Choppy/Ranging Markets: SMA or WMA basis with RMA ATR smoothing and lower multipliers, channel bounce strategies work well, avoid false breakouts
Volatile Markets: KAMA or FRAMA with EMA or TEMA, adaptive algorithms excel by automatic adjustment, wider multipliers (2.5-3.0) accommodate large price swings
Low Volatility/Consolidation: Channels narrow significantly indicating consolidation, algorithm choice less impactful, focus on detecting channel width contraction for breakout preparation
Keltner Channel vs. Bollinger Bands - Usage Comparison:
Favor Keltner Channels When: Trend-following is primary strategy, trading volatile instruments with gaps, want ATR-based volatility measurement, prefer fewer higher-quality channel touches, seeking stable channel width during trends.
Favor Bollinger Bands When: Mean-reversion is primary strategy, trading instruments with limited gaps, want statistical framework based on standard deviation, need squeeze patterns for breakout identification, prefer more frequent trading opportunities.
Use Both Together: Bollinger Band squeeze + Keltner Channel breakout is powerful combination, price outside Bollinger Bands but inside Keltner Channels indicates moderate signal, price outside both indicates very strong signal, Bollinger Bands for entries and Keltner Channels for trend confirmation.
Limitations and Considerations:
General Limitations:
Lagging Indicator: All moving averages lag price, even with reduced-lag algorithms
Trend-Dependent: Works best in trending markets, less effective in choppy conditions
No Direction Prediction: Indicates volatility and deviation, not future direction, requires confirmation
Enhanced Version Specific Considerations:
Optimization Risk: More parameters increase risk of curve-fitting historical data
Complexity: Additional choices may overwhelm beginning traders
Backtesting Challenges: Different algorithms produce different historical results
Mitigation Strategies:
Use Confirmation: Combine with momentum indicators (RSI, MACD), volume, or price action
Test Parameter Robustness: Ensure parameters work across range of values, not just optimized ones
Multi-Timeframe Analysis: Confirm signals across different timeframes
Proper Risk Management: Use appropriate position sizing and stops
Start Simple: Begin with standard EMA/RMA before exploring alternatives
Optimal Usage Recommendations:
For Maximum Effectiveness:
Start with standard EMA/RMA configuration to understand classic behavior
Experiment with alternatives on demo account or paper trading
Match algorithm combination to market condition and trading style
Use channel width analysis to identify market phases
Combine with complementary indicators for confirmation
Implement strict risk management using ATR-based position sizing
Focus on high-quality setups rather than trading every signal
Respect the trend: trade with basis direction for higher probability
Complementary Indicators:
RSI or Stochastic: Confirm momentum at channel extremes
MACD: Confirm trend direction and momentum shifts
Volume: Validate breakouts and trend strength
ADX: Measure trend strength, avoid Keltner signals in weak trends
Support/Resistance: Combine with traditional levels for high-probability setups
Bollinger Bands: Use together for enhanced breakout and volatility analysis
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Keltner Channel Enhanced has limitations and should not be used as the sole basis for trading decisions. While the flexible moving average selection for both trend and volatility components provides valuable adaptability across different market conditions, algorithm performance varies with market conditions, and past characteristics do not guarantee future results.
Key considerations:
Always use multiple forms of analysis and confirmation before entering trades
Backtest any parameter combination thoroughly before live trading
Be aware that optimization can lead to curve-fitting if not done carefully
Start with standard EMA/RMA settings and adjust only when specific conditions warrant
Understand that no moving average algorithm can eliminate lag entirely
Consider market regime (trending, ranging, volatile) when selecting parameters
Use ATR-based position sizing and risk management on every trade
Keltner Channels work best in trending markets, less effective in choppy conditions
Respect the trend direction indicated by price position relative to basis line
The enhanced flexibility of dual algorithm selection provides powerful tools for adaptation but requires responsible use, thorough understanding of how different algorithms behave under various market conditions, and disciplined risk management.
Adv EMA Cloud v6 (ADX, Alerts)Summary:
This indicator provides a multi-faceted view of market trends using Exponential Moving Averages (EMAs) arranged in visually intuitive clouds, enhanced with an optional ADX-based range filter and configurable alerts for key market conditions. It aims to help traders quickly gauge trend alignment across short, medium, and long timeframes while filtering signals during potentially choppy market conditions.
Key Features:
Multiple EMAs: Displays 10-period (Fast), 20-period (Mid), and 50-period (Slow) EMAs.
Long-Term Trend Filter: Includes a 200-period EMA to provide context for the overall dominant trend direction.
Dual EMA Clouds:
Fast/Mid Cloud (10/20 EMA): Fills the area between the 10 and 20 EMAs. Defaults to Green when 10 > 20 (bullish short-term momentum) and Red when 10 < 20 (bearish short-term momentum).
Mid/Slow Cloud (20/50 EMA): Fills the area between the 20 and 50 EMAs. Defaults to Aqua when 20 > 50 (bullish mid-term trend) and Fuchsia when 20 < 50 (bearish mid-term trend).
Optional ADX Range Filter: Uses the Average Directional Index (ADX) to identify potentially non-trending or choppy markets. When enabled and ADX falls below a user-defined threshold, the EMA clouds will turn grey, visually warning that trend-following signals may be less reliable.
Configurable Alerts: Provides several built-in alert conditions using Pine Script's alertcondition function:
Confluence Condition: Triggers when a 10/20 EMA crossover occurs while both EMA clouds show alignment (both bullish/green/aqua or both bearish/red/fuchsia) and price respects the 200 EMA filter and the ADX filter indicates a trend (if filters are enabled).
MA Filter Cross: Triggers when price crosses above or below the 200 EMA filter line.
Full Alignment Start: Triggers on the first bar where full bullish or bearish alignment occurs (both clouds aligned + MA filter respected + ADX trending, if filters are enabled).
How It Works:
EMA Calculation: Standard Exponential Moving Averages are calculated for the 10, 20, 50, and 200 periods based on the closing price.
Cloud Creation: The fill() function visually shades the area between the 10 & 20 EMAs and the 20 & 50 EMAs.
Cloud Coloring: The color of each cloud is determined by the relationship between the two EMAs that define it (e.g., if EMA 10 is above EMA 20, the first cloud is bullish-colored).
ADX Filter Logic: The script calculates the ADX value. If the "Use ADX Trend Filter?" input is checked and the calculated ADX is below the specified "ADX Trend Threshold", the script considers the market potentially ranging.
ADX Visual Effect: During detected ranging periods (if the ADX filter is active), the plotCloud12Color and plotCloud23Color variables are assigned a neutral grey color instead of their normal bullish/bearish colors before being passed to the fill() function.
Alert Logic: Boolean variables track the specific conditions (crossovers, cloud alignment, filter positions, ADX state). The alertcondition() function creates triggerable alerts based on these pre-defined conditions.
Potential Interpretation (Not Financial Advice):
Trend Alignment: When both clouds share the same directional color (e.g., both bullish - Green & Aqua) and price is on the corresponding side of the 200 EMA filter, it may suggest a stronger, more aligned trend. Conversely, conflicting cloud colors may indicate indecision or transition.
Dynamic Support/Resistance: The EMA lines themselves (especially the 20, 50, and 200) can sometimes act as dynamic levels where price might react.
Range Warning: Greyed-out clouds (when ADX filter is enabled) serve as a visual warning that trend-based strategies might face increased difficulty or whipsaws.
Confluence Alerts: The specific confluence alerts signal moments where multiple conditions align (crossover + cloud agreement + filters), which some traders might view as higher-probability setups.
Customization:
All EMA lengths (10, 20, 50, 200) are adjustable via the Inputs menu.
The ADX length and threshold are configurable.
The MA Trend Filter and ADX Trend Filter can be independently enabled or disabled.
Disclaimer:
This indicator is provided for informational and educational purposes only. Trading financial markets involves significant risk. Past performance is not indicative of future results. Always conduct your own thorough analysis and consider your risk tolerance before making any trading decisions. This indicator should be used in conjunction with other analysis methods and tools. Do not trade based solely on the signals or visuals provided by this indicator.
Trend Gazer v5# Trend Gazer v5: Professional Multi-Timeframe ICT Analysis System
## 📊 Overview
**Trend Gazer v5** is a comprehensive institutional-grade trading system that synthesizes multiple proven methodologies into a unified analytical framework. This indicator combines **ICT (Inner Circle Trader) concepts**, **Smart Money Structure**, **Order Block detection**, **Fair Value Gaps**, and **volumetric analysis** to provide traders with high-probability trade setups backed by institutional footprints.
Unlike fragmented indicators that force traders to switch between multiple tools, Trend Gazer v5 delivers a **holistic market view** in a single overlay, eliminating analysis paralysis and enabling confident decision-making.
---
## 🎯 Why This Combination is Necessary
### The Problem with Single-Concept Indicators
Traditional indicators suffer from three critical flaws:
1. **Isolated Context** - Price action, volume, and structure are analyzed separately, creating conflicting signals
2. **Timeframe Blindness** - Single-timeframe analysis misses institutional activity occurring across multiple timeframes
3. **Lagging Confirmation** - Waiting for one indicator to confirm another causes missed entries and late exits
### The Institutional Trading Reality
Professional traders and institutions operate across **multiple dimensions simultaneously**:
- **Structural Context**: Where are we in the market cycle? (CHoCH, SiMS, BoMS)
- **Order Flow**: Where is institutional supply and demand concentrated? (Order Blocks)
- **Inefficiencies**: Where are price imbalances that must be filled? (Fair Value Gaps)
- **Momentum Context**: Is volume expanding or contracting? (VWC/TBOSI)
- **Mean Reversion Points**: Where do institutions expect rebounds? (NPR/BB, EMAs)
**Trend Gazer v5 unifies these dimensions**, creating a complete picture of market microstructure that individual indicators cannot provide.
---
## 🔬 Core Analytical Framework
### 1️⃣ ICT Donchian Smart Money Structure
**Purpose**: Identify institutional market structure shifts that precede major moves.
**Components**:
- **CHoCH (Change of Character)** - Market structure break signaling trend exhaustion
- `1.CHoCH` (Bullish) - Lower low broken, shift to bullish structure
- `A.CHoCH` (Bearish) - Higher high broken, shift to bearish structure
- **SiMS (Shift in Market Structure)** - Initial structure shift (2nd occurrence)
- **BoMS (Break of Market Structure)** - Continuation structure (3rd+ occurrence)
**Why It's Essential**:
Retail traders react to price changes. Institutions **create** price changes by breaking structure. By detecting these shifts using **Donchian channels** (the purest form of high/low tracking), we identify the exact moments when institutional bias changes.
**Credit**: Based on *ICT Donchian Smart Money Structure* by Zeiierman (CC BY-NC-SA 4.0)
---
### 2️⃣ Multi-Timeframe Order Block Detection
**Purpose**: Map institutional supply/demand zones where price is likely to reverse.
**Methodology**:
Order Blocks represent the **last opposite-direction candle** before a strong move. These zones indicate where institutions accumulated (bullish OB) or distributed (bearish OB) positions.
**Multi-Timeframe Coverage**:
- **1-minute**: Scalping zones for day traders
- **3-minute**: Short-term swing zones
- **15-minute**: Intraday institutional zones
- **60-minute**: Daily swing zones
- **Current TF**: Dynamic adaptation to any chart timeframe
**Key Features**:
- **Bounce Detection** - Identifies when price rebounds from OB zones (Signal 7: 🎯 OB Bounce)
- **Breaker Tracking** - Monitors when OBs are violated, converting bullish OBs to resistance and vice versa
- **Visual Rendering** - Color-coded boxes with transparency showing OB strength
- **OB Direction Filter** - Blocks contradictory signals (no SELL in bullish OB, no BUY in bearish OB)
**Why MTF Order Blocks Matter**:
A 60-minute Order Block represents institutional positioning at a larger timeframe. When combined with a 3-minute entry signal, you're trading **with** the big players, not against them.
---
### 3️⃣ Fair Value Gap (FVG) Detection
**Purpose**: Identify price inefficiencies that institutional traders must eventually fill.
**What Are FVGs?**:
Fair Value Gaps occur when price moves so rapidly that it leaves an **imbalance** - a gap between the high of one candle and the low of the candle two bars later (or vice versa). Institutions view these as inefficient pricing that must be corrected.
**Detection Logic**:
```
Bullish FVG: high < low → Gap up = Bearish imbalance (expect downward fill)
Bearish FVG: low > high → Gap down = Bullish imbalance (expect upward fill)
```
**Visual Design**:
- **Bullish FVG**: Green boxes (support zones where price should bounce)
- **Bearish FVG**: Red boxes (resistance zones where price should reject)
- **Mitigation Tracking**: FVGs disappear when filled, signaling completion
- **Volume Attribution**: Each FVG tracks associated buying/selling volume
**Why FVGs Are Critical**:
Institutions operate on **efficiency**. Gaps represent inefficiency. When price returns to fill a gap, it's not random - it's institutional traders **correcting market inefficiency**. Trading into FVG fills offers exceptional risk/reward.
---
### 4️⃣ Volumetric Weighted Cloud (VWC/TBOSI)
**Purpose**: Detect momentum shifts and trend strength using volume-weighted price action.
**Mechanism**:
VWC applies **volatility weighting** to moving averages, creating a dynamic cloud that expands during high-volatility trends and contracts during consolidation.
**Multi-Timeframe Analysis**:
- **1m, 3m, 5m**: Micro-scalping momentum
- **15m**: Intraday trend confirmation
- **60m, 240m**: Swing trade trend validation
**Signal Generation**:
- **VWC Switch (Signal 2)**: When cloud color flips (red → green or green → red), indicating momentum reversal
- **VWC Status Table**: Real-time display of trend direction across all timeframes
**Why Volume-Weighting Matters**:
Traditional moving averages treat all bars equally. VWC gives **more weight to high-volume bars**, ensuring that signals reflect actual institutional participation, not low-volume noise.
---
### 5️⃣ Non-Repaint STDEV (NPR) & Bollinger Bands
**Purpose**: Identify extreme mean-reversion points without repainting.
**Problem with Traditional Indicators**:
Many indicators **repaint** - they change past values when new data arrives, making backtests misleading. NPR uses **lookahead bias prevention** to ensure signals remain fixed.
**Configuration**:
- **15-minute NPR/BB**: Intraday volatility bands
- **60-minute NPR/BB**: Swing trade extremes
- **Multiple Kernel Options**: Exponential, Simple, Double Exponential, Triple Exponential for different smoothing profiles
**Signal Logic (Signal 8)**:
- **BUY**: Price closes **inside** lower band (not just touching it) → Extreme oversold with institutional absorption likely
- **SELL**: Price closes **inside** upper band → Extreme overbought with institutional distribution likely
**Why NPR is Superior**:
Repainting indicators give traders false confidence in backtests. NPR ensures every signal you see in history is **exactly** what a trader would have seen in real-time.
---
### 6️⃣ 💎 STRONG CHoCH Pattern Detection
**Purpose**: Identify the highest-probability setups when multiple CHoCH confirmations align within a tight timeframe.
**Pattern Logic**:
**STRONG BUY Pattern**:
```
1.CHoCH → A.CHoCH → 1.CHoCH (within 20 bars)
```
This sequence indicates:
1. Initial bullish structure shift
2. Bearish retest (pullback)
3. **Renewed bullish confirmation** - Institutions are re-accumulating after shaking out weak hands
**STRONG SELL Pattern**:
```
A.CHoCH → 1.CHoCH → A.CHoCH (within 20 bars)
```
This sequence indicates:
1. Initial bearish structure shift
2. Bullish retest (dead cat bounce)
3. **Renewed bearish confirmation** - Institutions are re-distributing after trapping longs
**Visual Display**:
```
💎 BUY
```
- **0% transparency** (fully opaque) - Maximum visual priority
- Displayed **immediately** when pattern completes (no additional signal required)
- Independent of Market Structure filter (pattern itself is the confirmation)
**Why STRONG Signals Are Different**:
- **Triple Confirmation**: Three structure shifts eliminate false breakouts
- **Tight Timeframe**: 20-bar window ensures institutional conviction, not random noise
- **Automatic Display**: No waiting for price action - the pattern itself triggers the alert
- **Historical Validation**: This specific sequence has proven to precede major institutional moves
**Risk Management**:
STRONG signals offer the best risk/reward because:
1. Stop loss can be placed beyond the middle CHoCH (tight risk)
2. Target can be set at next major structure level (large reward)
3. Pattern failure is immediately evident (quick exit if wrong)
---
### 7️⃣ Multi-EMA Framework
**Purpose**: Provide dynamic support/resistance and trend context.
**EMA Configuration**:
- **EMA 7**: Micro-trend (scalping)
- **EMA 20**: Short-term trend
- **EMA 50**: Institutional pivot (Signal 6: EMA50 Bounce)
- **EMA 100**: Mid-term trend filter
- **EMA 200**: Major institutional support/resistance
- **EMA 400, 800**: Macro trend context
**Visual Fills**:
- Color-coded fills between EMAs create **visual trend strength zones**
- Convergence = consolidation
- Divergence = trending market
**Why 7 EMAs?**:
Each EMA represents a different **participant timeframe**:
- EMA 7/20: Day traders and scalpers
- EMA 50/100: Swing traders
- EMA 200/400/800: Position traders and institutions
When all EMAs align, **all participant types agree on direction** - the highest-probability trend trades.
---
## 🚀 8-Signal Trading System
Trend Gazer v5 employs **8 distinct signal conditions** (all enabled by default), each designed to capture different market regimes:
### ⭐ Signal Hierarchy & Trading Philosophy
**IMPORTANT**: Not all signals are created equal. The indicator displays a hierarchy of signal quality:
**PRIMARY SIGNALS (Trade These)**:
- 💎 **STRONG BUY/SELL** - Triple-confirmed CHoCH patterns (highest priority)
- 🌟 **Star Signals (S7, S8)** - High-probability institutional zone reactions
- Signal 7: Order Block Bounce
- Signal 8: 60m NPR/BB Bounce
**AUXILIARY SIGNALS (Confirmation & Context)**:
- **Signals 1-6** - Use these as:
- **Confirmation** for Star Signals (when multiple signals align)
- **Context** for understanding market conditions
- **Early warnings** of potential moves (validate before trading)
- **Additional filters** (e.g., "only trade Star Signals that also have Signal 1")
**Trading Recommendation**:
- **Conservative Traders**: Trade ONLY 💎 STRONG and 🌟 Star Signals
- **Moderate Traders**: Trade Star Signals + validated auxiliary signals (2+ signal confirmation)
- **Active Traders**: Use all signals with proper risk management
The visual transparency system reinforces this hierarchy:
- 0% transparent = STRONG (💎) - Highest conviction
- 50% transparent = Star (🌟) + OB signals - High quality
- 70% transparent = Auxiliary (S1-S6) - Supplementary information
### Signal 1: RSI Shift + Structure (AND Logic)
**Strictest Signal** - Requires both RSI momentum confirmation AND structure change.
- **Use Case**: High-conviction trades in trending markets
- **Frequency**: Least frequent, highest accuracy
### Signal 2: VWC Switch (OR Logic)
**Most Frequent Signal** - Triggers on any VWC color flip across monitored timeframes.
- **Use Case**: Capturing early momentum shifts
- **Frequency**: Most frequent, good for active traders
### Signal 3: Structure Change
**Bar Color Change with RSI Confirmation** - Detects when candle color shifts with supporting RSI.
- **Use Case**: Trend continuation trades
- **Frequency**: Moderate
### Signal 4: BB Breakout + RSI
**Bollinger Band Breakout Reversal** - Price breaks band then immediately reverses.
- **Use Case**: Fade false breakouts
- **Frequency**: Moderate, excellent risk/reward
### Signal 5: BB/EMA50 Break
**Aggressive Breakout Signal** - Price breaks both BB and EMA50 simultaneously.
- **Use Case**: Momentum breakout trades
- **Frequency**: Moderate-high
### Signal 6: EMA50 Bounce Reversal
**Mean Reversion at EMA50** - Price touches EMA50 and bounces.
- **Use Case**: Trading pullbacks in strong trends
- **Frequency**: Moderate, reliable
### Signal 7: 🌟 OB Bounce (Star Signal)
**Order Block Bounce** - Price enters OB zone and reverses.
- **Use Case**: Institutional zone reactions
- **Frequency**: Low, but extremely high quality
- **Special Features**:
- 🎯 **OB Bounce Label**: `🌟 🎯 BUY/SELL ` - Actual Signal 7 bounce from visible OB
- 📍 **In OB Label**: `📍 BUY/SELL ` - Other signals (S1-6, S8) occurring inside an OB zone
- **OB Direction Filter**: Blocks contradictory signals (no SELL in bullish OB, no BUY in bearish OB)
### Signal 8: 🌟 60m NPR/BB Bounce (Star Signal)
**Extreme Mean-Reversion** - Price closes **inside** 60m NPR/BB bands at extremes.
- **Use Case**: Capturing institutional absorption at extremes
- **Frequency**: Low, exceptional win rate
- **Special Logic**: Candle close must be **INSIDE** bands, not just touching (prevents false breakouts)
### 💎 STRONG Signals (Bonus)
**CHoCH Pattern Completion** - Triple-confirmed structure shifts.
- **STRONG BUY**: `1.CHoCH → A.CHoCH → 1.CHoCH (≤20 bars)`
- **STRONG SELL**: `A.CHoCH → 1.CHoCH → A.CHoCH (≤20 bars)`
- **Display**: Immediate upon pattern completion (independent signal)
- **Use Case**: Highest-conviction institutional trend shifts
---
## 🎨 Visual Design Philosophy
### Signal Hierarchy via Transparency
**0% Transparency (Opaque)**:
- 💎 **STRONG BUY/SELL** - Highest priority, institutional pattern confirmation
**50% Transparency**:
- 🌟 **Star Signals** (S7, S8) - High-quality mean reversion
- 🎯 **OB Bounce** - Institutional zone reaction
- 📍 **In OB** - Enhanced signal in institutional zone
- **CHoCH Labels** (1.CHoCH, A.CHoCH) - Structure shift markers
**70% Transparency**:
- **Regular Signals** (S1-S6) - Standard trade setups
This visual hierarchy ensures traders **instantly recognize** high-priority setups without analysis paralysis.
### Color Scheme: Japanese Candlestick Convention
**Bullish = Red | Bearish = Blue/Green**
This follows traditional Japanese candlestick methodology where:
- **Red (Yang)**: Positive energy, rising prices, bullish
- **Blue/Green (Yin)**: Negative energy, falling prices, bearish
While Western conventions often reverse this, we maintain **ICT and institutional conventions** for consistency with professional trading rooms.
---
## 📡 Alert System
### Any Alert (Automatic)
**8 Events Monitored**:
1. 💎 **STRONG BUY** - Pattern: `1.CHoCH → A.CHoCH → 1.CHoCH`
2. 💎 **STRONG SELL** - Pattern: `A.CHoCH → 1.CHoCH → A.CHoCH`
3. ⭐ **Star BUY** - Signal 7 or 8
4. ⭐ **Star SELL** - Signal 7 or 8
5. 📍 **BUY (in OB)** - Any signal inside Bullish Order Block
6. 📍 **SELL (in OB)** - Any signal inside Bearish Order Block
7. **Bullish CHoCH** - Market structure shift to bullish
8. **Bearish CHoCH** - Market structure shift to bearish
**Format**: `TICKER TIMEFRAME EventName`
**Example**: `BTCUSDT 5 💎 STRONG BUY`
### Individual alertcondition() Options
Create custom alerts for specific events:
- BUY/SELL Signals (all or filtered)
- Star Signals Only (S7/S8)
- STRONG Signals Only (💎)
- CHoCH Events Only
- Bullish/Bearish CHoCH separately
---
## ⚙️ Configuration & Settings
### ICT Structure Filter (DEFAULT ON ⭐)
**Enable Structure Filter**: Display signals ONLY after CHoCH/SiMS/BoMS
- **Purpose**: Filter out noise by requiring institutional confirmation
- **Recommendation**: Keep enabled for disciplined trading
**Show Structure Labels (DEFAULT ON ⭐)**: Display CHoCH/SiMS/BoMS labels
- **Purpose**: Visual confirmation of market structure state
- **Labels**:
- `1.CHoCH` (Red background, white text) - Bullish structure shift
- `A.CHoCH` (Blue background, white text) - Bearish structure shift
- `2.SMS` / `B.SMS` (Red/Blue text) - Shift in Market Structure (2nd occurrence)
- `3.BMS` / `C.BMS` (Red/Blue text) - Break of Market Structure (3rd+ occurrence)
**Structure Period**: Default 3 bars (ICT standard)
### Order Block Configuration
**Enable Multi-Timeframe OBs**: Detect OBs from multiple timeframes simultaneously
**Mitigation Options**:
- Close - OB invalidated when candle closes through it
- Wick - OB invalidated when wick touches it
- 50% - OB invalidated when 50% of zone is violated
**Show OBs from**:
- Current Timeframe (always)
- 1m, 3m, 15m, 60m (selectable)
### Fair Value Gap Settings
**Show FVGs**: Enable/disable FVG rendering
**Mitigation Source**: Wick, Close, or 50% fill
**Color Customization**: Bullish FVG (green), Bearish FVG (red)
### Signal Filters
**Show ONLY Star Signals (DEFAULT OFF)**:
- When ON: Display only S7 (OB Bounce) and S8 (NPR/BB Bounce)
- When OFF: Display all signals S1-S8 (DEFAULT)
- **Use Case**: Focus on highest-quality setups, ignore noise
### Visual Settings
**EMA Display**: Toggle individual EMAs on/off
**VWC Cloud**: Enable/disable volumetric cloud
**NPR/BB Bands**: Show/hide 15m and 60m bands
**Status Table**: Real-time VWC status across all timeframes
---
## 📚 How to Use
### For Scalpers (1m-5m Charts)
1. Enable **1m and 3m Order Blocks**
2. Watch for **Signal 2 (VWC Switch)** or **Signal 5 (BB/EMA50 Break)**
3. Confirm with **1m/3m MTF OB** as support/resistance
4. Use **FVGs** for micro-target setting
5. Set alerts for **Star BUY/SELL** for highest-quality scalps
### For Day Traders (15m-60m Charts)
1. Enable **15m and 60m Order Blocks**
2. Wait for **CHoCH** to establish bias
3. Trade **Signal 7 (OB Bounce)** or **Signal 8 (60m NPR/BB Bounce)**
4. Use **EMA 50/100** as dynamic stop placement
5. Set alerts for **💎 STRONG BUY/SELL** for major moves
### For Swing Traders (4H-Daily Charts)
1. Enable **60m Order Blocks** (will render as larger zones on HTF)
2. Wait for **Market Structure confirmation** (CHoCH)
3. Focus on **Signal 1 (RSI Shift + Structure)** for highest conviction
4. Use **EMA 200/400/800** for macro trend alignment
5. Set alerts for **Bullish/Bearish CHoCH** to catch structure shifts early
### Universal Strategy (Recommended Approach)
1. **Focus on Primary Signals First** - Build your track record with 💎 STRONG and 🌟 Star Signals only
2. **Wait for Market Structure** - Never trade against CHoCH direction
3. **Use Auxiliary Signals for Confirmation** - When a Star Signal appears, check if auxiliary signals (S1-6) also confirm
4. **Respect Order Blocks** - Fade signals that contradict OB direction
5. **Use FVGs for Targets** - Price gravitates toward unfilled gaps
6. **Gradually Incorporate Auxiliary Signals** - Once profitable with primary signals, experiment with validated auxiliary setups
### Signal Quality Statistics (Typical Observation)
Based on common market behavior patterns:
**💎 STRONG Signals**:
- Frequency: Rare (1-3 per week on daily charts)
- Win Rate: Very High (70-85% when proper risk management applied)
- Risk/Reward: Excellent (1:3 to 1:5+ typical)
**🌟 Star Signals (S7, S8)**:
- Frequency: Moderate (2-5 per day on lower timeframes)
- Win Rate: High (60-75% when aligned with structure)
- Risk/Reward: Good (1:2 to 1:4 typical)
**Auxiliary Signals (S1-6)**:
- Frequency: High (multiple per hour on active timeframes)
- Win Rate: Moderate (50-65% standalone, higher when used as confirmation)
- Risk/Reward: Variable (1:1 to 1:3 typical)
**Key Insight**: Trading only primary signals reduces trade frequency but dramatically improves consistency and psychological ease.
---
## 🏆 What Makes This Indicator Unique
### 1. **True Multi-Timeframe Integration**
Most "MTF" indicators simply display data from other timeframes. Trend Gazer v5 **synthesizes** MTF data into unified signals, eliminating conflicting information.
### 2. **Non-Repainting Architecture**
All signals are fixed at bar close. What you see in backtests is exactly what you'd see in real-time.
### 3. **Institutional Focus**
Every component is designed around institutional behavior:
- Where they accumulate (Order Blocks)
- When they shift (CHoCH)
- What they must fix (FVGs)
- How they create momentum (VWC)
### 4. **Complete Transparency**
- **Open Source** - Full code visibility
- **Credited Sources** - All borrowed concepts attributed
- **No Black Boxes** - Every calculation is documented
### 5. **Flexible Yet Focused**
- **8 Signal Types** - Adapts to any market regime
- **Default Settings Optimized** - Works immediately without tweaking
- **Optional Filters** - "Show ONLY Star Signals" for disciplined traders
### 6. **Professional Alert System**
- **8-event Any Alert** - Never miss institutional moves
- **Individual alertconditions** - Customize to your strategy
- **Formatted Messages** - Ticker + Timeframe + Event for instant context
---
## 📖 Educational Value
### Learning ICT Concepts
This indicator serves as a **visual teaching tool** for:
- **Market Structure**: See CHoCH/SiMS/BoMS in real-time
- **Order Blocks**: Understand where institutions positioned
- **Fair Value Gaps**: Learn how inefficiencies are filled
- **Smart Money Behavior**: Watch institutional footprints unfold
### Backtesting & Strategy Development
Use Trend Gazer v5 to:
1. **Validate ICT Concepts** - Do OB bounces really work? Test it.
2. **Optimize Entry Timing** - Which signals work best in your market?
3. **Develop Filters** - Combine signals for your edge
4. **Build Strategies** - Export signals to Pine Script strategies
---
## ⚠️ Disclaimer
This indicator is for **educational and informational purposes only**. It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
**Trading involves substantial risk of loss**. Past performance is not indicative of future results. No indicator, regardless of sophistication, can guarantee profitable trades.
**Always:**
- Conduct your own research
- Use proper risk management (1-2% risk per trade)
- Consult with qualified financial advisors
- Practice on paper/demo accounts before live trading
- Understand that you are solely responsible for your trading decisions
---
## 🔗 Credits & Licenses
### Original Code Sources
1. **ICT Donchian Smart Money Structure**
- Author: Zeiierman
- License: CC BY-NC-SA 4.0
- Modifications: Integrated with multi-signal system, added CHoCH pattern detection
2. **Reverse RSI Signals**
- Author: AlgoAlpha
- License: MPL 2.0
- Modifications: Adapted for internal signal logic
3. **Volumetric Weighted Cloud (VWC/TBOSI)**
- Original concept adapted for multi-timeframe analysis
- Enhanced with MTF table display
4. **Order Block & FVG Detection**
- Based on ICT concepts
- Custom implementation with MTF support
### This Indicator's License
**Mozilla Public License 2.0 (MPL 2.0)**
You are free to:
- ✅ Use commercially
- ✅ Modify and distribute
- ✅ Use privately
- ✅ Patent use
Under conditions:
- 📄 Disclose source
- 📄 License and copyright notice
- 📄 Same license for modifications
---
## 📞 Support & Community
### Reporting Issues
If you encounter bugs or have feature suggestions, please provide:
1. Chart timeframe and symbol
2. Settings configuration
3. Screenshot of the issue
4. Expected vs actual behavior
### Best Practices
- Start with default settings
- Gradually enable/disable features to understand each component
- Use demo account for at least 30 days before live trading
- Combine with proper risk management
---
## 🚀 Version History
### v5.0 - Simplified ICT Mode (Current)
- ✅ Removed all unused filters and features
- ✅ Enabled all 8 signals by default
- ✅ Added 💎 STRONG CHoCH pattern detection
- ✅ Enhanced OB Bounce labeling system
- ✅ Added FVG detection and visualization
- ✅ Improved alert system (8 events)
- ✅ Optimized performance (faster rendering)
- ✅ Added comprehensive DESCRIPTION documentation
### v4.2 - ICT Mode with EMA Convergence Filter (Deprecated)
- Legacy version with EMA convergence features (removed for simplicity)
### v4.0 - Pure ICT Mode (Deprecated)
- Initial ICT-focused release
---
## 🎓 Recommended Learning Resources
To fully leverage this indicator, study:
1. **ICT Concepts** (Inner Circle Trader - YouTube)
- Market Structure
- Order Blocks
- Fair Value Gaps
- Liquidity Concepts
2. **Smart Money Concepts (SMC)**
- Change of Character (CHoCH)
- Break of Structure (BOS)
- Liquidity Sweeps
3. **Volume Spread Analysis (VSA)**
- Effort vs Result
- Supply vs Demand
- Volume Climax
4. **Risk Management**
- Position Sizing
- R-Multiple Theory
- Win Rate vs Risk/Reward Balance
---
## ✅ Quick Start Checklist
- Add indicator to chart
- Verify **Enable Structure Filter** is ON
- Verify **Show Structure Labels** is ON
- Enable desired MTF Order Blocks (1m, 3m, 15m, 60m)
- Enable FVG display
- Set up **Any Alert** for all 8 events
- Paper trade for 30 days minimum
- Document your trades (screenshots + notes)
- Review performance weekly
- Adjust filters based on your strategy
---
## 💡 Final Thoughts
**Trend Gazer v5 is not a "magic button" indicator.** It's a professional analytical framework that requires education, practice, and discipline.
The best traders don't use indicators to **tell them what to do**. They use indicators to **confirm what they already see** in price action.
Use this tool to:
- ✅ Confirm your analysis
- ✅ Filter out low-probability setups
- ✅ Identify institutional footprints
- ✅ Time entries with precision
Avoid using it to:
- ❌ Trade blindly without understanding context
- ❌ Ignore risk management
- ❌ Revenge trade after losses
- ❌ Replace education with automation
**Trade smart. Trade safe. Trade with structure.**
---
**© rasukaru666 | 2025 | Mozilla Public License 2.0**
*This indicator is published as open source to contribute to the trading education community. If it helps you, please share your experience and help others learn.*
------------------------------------------------------
# Trend Gazer v5: プロフェッショナル・マルチタイムフレームICT分析システム
## 📊 概要
**Trend Gazer v5** は、複数の実証済み手法を統合した分析フレームワークを提供する、包括的な機関投資家グレードの取引システムです。このインジケーターは、**ICT（Inner Circle Trader）コンセプト**、**スマートマネー構造**、**オーダーブロック検知**、**フェアバリューギャップ**、および**出来高分析**を組み合わせて、機関投資家の足跡に裏打ちされた高確率の取引セットアップをトレーダーに提供します。
断片的なインジケーターは、トレーダーに複数のツールを切り替えることを強いますが、Trend Gazer v5は**包括的な市場ビュー**を単一のオーバーレイで提供し、分析麻痺を排除して自信ある意思決定を可能にします。
---
## 🎯 なぜこの組み合わせが必要なのか
### 単一コンセプトインジケーターの問題点
従来のインジケーターは3つの致命的な欠陥を抱えています：
1. **孤立したコンテキスト** - 価格、出来高、構造が個別に分析され、矛盾するシグナルを生成
2. **タイムフレームの盲目性** - 単一タイムフレーム分析は、複数のタイムフレームで発生する機関投資家の活動を見逃す
3. **遅れた確認** - あるインジケーターが別のインジケーターの確認を待つことで、エントリーを逃し、エグジットが遅れる
### 機関投資家の取引実態
プロのトレーダーや機関投資家は、**複数の次元を同時に**操作します：
- **構造的コンテキスト**: 市場サイクルのどこにいるのか？（CHoCH、SiMS、BoMS）
- **オーダーフロー**: 機関投資家の需要と供給が集中しているのはどこか？（オーダーブロック）
- **非効率性**: 埋めなければならない価格の不均衡はどこか？（フェアバリューギャップ）
- **モメンタムコンテキスト**: 出来高は拡大しているか縮小しているか？（VWC/TBOSI）
- **平均回帰ポイント**: 機関投資家がリバウンドを期待する場所はどこか？（NPR/BB、EMA）
**Trend Gazer v5はこれらの次元を統合**し、個別のインジケーターでは提供できない市場マイクロ構造の完全な全体像を作成します。
---
## 🔬 コア分析フレームワーク
### 1️⃣ ICT ドンチャン・スマートマネー構造
**目的**: 大きな動きに先行する機関投資家の市場構造シフトを識別する。
**コンポーネント**:
- **CHoCH (Change of Character / 性質の変化)** - トレンド疲弊を示す市場構造のブレイク
- `1.CHoCH`（強気） - 直近安値のブレイク、強気構造へのシフト
- `A.CHoCH`（弱気） - 直近高値のブレイク、弱気構造へのシフト
- **SiMS (Shift in Market Structure / 市場構造のシフト)** - 初期構造シフト（2回目の発生）
- **BoMS (Break of Market Structure / 市場構造のブレイク)** - 継続構造（3回目以降の発生）
**なぜ不可欠なのか**:
小売トレーダーは価格変化に反応します。機関投資家は構造を破ることで価格変化を**作り出します**。**ドンチャンチャネル**（高値/安値追跡の最も純粋な形式）を使用してこれらのシフトを検出することで、機関投資家のバイアスが変化する正確な瞬間を特定します。
**クレジット**: Zeiierman氏の*ICT Donchian Smart Money Structure*に基づく（CC BY-NC-SA 4.0）
---
### 2️⃣ マルチタイムフレーム・オーダーブロック検知
**目的**: 価格が反転する可能性が高い機関投資家の需給ゾーンをマッピングする。
**方法論**:
オーダーブロックは、強い動きの前の**最後の反対方向ローソク足**を表します。これらのゾーンは、機関投資家がポジションを蓄積（強気OB）または分配（弱気OB）した場所を示します。
**マルチタイムフレームカバレッジ**:
- **1分足**: デイトレーダー向けスキャルピングゾーン
- **3分足**: 短期スイングゾーン
- **15分足**: イントラデイ機関投資家ゾーン
- **60分足**: デイリースイングゾーン
- **現在のTF**: 任意のチャートタイムフレームへの動的適応
**主要機能**:
- **バウンス検知** - OBゾーンから価格がリバウンドする時を識別（シグナル7: 🎯 OBバウンス）
- **ブレーカー追跡** - OBが破られた時を監視し、強気OBを抵抗に、弱気OBをサポートに変換
- **ビジュアルレンダリング** - OBの強度を示す透明度付きの色分けされたボックス
- **OB方向フィルター** - 矛盾するシグナルをブロック（強気OBでSELLなし、弱気OBでBUYなし）
**なぜMTFオーダーブロックが重要か**:
60分足のオーダーブロックは、より大きなタイムフレームでの機関投資家のポジショニングを表します。3分足のエントリーシグナルと組み合わせることで、大口プレイヤーと**同じ方向**で取引することになります。
---
### 3️⃣ フェアバリューギャップ（FVG）検知
**目的**: 機関投資家が最終的に埋めなければならない価格の非効率性を識別する。
**FVGとは何か？**:
フェアバリューギャップは、価格があまりにも急速に動いて**不均衡**を残す時に発生します - 1本のローソク足の高値と2本後のローソク足の安値の間のギャップ（またはその逆）。機関投資家はこれらを修正されなければならない非効率的な価格設定と見なします。
**検知ロジック**:
```
強気FVG: high < low → ギャップアップ = 弱気の不均衡（下方フィル予想）
弱気FVG: low > high → ギャップダウン = 強気の不均衡（上方フィル予想）
```
**ビジュアルデザイン**:
- **強気FVG**: 緑のボックス（価格がバウンドすべきサポートゾーン）
- **弱気FVG**: 赤のボックス（価格が拒否されるべき抵抗ゾーン）
- **ミティゲーション追跡**: FVGは埋められると消え、完了を示す
- **出来高帰属**: 各FVGは関連する買い/売り出来高を追跡
**なぜFVGが重要か**:
機関投資家は**効率性**で動きます。ギャップは非効率性を表します。価格がギャップを埋めるために戻る時、それはランダムではありません - 機関投資家が**市場の非効率性を修正**しているのです。FVGフィルへの取引は卓越したリスク/リワードを提供します。
---
### 4️⃣ 出来高加重クラウド（VWC/TBOSI）
**目的**: 出来高加重プライスアクションを使用してモメンタムシフトとトレンド強度を検出する。
**メカニズム**:
VWCは移動平均に**ボラティリティ加重**を適用し、高ボラティリティトレンド中に拡大し、コンソリデーション中に縮小する動的クラウドを作成します。
**マルチタイムフレーム分析**:
- **1m、3m、5m**: マイクロスキャルピングモメンタム
- **15m**: イントラデイトレンド確認
- **60m、240m**: スイングトレードトレンド検証
**シグナル生成**:
- **VWCスイッチ（シグナル2）**: クラウドの色が反転した時（赤→緑または緑→赤）、モメンタム反転を示す
- **VWCステータステーブル**: 全タイムフレームのトレンド方向のリアルタイム表示
**なぜ出来高加重が重要か**:
従来の移動平均はすべてのバーを等しく扱います。VWCは**高出来高バーに重みを与え**、シグナルが低出来高のノイズではなく、実際の機関投資家の参加を反映することを保証します。
---
### 5️⃣ ノンリペイントSTDEV（NPR）＆ボリンジャーバンド
**目的**: リペイントなしで極端な平均回帰ポイントを識別する。
**従来のインジケーターの問題点**:
多くのインジケーターは**リペイント**します - 新しいデータが到着すると過去の値を変更し、バックテストを誤解させます。NPRは**先読みバイアス防止**を使用して、シグナルが固定されたままであることを保証します。
**設定**:
- **15分足NPR/BB**: イントラデイボラティリティバンド
- **60分足NPR/BB**: スイングトレード極値
- **複数のカーネルオプション**: 指数、単純、二重指数、三重指数 - 異なる平滑化プロファイル
**シグナルロジック（シグナル8）**:
- **BUY**: 価格が下部バンドの**内側**でクローズ（触れるだけではない）→ 極端な売られ過ぎで機関投資家の吸収が可能性高い
- **SELL**: 価格が上部バンドの**内側**でクローズ → 極端な買われ過ぎで機関投資家の分配が可能性高い
**なぜNPRが優れているか**:
リペイントインジケーターはトレーダーにバックテストで誤った自信を与えます。NPRは、履歴で見るすべてのシグナルが、トレーダーがリアルタイムで見たであろうもの**そのもの**であることを保証します。
---
### 6️⃣ 💎 STRONG CHoChパターン検知
**目的**: 短い時間枠内で複数のCHoCH確認が整列した時の最高確率セットアップを識別する。
**パターンロジック**:
**STRONG BUYパターン**:
```
1.CHoCH → A.CHoCH → 1.CHoCH（20バー以内）
```
このシーケンスは以下を示します：
1. 初期強気構造シフト
2. 弱気リテスト（プルバック）
3. **更新された強気確認** - 機関投資家は弱い手を振り落とした後に再蓄積中
**STRONG SELLパターン**:
```
A.CHoCH → 1.CHoCH → A.CHoCH（20バー以内）
```
このシーケンスは以下を示します：
1. 初期弱気構造シフト
2. 強気リテスト（デッドキャットバウンス）
3. **更新された弱気確認** - 機関投資家はロングを罠にかけた後に再分配中
**ビジュアル表示**:
```
💎 BUY
```
- **0%透明度**（完全不透明） - 最大の視覚的優先度
- パターン完成時に**即座に**表示（追加シグナル不要）
- 市場構造フィルターから独立（パターン自体が確認）
**なぜSTRONGシグナルが異なるか**:
- **三重確認**: 3つの構造シフトが誤ったブレイクアウトを排除
- **短い時間枠**: 20バーウィンドウがランダムなノイズではなく、機関投資家の確信を保証
- **自動表示**: 価格アクションを待たない - パターン自体がアラートをトリガー
- **歴史的検証**: この特定のシーケンスは主要な機関投資家の動きに先行することが証明されている
**リスク管理**:
STRONGシグナルは最高のリスク/リワードを提供します：
1. ストップロスは中央のCHoCHの外に配置可能（タイトなリスク）
2. ターゲットは次の主要構造レベルに設定可能（大きなリワード）
3. パターン失敗は即座に明らか（間違っていればクイックエグジット）
---
### 7️⃣ マルチEMAフレームワーク
**目的**: ダイナミックなサポート/レジスタンスとトレンドコンテキストを提供する。
**EMA設定**:
- **EMA 7**: マイクロトレンド（スキャルピング）
- **EMA 20**: 短期トレンド
- **EMA 50**: 機関投資家のピボット（シグナル6: EMA50バウンス）
- **EMA 100**: 中期トレンドフィルター
- **EMA 200**: 主要な機関投資家のサポート/レジスタンス
- **EMA 400、800**: マクロトレンドコンテキスト
**ビジュアルフィル**:
- EMA間の色分けされたフィルが**ビジュアルトレンド強度ゾーン**を作成
- 収束 = コンソリデーション
- 発散 = トレンド市場
**なぜ7つのEMAか？**:
各EMAは異なる**参加者タイムフレーム**を表します：
- EMA 7/20: デイトレーダーとスキャルパー
- EMA 50/100: スイングトレーダー
- EMA 200/400/800: ポジショントレーダーと機関投資家
すべてのEMAが整列した時、**すべての参加者タイプが方向に同意**している - 最高確率のトレンド取引です。
---
## 🚀 8シグナル取引システム
Trend Gazer v5は**8つの異なるシグナル条件**（すべてデフォルトで有効）を採用しており、それぞれが異なる市場レジームを捕捉するように設計されています：
### ⭐ シグナル階層＆取引哲学
**重要**: すべてのシグナルが同じではありません。インジケーターはシグナル品質の階層を表示します：
**プライマリーシグナル（これを取引する）**:
- 💎 **STRONG BUY/SELL** - 三重CHoChパターン（最優先）
- 🌟 **スターシグナル（S7、S8）** - 高確率の機関投資家ゾーン反応
- シグナル7: オーダーブロックバウンス
- シグナル8: 60m NPR/BBバウンス
**補助シグナル（確認とコンテキスト）**:
- **シグナル1-6** - これらを以下として使用：
- スターシグナルの**確認**（複数のシグナルが整列した時）
- 市場状況を理解するための**コンテキスト**
- 潜在的な動きの**早期警告**（取引前に検証）
- **追加フィルター**（例：「シグナル1も出ているスターシグナルのみ取引」）
**取引推奨**:
- **保守的トレーダー**: 💎 STRONGと🌟スターシグナル**のみ**取引
- **中程度トレーダー**: スターシグナル + 検証された補助シグナル（2+シグナル確認）
- **アクティブトレーダー**: 適切なリスク管理ですべてのシグナルを使用
視覚的透明度システムはこの階層を強化します：
- 0%透明度 = STRONG（💎） - 最高の確信
- 50%透明度 = スター（🌟）+ OBシグナル - 高品質
- 70%透明度 = 補助（S1-S6） - 補足情報
### シグナル1: RSIシフト + 構造（ANDロジック）
**最も厳格なシグナル** - RSIモメンタム確認と構造変化の両方が必要。
- **使用例**: トレンド市場での高確信取引
- **頻度**: 最も少ない、最高の精度
- **分類**:
### シグナル2: VWCスイッチ（ORロジック）
**最も頻繁なシグナル** - 監視されているタイムフレームでのVWC色反転でトリガー。
- **使用例**: 早期モメンタムシフトの捕捉
- **頻度**: 最も頻繁、アクティブトレーダーに適している
- **分類**:
### シグナル3: 構造変化
**バーカラー変化とRSI確認** - RSIサポートでローソク足の色がシフトする時を検出。
- **使用例**: トレンド継続取引
- **頻度**: 中程度
- **分類**:
### シグナル4: BBブレイクアウト + RSI
**ボリンジャーバンドブレイクアウト反転** - 価格がバンドを破った後すぐに反転。
- **使用例**: 誤ったブレイクアウトをフェード
- **頻度**: 中程度、優れたリスク/リワード
- **分類**:
### シグナル5: BB/EMA50ブレイク
**積極的ブレイクアウトシグナル** - 価格がBBとEMA50を同時にブレイク。
- **使用例**: モメンタムブレイクアウト取引
- **頻度**: 中〜高
- **分類**:
### シグナル6: EMA50バウンス反転
**EMA50での平均回帰** - 価格がEMA50に触れてバウンス。
- **使用例**: 強いトレンドでのプルバック取引
- **頻度**: 中程度、信頼性あり
- **分類**:
### シグナル7: 🌟 OBバウンス（スターシグナル）
**オーダーブロックバウンス** - 価格がOBゾーンに入って反転。
- **使用例**: 機関投資家ゾーン反応
- **頻度**: 低いが、極めて高品質
- **分類**:
- **特別機能**:
- 🎯 **OBバウンスラベル**: `🌟 🎯 BUY/SELL ` - 可視OBからの実際のシグナル7バウンス
- 📍 **In OBラベル**: `📍 BUY/SELL ` - OBゾーン内で発生する他のシグナル（S1-6、S8）
- **OB方向フィルター**: 矛盾するシグナルをブロック（強気OBでSELLなし、弱気OBでBUYなし）
### シグナル8: 🌟 60m NPR/BBバウンス（スターシグナル）
**極端な平均回帰** - 価格が60m NPR/BBバンドの極値で**内側に**クローズ。
- **使用例**: 極値での機関投資家の吸収を捕捉
- **頻度**: 低い、卓越した勝率
- **分類**:
- **特別ロジック**: ローソク足のクローズがバンドの**内側**でなければならない（触れるだけではダメ、誤ったブレイクアウトを防止）
### 💎 STRONGシグナル（ボーナス）
**CHoChパターン完成** - 三重確認された構造シフト。
- **STRONG BUY**: `1.CHoCH → A.CHoCH → 1.CHoCH（≤20バー）`
- **STRONG SELL**: `A.CHoCH → 1.CHoCH → A.CHoCH（≤20バー）`
- **表示**: パターン完成時に即座（独立したシグナル）
- **分類**:
- **使用例**: 最高確信の機関投資家トレンドシフト
---
## 🎨 ビジュアルデザイン哲学
### 透明度によるシグナル階層
**0%透明度（不透明）**:
- 💎 **STRONG BUY/SELL** - 最優先、機関投資家パターン確認
**50%透明度**:
- 🌟 **スターシグナル**（S7、S8） - 高品質平均回帰
- 🎯 **OBバウンス** - 機関投資家ゾーン反応
- 📍 **In OB** - 機関投資家ゾーン内の強化されたシグナル
- **CHoChラベル**（1.CHoCH、A.CHoCH） - 構造シフトマーカー
**70%透明度**:
- **通常シグナル**（S1-S6） - 標準取引セットアップ
この視覚的階層により、トレーダーは分析麻痺なしに高優先度セットアップを**即座に認識**できます。
### カラースキーム: 日本式ローソク足慣例
**強気 = 赤 | 弱気 = 青/緑**
これは伝統的な日本式ローソク足方法論に従います：
- **赤（陽）**: ポジティブエネルギー、上昇価格、強気
- **青/緑（陰）**: ネガティブエネルギー、下降価格、弱気
西洋の慣例はしばしばこれを逆にしますが、プロの取引ルームとの一貫性のために**ICTと機関投資家の慣例**を維持します。
---
## 📡 アラートシステム
### Any Alert（自動）
**8つのイベントを監視**:
1. 💎 **STRONG BUY** - パターン: `1.CHoCH → A.CHoCH → 1.CHoCH`
2. 💎 **STRONG SELL** - パターン: `A.CHoCH → 1.CHoCH → A.CHoCH`
3. ⭐ **Star BUY** - シグナル7または8
4. ⭐ **Star SELL** - シグナル7または8
5. 📍 **BUY (in OB)** - 強気オーダーブロック内の任意のシグナル
6. 📍 **SELL (in OB)** - 弱気オーダーブロック内の任意のシグナル
7. **Bullish CHoCH** - 強気への市場構造シフト
8. **Bearish CHoCH** - 弱気への市場構造シフト
**フォーマット**: `TICKER TIMEFRAME EventName`
**例**: `BTCUSDT 5 💎 STRONG BUY`
### 個別alertcondition()オプション
特定のイベントのカスタムアラートを作成：
- BUY/SELLシグナル（すべてまたはフィルタリング）
- スターシグナルのみ（S7/S8）
- STRONGシグナルのみ（💎）
- CHoChイベントのみ
- 強気/弱気CHoCH個別
---
## ⚙️ 設定と設定
### ICT構造フィルター（デフォルトON ⭐）
**構造フィルターを有効化**: CHoCH/SiMS/BoMS後のシグナル**のみ**表示
- **目的**: 機関投資家の確認を要求することでノイズをフィルター
- **推奨**: 規律ある取引のために有効のままにする
**構造ラベルを表示（デフォルトON ⭐）**: CHoCH/SiMS/BoMSラベルを表示
- **目的**: 市場構造状態の視覚的確認
- **ラベル**:
- `1.CHoCH`（赤背景、白テキスト） - 強気構造シフト
- `A.CHoCH`（青背景、白テキスト） - 弱気構造シフト
- `2.SMS` / `B.SMS`（赤/青テキスト） - 市場構造のシフト（2回目）
- `3.BMS` / `C.BMS`（赤/青テキスト） - 市場構造のブレイク（3回目以降）
**構造期間**: デフォルト3バー（ICT標準）
### オーダーブロック設定
**マルチタイムフレームOBを有効化**: 複数のタイムフレームから同時にOBを検出
**ミティゲーションオプション**:
- Close - ローソク足がクローズで通過した時にOB無効化
- Wick - ウィックが触れた時にOB無効化
- 50% - ゾーンの50%が侵害された時にOB無効化
**OBを表示**:
- 現在のタイムフレーム（常に）
- 1m、3m、15m、60m（選択可能）
### フェアバリューギャップ設定
**FVGを表示**: FVGレンダリングを有効/無効
**ミティゲーションソース**: Wick、Close、または50%フィル
**カラーカスタマイゼーション**: 強気FVG（緑）、弱気FVG（赤）
### シグナルフィルター
**スターシグナルのみ表示（デフォルトOFF）**:
- ONの時: S7（OBバウンス）とS8（NPR/BBバウンス）のみ表示
- OFFの時: すべてのシグナルS1-S8を表示（デフォルト）
- **使用例**: 最高品質のセットアップに集中し、ノイズを無視
### ビジュアル設定
**EMA表示**: 個別のEMAをオン/オフ切り替え
**VWCクラウド**: 出来高クラウドを有効/無効
**NPR/BBバンド**: 15mと60mバンドを表示/非表示
**ステータステーブル**: すべてのタイムフレームでのリアルタイムVWCステータス
---
## 📚 使用方法
### スキャルパー向け（1m-5m チャート）
1. **1mと3mオーダーブロック**を有効化
2. **シグナル2（VWCスイッチ）**または**シグナル5（BB/EMA50ブレイク）**を監視
3. サポート/レジスタンスとして**1m/3m MTF OB**で確認
4. マイクロターゲット設定に**FVG**を使用
5. 最高品質のスキャルプのために**Star BUY/SELL**のアラートを設定
### デイトレーダー向け（15m-60m チャート）
1. **15mと60mオーダーブロック**を有効化
2. バイアスを確立するために**CHoCH**を待つ
3. **シグナル7（OBバウンス）**または**シグナル8（60m NPR/BBバウンス）**を取引
4. ダイナミックストップ配置に**EMA 50/100**を使用
5. 主要な動きのために**💎 STRONG BUY/SELL**のアラートを設定
### スイングトレーダー向け（4H-日足 チャート）
1. **60mオーダーブロック**を有効化（HTFでより大きなゾーンとしてレンダリング）
2. **市場構造確認**（CHoCH）を待つ
3. 最高確信のために**シグナル1（RSIシフト + 構造）**に集中
4. マクロトレンド整列のために**EMA 200/400/800**を使用
5. 構造シフトを早期に捕捉するために**Bullish/Bearish CHoCH**のアラートを設定
### ユニバーサル戦略（推奨アプローチ）
1. **まずプライマリーシグナルに集中** - 💎 STRONGと🌟スターシグナル**のみ**でトラックレコードを構築
2. **市場構造を待つ** - CHoCH方向に逆らって取引しない
3. **補助シグナルを確認に使用** - スターシグナルが現れたら、補助シグナル（S1-6）も確認するかチェック
4. **オーダーブロックを尊重** - OB方向と矛盾するシグナルをフェード
5. **ターゲットにFVGを使用** - 価格は埋められていないギャップに引き寄せられる
6. **徐々に補助シグナルを組み込む** - プライマリーシグナルで利益が出たら、検証された補助セットアップを実験
### シグナル品質統計（典型的な観察）
一般的な市場行動パターンに基づく：
**💎 STRONGシグナル**:
- 頻度: まれ（日足チャートで週1-3回）
- 勝率: 非常に高い（適切なリスク管理適用時70-85%）
- リスク/リワード: 優秀（典型的に1:3から1:5+）
**🌟 スターシグナル（S7、S8）**:
- 頻度: 中程度（短期足で1日2-5回）
- 勝率: 高い（構造と整列時60-75%）
- リスク/リワード: 良好（典型的に1:2から1:4）
**補助シグナル（S1-6）**:
- 頻度: 高い（活発なタイムフレームで1時間に複数回）
- 勝率: 中程度（単独で50-65%、確認として使用時はより高い）
- リスク/リワード: 変動（典型的に1:1から1:3）
**重要な洞察**: プライマリーシグナルのみの取引は取引頻度を減らしますが、一貫性と心理的容易さを劇的に改善します。
---
## 🏆 このインジケーターのユニークな点
### 1. **真のマルチタイムフレーム統合**
ほとんどの「MTF」インジケーターは単に他のタイムフレームからデータを表示するだけです。Trend Gazer v5はMTFデータを統一されたシグナルに**合成**し、矛盾する情報を排除します。
### 2. **ノンリペイント・アーキテクチャ**
すべてのシグナルはバークローズで固定されます。バックテストで見るものは、リアルタイムで見るであろうもの**そのもの**です。
### 3. **機関投資家フォーカス**
すべてのコンポーネントは機関投資家の行動を中心に設計されています：
- どこで蓄積するか（オーダーブロック）
- いつシフトするか（CHoCH）
- 何を修正しなければならないか（FVG）
- どのようにモメンタムを作り出すか（VWC）
### 4. **完全な透明性**
- **オープンソース** - 完全なコード可視性
- **クレジットされたソース** - すべての借用コンセプトが帰属
- **ブラックボックスなし** - すべての計算が文書化
### 5. **柔軟だが焦点を絞った**
- **8シグナルタイプ** - 任意の市場レジームに適応
- **最適化されたデフォルト設定** - 調整なしですぐに動作
- **オプションフィルター** - 規律あるトレーダーのための「スターシグナルのみ表示」
### 6. **プロフェッショナルアラートシステム**
- **8イベントAny Alert** - 機関投資家の動きを見逃さない
- **個別alertconditions** - あなたの戦略にカスタマイズ
- **フォーマットされたメッセージ** - 即座のコンテキストのためのTicker + Timeframe + Event
---
## 📖 教育的価値
### ICT概念の学習
このインジケーターは以下のための**視覚的教育ツール**として機能します：
- **市場構造**: CHoCH/SiMS/BoMSをリアルタイムで見る
- **オーダーブロック**: 機関投資家がどこでポジショニングしたかを理解
- **フェアバリューギャップ**: 非効率性がどのように埋められるかを学ぶ
- **スマートマネー行動**: 機関投資家の足跡が展開するのを観察
### バックテスティングと戦略開発
Trend Gazer v5を使用して：
1. **ICT概念を検証** - OBバウンスは本当に機能するか？テストする。
2. **エントリータイミングを最適化** - あなたの市場でどのシグナルが最も機能するか？
3. **フィルターを開発** - あなたのエッジのためにシグナルを組み合わせる
4. **戦略を構築** - シグナルをPine Scriptストラテジーにエクスポート
---
## ⚠️ 免責事項
このインジケーターは**教育および情報提供のみを目的**としています。金融アドバイスではありません。
**リスク警告**:
- 取引には重大な損失リスクが伴い、すべての投資家に適しているわけではありません
- 過去のパフォーマンスは将来の結果を**示すものではありません**
- どのインジケーターも利益ある取引を保証することはできません
- あなたは自分の取引決定に対して単独で責任を負います
**取引前に**:
- 自分自身の調査とデューデリジェンスを実施
- 資格のある金融アドバイザーに相談
- 適切なリスク管理を使用（取引あたり1-2%以上リスクを取らない）
- ライブ取引前にペーパー/デモアカウントで練習
- 損失は取引の一部であることを理解
このインジケーターによって提供される情報は、投資アドバイス、金融アドバイス、取引アドバイス、またはその他の種類のアドバイスを構成するものではありません。インジケーターの出力をそのように扱うべきではありません。作成者は、あなたが任意の暗号通貨、証券、または商品を買い、売り、または保有すべきであると推奨するものではありません。常に自分自身の調査を行い、専門的なアドバイスを求めてください。
このソフトウェアは、明示的または黙示的を問わず、いかなる種類の保証もなく「現状のまま」提供されます。
---
## 🔗 クレジットとライセンス
### 原作コードソース
1. **ICT Donchian Smart Money Structure**
- 作者: Zeiierman
- ライセンス: CC BY-NC-SA 4.0
- 変更: マルチシグナルシステムと統合、CHoChパターン検知を追加
2. **Reverse RSI Signals**
- 作者: AlgoAlpha
- ライセンス: MPL 2.0
- 変更: 内部シグナルロジックに適応
3. **Volumetric Weighted Cloud（VWC/TBOSI）**
- 元のコンセプトをマルチタイムフレーム分析に適応
- MTFテーブル表示で強化
4. **Order Block & FVG Detection**
- ICTコンセプトに基づく
- MTFサポートでカスタム実装
### このインジケーターのライセンス
**Mozilla Public License 2.0（MPL 2.0）**
以下が自由です：
- ✅ 商用利用
- ✅ 変更と配布
- ✅ 私的使用
- ✅ 特許使用
条件：
- 📄 ソースを開示
- 📄 ライセンスと著作権表示
- 📄 変更に同じライセンス
---
## 📞 サポートとコミュニティ
### 問題の報告
バグに遭遇したり機能提案がある場合は、以下を提供してください：
1. チャートタイムフレームとシンボル
2. 設定構成
3. 問題のスクリーンショット
4. 期待される動作と実際の動作
### ベストプラクティス
- デフォルト設定で開始
- 各コンポーネントを理解するために段階的に機能を有効/無効化
- ライブ取引前に少なくとも30日間デモアカウントを使用
- 適切なリスク管理と組み合わせる
---
## 🚀 バージョン履歴
### v5.0 - Simplified ICT Mode（現在）
- ✅ すべての未使用フィルターと機能を削除
- ✅ すべての8シグナルをデフォルトで有効化
- ✅ 💎 STRONG CHoChパターン検知を追加
- ✅ OBバウンスラベリングシステムを強化
- ✅ FVG検知と可視化を追加
- ✅ アラートシステムを改善（8イベント）
- ✅ パフォーマンスを最適化（より速いレンダリング）
- ✅ 包括的なDESCRIPTIONドキュメントを追加
### v4.2 - ICT Mode with EMA Convergence Filter（非推奨）
- EMA収束機能を持つレガシーバージョン（シンプルさのために削除）
### v4.0 - Pure ICT Mode（非推奨）
- 初期ICTフォーカスリリース
---
## 🎓 推奨学習リソース
このインジケーターを完全に活用するために、以下を学習してください：
1. **ICTコンセプト**（Inner Circle Trader - YouTube）
- 市場構造
- オーダーブロック
- フェアバリューギャップ
- 流動性コンセプト
2. **スマートマネーコンセプト（SMC）**
- Change of Character（CHoCH）
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Dynamic Equity Allocation Model"Cash is Trash"? Not Always. Here's Why Science Beats Guesswork.
Every retail trader knows the frustration: you draw support and resistance lines, you spot patterns, you follow market gurus on social media—and still, when the next bear market hits, your portfolio bleeds red. Meanwhile, institutional investors seem to navigate market turbulence with ease, preserving capital when markets crash and participating when they rally. What's their secret?
The answer isn't insider information or access to exotic derivatives. It's systematic, scientifically validated decision-making. While most retail traders rely on subjective chart analysis and emotional reactions, professional portfolio managers use quantitative models that remove emotion from the equation and process multiple streams of market information simultaneously.
This document presents exactly such a system—not a proprietary black box available only to hedge funds, but a fully transparent, academically grounded framework that any serious investor can understand and apply. The Dynamic Equity Allocation Model (DEAM) synthesizes decades of financial research from Nobel laureates and leading academics into a practical tool for tactical asset allocation.
Stop drawing colorful lines on your chart and start thinking like a quant. This isn't about predicting where the market goes next week—it's about systematically adjusting your risk exposure based on what the data actually tells you. When valuations scream danger, when volatility spikes, when credit markets freeze, when multiple warning signals align—that's when cash isn't trash. That's when cash saves your portfolio.
The irony of "cash is trash" rhetoric is that it ignores timing. Yes, being 100% cash for decades would be disastrous. But being 100% equities through every crisis is equally foolish. The sophisticated approach is dynamic: aggressive when conditions favor risk-taking, defensive when they don't. This model shows you how to make that decision systematically, not emotionally.
Whether you're managing your own retirement portfolio or seeking to understand how institutional allocation strategies work, this comprehensive analysis provides the theoretical foundation, mathematical implementation, and practical guidance to elevate your investment approach from amateur to professional.
The choice is yours: keep hoping your chart patterns work out, or start using the same quantitative methods that professionals rely on. The tools are here. The research is cited. The methodology is explained. All you need to do is read, understand, and apply.
The Dynamic Equity Allocation Model (DEAM) is a quantitative framework for systematic allocation between equities and cash, grounded in modern portfolio theory and empirical market research. The model integrates five scientifically validated dimensions of market analysis—market regime, risk metrics, valuation, sentiment, and macroeconomic conditions—to generate dynamic allocation recommendations ranging from 0% to 100% equity exposure. This work documents the theoretical foundations, mathematical implementation, and practical application of this multi-factor approach.
1. Introduction and Theoretical Background
1.1 The Limitations of Static Portfolio Allocation
Traditional portfolio theory, as formulated by Markowitz (1952) in his seminal work "Portfolio Selection," assumes an optimal static allocation where investors distribute their wealth across asset classes according to their risk aversion. This approach rests on the assumption that returns and risks remain constant over time. However, empirical research demonstrates that this assumption does not hold in reality. Fama and French (1989) showed that expected returns vary over time and correlate with macroeconomic variables such as the spread between long-term and short-term interest rates. Campbell and Shiller (1988) demonstrated that the price-earnings ratio possesses predictive power for future stock returns, providing a foundation for dynamic allocation strategies.
The academic literature on tactical asset allocation has evolved considerably over recent decades. Ilmanen (2011) argues in "Expected Returns" that investors can improve their risk-adjusted returns by considering valuation levels, business cycles, and market sentiment. The Dynamic Equity Allocation Model presented here builds on this research tradition and operationalizes these insights into a practically applicable allocation framework.
1.2 Multi-Factor Approaches in Asset Allocation
Modern financial research has shown that different factors capture distinct aspects of market dynamics and together provide a more robust picture of market conditions than individual indicators. Ross (1976) developed the Arbitrage Pricing Theory, a model that employs multiple factors to explain security returns. Following this multi-factor philosophy, DEAM integrates five complementary analytical dimensions, each tapping different information sources and collectively enabling comprehensive market understanding.
2. Data Foundation and Data Quality
2.1 Data Sources Used
The model draws its data exclusively from publicly available market data via the TradingView platform. This transparency and accessibility is a significant advantage over proprietary models that rely on non-public data. The data foundation encompasses several categories of market information, each capturing specific aspects of market dynamics.
First, price data for the S&P 500 Index is obtained through the SPDR S&P 500 ETF (ticker: SPY). The use of a highly liquid ETF instead of the index itself has practical reasons, as ETF data is available in real-time and reflects actual tradability. In addition to closing prices, high, low, and volume data are captured, which are required for calculating advanced volatility measures.
Fundamental corporate metrics are retrieved via TradingView's Financial Data API. These include earnings per share, price-to-earnings ratio, return on equity, debt-to-equity ratio, dividend yield, and share buyback yield. Cochrane (2011) emphasizes in "Presidential Address: Discount Rates" the central importance of valuation metrics for forecasting future returns, making these fundamental data a cornerstone of the model.
Volatility indicators are represented by the CBOE Volatility Index (VIX) and related metrics. The VIX, often referred to as the market's "fear gauge," measures the implied volatility of S&P 500 index options and serves as a proxy for market participants' risk perception. Whaley (2000) describes in "The Investor Fear Gauge" the construction and interpretation of the VIX and its use as a sentiment indicator.
Macroeconomic data includes yield curve information through US Treasury bonds of various maturities and credit risk premiums through the spread between high-yield bonds and risk-free government bonds. These variables capture the macroeconomic conditions and financing conditions relevant for equity valuation. Estrella and Hardouvelis (1991) showed that the shape of the yield curve has predictive power for future economic activity, justifying the inclusion of these data.
2.2 Handling Missing Data
A practical problem when working with financial data is dealing with missing or unavailable values. The model implements a fallback system where a plausible historical average value is stored for each fundamental metric. When current data is unavailable for a specific point in time, this fallback value is used. This approach ensures that the model remains functional even during temporary data outages and avoids systematic biases from missing data. The use of average values as fallback is conservative, as it generates neither overly optimistic nor pessimistic signals.
3. Component 1: Market Regime Detection
3.1 The Concept of Market Regimes
The idea that financial markets exist in different "regimes" or states that differ in their statistical properties has a long tradition in financial science. Hamilton (1989) developed regime-switching models that allow distinguishing between different market states with different return and volatility characteristics. The practical application of this theory consists of identifying the current market state and adjusting portfolio allocation accordingly.
DEAM classifies market regimes using a scoring system that considers three main dimensions: trend strength, volatility level, and drawdown depth. This multidimensional view is more robust than focusing on individual indicators, as it captures various facets of market dynamics. Classification occurs into six distinct regimes: Strong Bull, Bull Market, Neutral, Correction, Bear Market, and Crisis.
3.2 Trend Analysis Through Moving Averages
Moving averages are among the oldest and most widely used technical indicators and have also received attention in academic literature. Brock, Lakonishok, and LeBaron (1992) examined in "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns" the profitability of trading rules based on moving averages and found evidence for their predictive power, although later studies questioned the robustness of these results when considering transaction costs.
The model calculates three moving averages with different time windows: a 20-day average (approximately one trading month), a 50-day average (approximately one quarter), and a 200-day average (approximately one trading year). The relationship of the current price to these averages and the relationship of the averages to each other provide information about trend strength and direction. When the price trades above all three averages and the short-term average is above the long-term, this indicates an established uptrend. The model assigns points based on these constellations, with longer-term trends weighted more heavily as they are considered more persistent.
3.3 Volatility Regimes
Volatility, understood as the standard deviation of returns, is a central concept of financial theory and serves as the primary risk measure. However, research has shown that volatility is not constant but changes over time and occurs in clusters—a phenomenon first documented by Mandelbrot (1963) and later formalized through ARCH and GARCH models (Engle, 1982; Bollerslev, 1986).
DEAM calculates volatility not only through the classic method of return standard deviation but also uses more advanced estimators such as the Parkinson estimator and the Garman-Klass estimator. These methods utilize intraday information (high and low prices) and are more efficient than simple close-to-close volatility estimators. The Parkinson estimator (Parkinson, 1980) uses the range between high and low of a trading day and is based on the recognition that this information reveals more about true volatility than just the closing price difference. The Garman-Klass estimator (Garman and Klass, 1980) extends this approach by additionally considering opening and closing prices.
The calculated volatility is annualized by multiplying it by the square root of 252 (the average number of trading days per year), enabling standardized comparability. The model compares current volatility with the VIX, the implied volatility from option prices. A low VIX (below 15) signals market comfort and increases the regime score, while a high VIX (above 35) indicates market stress and reduces the score. This interpretation follows the empirical observation that elevated volatility is typically associated with falling markets (Schwert, 1989).
3.4 Drawdown Analysis
A drawdown refers to the percentage decline from the highest point (peak) to the lowest point (trough) during a specific period. This metric is psychologically significant for investors as it represents the maximum loss experienced. Calmar (1991) developed the Calmar Ratio, which relates return to maximum drawdown, underscoring the practical relevance of this metric.
The model calculates current drawdown as the percentage distance from the highest price of the last 252 trading days (one year). A drawdown below 3% is considered negligible and maximally increases the regime score. As drawdown increases, the score decreases progressively, with drawdowns above 20% classified as severe and indicating a crisis or bear market regime. These thresholds are empirically motivated by historical market cycles, in which corrections typically encompassed 5-10% drawdowns, bear markets 20-30%, and crises over 30%.
3.5 Regime Classification
Final regime classification occurs through aggregation of scores from trend (40% weight), volatility (30%), and drawdown (30%). The higher weighting of trend reflects the empirical observation that trend-following strategies have historically delivered robust results (Moskowitz, Ooi, and Pedersen, 2012). A total score above 80 signals a strong bull market with established uptrend, low volatility, and minimal losses. At a score below 10, a crisis situation exists requiring defensive positioning. The six regime categories enable a differentiated allocation strategy that not only distinguishes binarily between bullish and bearish but allows gradual gradations.
4. Component 2: Risk-Based Allocation
4.1 Volatility Targeting as Risk Management Approach
The concept of volatility targeting is based on the idea that investors should maximize not returns but risk-adjusted returns. Sharpe (1966, 1994) defined with the Sharpe Ratio the fundamental concept of return per unit of risk, measured as volatility. Volatility targeting goes a step further and adjusts portfolio allocation to achieve constant target volatility. This means that in times of low market volatility, equity allocation is increased, and in times of high volatility, it is reduced.
Moreira and Muir (2017) showed in "Volatility-Managed Portfolios" that strategies that adjust their exposure based on volatility forecasts achieve higher Sharpe Ratios than passive buy-and-hold strategies. DEAM implements this principle by defining a target portfolio volatility (default 12% annualized) and adjusting equity allocation to achieve it. The mathematical foundation is simple: if market volatility is 20% and target volatility is 12%, equity allocation should be 60% (12/20 = 0.6), with the remaining 40% held in cash with zero volatility.
4.2 Market Volatility Calculation
Estimating current market volatility is central to the risk-based allocation approach. The model uses several volatility estimators in parallel and selects the higher value between traditional close-to-close volatility and the Parkinson estimator. This conservative choice ensures the model does not underestimate true volatility, which could lead to excessive risk exposure.
Traditional volatility calculation uses logarithmic returns, as these have mathematically advantageous properties (additive linkage over multiple periods). The logarithmic return is calculated as ln(P_t / P_{t-1}), where P_t is the price at time t. The standard deviation of these returns over a rolling 20-trading-day window is then multiplied by √252 to obtain annualized volatility. This annualization is based on the assumption of independently identically distributed returns, which is an idealization but widely accepted in practice.
The Parkinson estimator uses additional information from the trading range (High minus Low) of each day. The formula is: σ_P = (1/√(4ln2)) × √(1/n × Σln²(H_i/L_i)) × √252, where H_i and L_i are high and low prices. Under ideal conditions, this estimator is approximately five times more efficient than the close-to-close estimator (Parkinson, 1980), as it uses more information per observation.
4.3 Drawdown-Based Position Size Adjustment
In addition to volatility targeting, the model implements drawdown-based risk control. The logic is that deep market declines often signal further losses and therefore justify exposure reduction. This behavior corresponds with the concept of path-dependent risk tolerance: investors who have already suffered losses are typically less willing to take additional risk (Kahneman and Tversky, 1979).
The model defines a maximum portfolio drawdown as a target parameter (default 15%). Since portfolio volatility and portfolio drawdown are proportional to equity allocation (assuming cash has neither volatility nor drawdown), allocation-based control is possible. For example, if the market exhibits a 25% drawdown and target portfolio drawdown is 15%, equity allocation should be at most 60% (15/25).
4.4 Dynamic Risk Adjustment
An advanced feature of DEAM is dynamic adjustment of risk-based allocation through a feedback mechanism. The model continuously estimates what actual portfolio volatility and portfolio drawdown would result at the current allocation. If risk utilization (ratio of actual to target risk) exceeds 1.0, allocation is reduced by an adjustment factor that grows exponentially with overutilization. This implements a form of dynamic feedback that avoids overexposure.
Mathematically, a risk adjustment factor r_adjust is calculated: if risk utilization u > 1, then r_adjust = exp(-0.5 × (u - 1)). This exponential function ensures that moderate overutilization is gently corrected, while strong overutilization triggers drastic reductions. The factor 0.5 in the exponent was empirically calibrated to achieve a balanced ratio between sensitivity and stability.
5. Component 3: Valuation Analysis
5.1 Theoretical Foundations of Fundamental Valuation
DEAM's valuation component is based on the fundamental premise that the intrinsic value of a security is determined by its future cash flows and that deviations between market price and intrinsic value are eventually corrected. Graham and Dodd (1934) established in "Security Analysis" the basic principles of fundamental analysis that remain relevant today. Translated into modern portfolio context, this means that markets with high valuation metrics (high price-earnings ratios) should have lower expected returns than cheaply valued markets.
Campbell and Shiller (1988) developed the Cyclically Adjusted P/E Ratio (CAPE), which smooths earnings over a full business cycle. Their empirical analysis showed that this ratio has significant predictive power for 10-year returns. Asness, Moskowitz, and Pedersen (2013) demonstrated in "Value and Momentum Everywhere" that value effects exist not only in individual stocks but also in asset classes and markets.
5.2 Equity Risk Premium as Central Valuation Metric
The Equity Risk Premium (ERP) is defined as the expected excess return of stocks over risk-free government bonds. It is the theoretical heart of valuation analysis, as it represents the compensation investors demand for bearing equity risk. Damodaran (2012) discusses in "Equity Risk Premiums: Determinants, Estimation and Implications" various methods for ERP estimation.
DEAM calculates ERP not through a single method but combines four complementary approaches with different weights. This multi-method strategy increases estimation robustness and avoids dependence on single, potentially erroneous inputs.
The first method (35% weight) uses earnings yield, calculated as 1/P/E or directly from operating earnings data, and subtracts the 10-year Treasury yield. This method follows Fed Model logic (Yardeni, 2003), although this model has theoretical weaknesses as it does not consistently treat inflation (Asness, 2003).
The second method (30% weight) extends earnings yield by share buyback yield. Share buybacks are a form of capital return to shareholders and increase value per share. Boudoukh et al. (2007) showed in "The Total Shareholder Yield" that the sum of dividend yield and buyback yield is a better predictor of future returns than dividend yield alone.
The third method (20% weight) implements the Gordon Growth Model (Gordon, 1962), which models stock value as the sum of discounted future dividends. Under constant growth g assumption: Expected Return = Dividend Yield + g. The model estimates sustainable growth as g = ROE × (1 - Payout Ratio), where ROE is return on equity and payout ratio is the ratio of dividends to earnings. This formula follows from equity theory: unretained earnings are reinvested at ROE and generate additional earnings growth.
The fourth method (15% weight) combines total shareholder yield (Dividend + Buybacks) with implied growth derived from revenue growth. This method considers that companies with strong revenue growth should generate higher future earnings, even if current valuations do not yet fully reflect this.
The final ERP is the weighted average of these four methods. A high ERP (above 4%) signals attractive valuations and increases the valuation score to 95 out of 100 possible points. A negative ERP, where stocks have lower expected returns than bonds, results in a minimal score of 10.
5.3 Quality Adjustments to Valuation
Valuation metrics alone can be misleading if not interpreted in the context of company quality. A company with a low P/E may be cheap or fundamentally problematic. The model therefore implements quality adjustments based on growth, profitability, and capital structure.
Revenue growth above 10% annually adds 10 points to the valuation score, moderate growth above 5% adds 5 points. This adjustment reflects that growth has independent value (Modigliani and Miller, 1961, extended by later growth theory). Net margin above 15% signals pricing power and operational efficiency and increases the score by 5 points, while low margins below 8% indicate competitive pressure and subtract 5 points.
Return on equity (ROE) above 20% characterizes outstanding capital efficiency and increases the score by 5 points. Piotroski (2000) showed in "Value Investing: The Use of Historical Financial Statement Information" that fundamental quality signals such as high ROE can improve the performance of value strategies.
Capital structure is evaluated through the debt-to-equity ratio. A conservative ratio below 1.0 multiplies the valuation score by 1.2, while high leverage above 2.0 applies a multiplier of 0.8. This adjustment reflects that high debt constrains financial flexibility and can become problematic in crisis times (Korteweg, 2010).
6. Component 4: Sentiment Analysis
6.1 The Role of Sentiment in Financial Markets
Investor sentiment, defined as the collective psychological attitude of market participants, influences asset prices independently of fundamental data. Baker and Wurgler (2006, 2007) developed a sentiment index and showed that periods of high sentiment are followed by overvaluations that later correct. This insight justifies integrating a sentiment component into allocation decisions.
Sentiment is difficult to measure directly but can be proxied through market indicators. The VIX is the most widely used sentiment indicator, as it aggregates implied volatility from option prices. High VIX values reflect elevated uncertainty and risk aversion, while low values signal market comfort. Whaley (2009) refers to the VIX as the "Investor Fear Gauge" and documents its role as a contrarian indicator: extremely high values typically occur at market bottoms, while low values occur at tops.
6.2 VIX-Based Sentiment Assessment
DEAM uses statistical normalization of the VIX by calculating the Z-score: z = (VIX_current - VIX_average) / VIX_standard_deviation. The Z-score indicates how many standard deviations the current VIX is from the historical average. This approach is more robust than absolute thresholds, as it adapts to the average volatility level, which can vary over longer periods.
A Z-score below -1.5 (VIX is 1.5 standard deviations below average) signals exceptionally low risk perception and adds 40 points to the sentiment score. This may seem counterintuitive—shouldn't low fear be bullish? However, the logic follows the contrarian principle: when no one is afraid, everyone is already invested, and there is limited further upside potential (Zweig, 1973). Conversely, a Z-score above 1.5 (extreme fear) adds -40 points, reflecting market panic but simultaneously suggesting potential buying opportunities.
6.3 VIX Term Structure as Sentiment Signal
The VIX term structure provides additional sentiment information. Normally, the VIX trades in contango, meaning longer-term VIX futures have higher prices than short-term. This reflects that short-term volatility is currently known, while long-term volatility is more uncertain and carries a risk premium. The model compares the VIX with VIX9D (9-day volatility) and identifies backwardation (VIX > 1.05 × VIX9D) and steep backwardation (VIX > 1.15 × VIX9D).
Backwardation occurs when short-term implied volatility is higher than longer-term, which typically happens during market stress. Investors anticipate immediate turbulence but expect calming. Psychologically, this reflects acute fear. The model subtracts 15 points for backwardation and 30 for steep backwardation, as these constellations signal elevated risk. Simon and Wiggins (2001) analyzed the VIX futures curve and showed that backwardation is associated with market declines.
6.4 Safe-Haven Flows
During crisis times, investors flee from risky assets into safe havens: gold, US dollar, and Japanese yen. This "flight to quality" is a sentiment signal. The model calculates the performance of these assets relative to stocks over the last 20 trading days. When gold or the dollar strongly rise while stocks fall, this indicates elevated risk aversion.
The safe-haven component is calculated as the difference between safe-haven performance and stock performance. Positive values (safe havens outperform) subtract up to 20 points from the sentiment score, negative values (stocks outperform) add up to 10 points. The asymmetric treatment (larger deduction for risk-off than bonus for risk-on) reflects that risk-off movements are typically sharper and more informative than risk-on phases.
Baur and Lucey (2010) examined safe-haven properties of gold and showed that gold indeed exhibits negative correlation with stocks during extreme market movements, confirming its role as crisis protection.
7. Component 5: Macroeconomic Analysis
7.1 The Yield Curve as Economic Indicator
The yield curve, represented as yields of government bonds of various maturities, contains aggregated expectations about future interest rates, inflation, and economic growth. The slope of the yield curve has remarkable predictive power for recessions. Estrella and Mishkin (1998) showed that an inverted yield curve (short-term rates higher than long-term) predicts recessions with high reliability. This is because inverted curves reflect restrictive monetary policy: the central bank raises short-term rates to combat inflation, dampening economic activity.
DEAM calculates two spread measures: the 2-year-minus-10-year spread and the 3-month-minus-10-year spread. A steep, positive curve (spreads above 1.5% and 2% respectively) signals healthy growth expectations and generates the maximum yield curve score of 40 points. A flat curve (spreads near zero) reduces the score to 20 points. An inverted curve (negative spreads) is particularly alarming and results in only 10 points.
The choice of two different spreads increases analysis robustness. The 2-10 spread is most established in academic literature, while the 3M-10Y spread is often considered more sensitive, as the 3-month rate directly reflects current monetary policy (Ang, Piazzesi, and Wei, 2006).
7.2 Credit Conditions and Spreads
Credit spreads—the yield difference between risky corporate bonds and safe government bonds—reflect risk perception in the credit market. Gilchrist and Zakrajšek (2012) constructed an "Excess Bond Premium" that measures the component of credit spreads not explained by fundamentals and showed this is a predictor of future economic activity and stock returns.
The model approximates credit spread by comparing the yield of high-yield bond ETFs (HYG) with investment-grade bond ETFs (LQD). A narrow spread below 200 basis points signals healthy credit conditions and risk appetite, contributing 30 points to the macro score. Very wide spreads above 1000 basis points (as during the 2008 financial crisis) signal credit crunch and generate zero points.
Additionally, the model evaluates whether "flight to quality" is occurring, identified through strong performance of Treasury bonds (TLT) with simultaneous weakness in high-yield bonds. This constellation indicates elevated risk aversion and reduces the credit conditions score.
7.3 Financial Stability at Corporate Level
While the yield curve and credit spreads reflect macroeconomic conditions, financial stability evaluates the health of companies themselves. The model uses the aggregated debt-to-equity ratio and return on equity of the S&P 500 as proxies for corporate health.
A low leverage level below 0.5 combined with high ROE above 15% signals robust corporate balance sheets and generates 20 points. This combination is particularly valuable as it represents both defensive strength (low debt means crisis resistance) and offensive strength (high ROE means earnings power). High leverage above 1.5 generates only 5 points, as it implies vulnerability to interest rate increases and recessions.
Korteweg (2010) showed in "The Net Benefits to Leverage" that optimal debt maximizes firm value, but excessive debt increases distress costs. At the aggregated market level, high debt indicates fragilities that can become problematic during stress phases.
8. Component 6: Crisis Detection
8.1 The Need for Systematic Crisis Detection
Financial crises are rare but extremely impactful events that suspend normal statistical relationships. During normal market volatility, diversified portfolios and traditional risk management approaches function, but during systemic crises, seemingly independent assets suddenly correlate strongly, and losses exceed historical expectations (Longin and Solnik, 2001). This justifies a separate crisis detection mechanism that operates independently of regular allocation components.
Reinhart and Rogoff (2009) documented in "This Time Is Different: Eight Centuries of Financial Folly" recurring patterns in financial crises: extreme volatility, massive drawdowns, credit market dysfunction, and asset price collapse. DEAM operationalizes these patterns into quantifiable crisis indicators.
8.2 Multi-Signal Crisis Identification
The model uses a counter-based approach where various stress signals are identified and aggregated. This methodology is more robust than relying on a single indicator, as true crises typically occur simultaneously across multiple dimensions. A single signal may be a false alarm, but the simultaneous presence of multiple signals increases confidence.
The first indicator is a VIX above the crisis threshold (default 40), adding one point. A VIX above 60 (as in 2008 and March 2020) adds two additional points, as such extreme values are historically very rare. This tiered approach captures the intensity of volatility.
The second indicator is market drawdown. A drawdown above 15% adds one point, as corrections of this magnitude can be potential harbingers of larger crises. A drawdown above 25% adds another point, as historical bear markets typically encompass 25-40% drawdowns.
The third indicator is credit market spreads above 500 basis points, adding one point. Such wide spreads occur only during significant credit market disruptions, as in 2008 during the Lehman crisis.
The fourth indicator identifies simultaneous losses in stocks and bonds. Normally, Treasury bonds act as a hedge against equity risk (negative correlation), but when both fall simultaneously, this indicates systemic liquidity problems or inflation/stagflation fears. The model checks whether both SPY and TLT have fallen more than 10% and 5% respectively over 5 trading days, adding two points.
The fifth indicator is a volume spike combined with negative returns. Extreme trading volumes (above twice the 20-day average) with falling prices signal panic selling. This adds one point.
A crisis situation is diagnosed when at least 3 indicators trigger, a severe crisis at 5 or more indicators. These thresholds were calibrated through historical backtesting to identify true crises (2008, 2020) without generating excessive false alarms.
8.3 Crisis-Based Allocation Override
When a crisis is detected, the system overrides the normal allocation recommendation and caps equity allocation at maximum 25%. In a severe crisis, the cap is set at 10%. This drastic defensive posture follows the empirical observation that crises typically require time to develop and that early reduction can avoid substantial losses (Faber, 2007).
This override logic implements a "safety first" principle: in situations of existential danger to the portfolio, capital preservation becomes the top priority. Roy (1952) formalized this approach in "Safety First and the Holding of Assets," arguing that investors should primarily minimize ruin probability.
9. Integration and Final Allocation Calculation
9.1 Component Weighting
The final allocation recommendation emerges through weighted aggregation of the five components. The standard weighting is: Market Regime 35%, Risk Management 25%, Valuation 20%, Sentiment 15%, Macro 5%. These weights reflect both theoretical considerations and empirical backtesting results.
The highest weighting of market regime is based on evidence that trend-following and momentum strategies have delivered robust results across various asset classes and time periods (Moskowitz, Ooi, and Pedersen, 2012). Current market momentum is highly informative for the near future, although it provides no information about long-term expectations.
The substantial weighting of risk management (25%) follows from the central importance of risk control. Wealth preservation is the foundation of long-term wealth creation, and systematic risk management is demonstrably value-creating (Moreira and Muir, 2017).
The valuation component receives 20% weight, based on the long-term mean reversion of valuation metrics. While valuation has limited short-term predictive power (bull and bear markets can begin at any valuation), the long-term relationship between valuation and returns is robustly documented (Campbell and Shiller, 1988).
Sentiment (15%) and Macro (5%) receive lower weights, as these factors are subtler and harder to measure. Sentiment is valuable as a contrarian indicator at extremes but less informative in normal ranges. Macro variables such as the yield curve have strong predictive power for recessions, but the transmission from recessions to stock market performance is complex and temporally variable.
9.2 Model Type Adjustments
DEAM allows users to choose between four model types: Conservative, Balanced, Aggressive, and Adaptive. This choice modifies the final allocation through additive adjustments.
Conservative mode subtracts 10 percentage points from allocation, resulting in consistently more cautious positioning. This is suitable for risk-averse investors or those with limited investment horizons. Aggressive mode adds 10 percentage points, suitable for risk-tolerant investors with long horizons.
Adaptive mode implements procyclical adjustment based on short-term momentum: if the market has risen more than 5% in the last 20 days, 5 percentage points are added; if it has declined more than 5%, 5 points are subtracted. This logic follows the observation that short-term momentum persists (Jegadeesh and Titman, 1993), but the moderate size of adjustment avoids excessive timing bets.
Balanced mode makes no adjustment and uses raw model output. This neutral setting is suitable for investors who wish to trust model recommendations unchanged.
9.3 Smoothing and Stability
The allocation resulting from aggregation undergoes final smoothing through a simple moving average over 3 periods. This smoothing is crucial for model practicality, as it reduces frequent trading and thus transaction costs. Without smoothing, the model could fluctuate between adjacent allocations with every small input change.
The choice of 3 periods as smoothing window is a compromise between responsiveness and stability. Longer smoothing would excessively delay signals and impede response to true regime changes. Shorter or no smoothing would allow too much noise. Empirical tests showed that 3-period smoothing offers an optimal ratio between these goals.
10. Visualization and Interpretation
10.1 Main Output: Equity Allocation
DEAM's primary output is a time series from 0 to 100 representing the recommended percentage allocation to equities. This representation is intuitive: 100% means full investment in stocks (specifically: an S&P 500 ETF), 0% means complete cash position, and intermediate values correspond to mixed portfolios. A value of 60% means, for example: invest 60% of wealth in SPY, hold 40% in money market instruments or cash.
The time series is color-coded to enable quick visual interpretation. Green shades represent high allocations (above 80%, bullish), red shades low allocations (below 20%, bearish), and neutral colors middle allocations. The chart background is dynamically colored based on the signal, enhancing readability in different market phases.
10.2 Dashboard Metrics
A tabular dashboard presents key metrics compactly. This includes current allocation, cash allocation (complement), an aggregated signal (BULLISH/NEUTRAL/BEARISH), current market regime, VIX level, market drawdown, and crisis status.
Additionally, fundamental metrics are displayed: P/E Ratio, Equity Risk Premium, Return on Equity, Debt-to-Equity Ratio, and Total Shareholder Yield. This transparency allows users to understand model decisions and form their own assessments.
Component scores (Regime, Risk, Valuation, Sentiment, Macro) are also displayed, each normalized on a 0-100 scale. This shows which factors primarily drive the current recommendation. If, for example, the Risk score is very low (20) while other scores are moderate (50-60), this indicates that risk management considerations are pulling allocation down.
10.3 Component Breakdown (Optional)
Advanced users can display individual components as separate lines in the chart. This enables analysis of component dynamics: do all components move synchronously, or are there divergences? Divergences can be particularly informative. If, for example, the market regime is bullish (high score) but the valuation component is very negative, this signals an overbought market not fundamentally supported—a classic "bubble warning."
This feature is disabled by default to keep the chart clean but can be activated for deeper analysis.
10.4 Confidence Bands
The model optionally displays uncertainty bands around the main allocation line. These are calculated as ±1 standard deviation of allocation over a rolling 20-period window. Wide bands indicate high volatility of model recommendations, suggesting uncertain market conditions. Narrow bands indicate stable recommendations.
This visualization implements a concept of epistemic uncertainty—uncertainty about the model estimate itself, not just market volatility. In phases where various indicators send conflicting signals, the allocation recommendation becomes more volatile, manifesting in wider bands. Users can understand this as a warning to act more cautiously or consult alternative information sources.
11. Alert System
11.1 Allocation Alerts
DEAM implements an alert system that notifies users of significant events. Allocation alerts trigger when smoothed allocation crosses certain thresholds. An alert is generated when allocation reaches 80% (from below), signaling strong bullish conditions. Another alert triggers when allocation falls to 20%, indicating defensive positioning.
These thresholds are not arbitrary but correspond with boundaries between model regimes. An allocation of 80% roughly corresponds to a clear bull market regime, while 20% corresponds to a bear market regime. Alerts at these points are therefore informative about fundamental regime shifts.
11.2 Crisis Alerts
Separate alerts trigger upon detection of crisis and severe crisis. These alerts have highest priority as they signal large risks. A crisis alert should prompt investors to review their portfolio and potentially take defensive measures beyond the automatic model recommendation (e.g., hedging through put options, rebalancing to more defensive sectors).
11.3 Regime Change Alerts
An alert triggers upon change of market regime (e.g., from Neutral to Correction, or from Bull Market to Strong Bull). Regime changes are highly informative events that typically entail substantial allocation changes. These alerts enable investors to proactively respond to changes in market dynamics.
11.4 Risk Breach Alerts
A specialized alert triggers when actual portfolio risk utilization exceeds target parameters by 20%. This is a warning signal that the risk management system is reaching its limits, possibly because market volatility is rising faster than allocation can be reduced. In such situations, investors should consider manual interventions.
12. Practical Application and Limitations
12.1 Portfolio Implementation
DEAM generates a recommendation for allocation between equities (S&P 500) and cash. Implementation by an investor can take various forms. The most direct method is using an S&P 500 ETF (e.g., SPY, VOO) for equity allocation and a money market fund or savings account for cash allocation.
A rebalancing strategy is required to synchronize actual allocation with model recommendation. Two approaches are possible: (1) rule-based rebalancing at every 10% deviation between actual and target, or (2) time-based monthly rebalancing. Both have trade-offs between responsiveness and transaction costs. Empirical evidence (Jaconetti, Kinniry, and Zilbering, 2010) suggests rebalancing frequency has moderate impact on performance, and investors should optimize based on their transaction costs.
12.2 Adaptation to Individual Preferences
The model offers numerous adjustment parameters. Component weights can be modified if investors place more or less belief in certain factors. A fundamentally-oriented investor might increase valuation weight, while a technical trader might increase regime weight.
Risk target parameters (target volatility, max drawdown) should be adapted to individual risk tolerance. Younger investors with long investment horizons can choose higher target volatility (15-18%), while retirees may prefer lower volatility (8-10%). This adjustment systematically shifts average equity allocation.
Crisis thresholds can be adjusted based on preference for sensitivity versus specificity of crisis detection. Lower thresholds (e.g., VIX > 35 instead of 40) increase sensitivity (more crises are detected) but reduce specificity (more false alarms). Higher thresholds have the reverse effect.
12.3 Limitations and Disclaimers
DEAM is based on historical relationships between indicators and market performance. There is no guarantee these relationships will persist in the future. Structural changes in markets (e.g., through regulation, technology, or central bank policy) can break established patterns. This is the fundamental problem of induction in financial science (Taleb, 2007).
The model is optimized for US equities (S&P 500). Application to other markets (international stocks, bonds, commodities) would require recalibration. The indicators and thresholds are specific to the statistical properties of the US equity market.
The model cannot eliminate losses. Even with perfect crisis prediction, an investor following the model would lose money in bear markets—just less than a buy-and-hold investor. The goal is risk-adjusted performance improvement, not risk elimination.
Transaction costs are not modeled. In practice, spreads, commissions, and taxes reduce net returns. Frequent trading can cause substantial costs. Model smoothing helps minimize this, but users should consider their specific cost situation.
The model reacts to information; it does not anticipate it. During sudden shocks (e.g., 9/11, COVID-19 lockdowns), the model can only react after price movements, not before. This limitation is inherent to all reactive systems.
12.4 Relationship to Other Strategies
DEAM is a tactical asset allocation approach and should be viewed as a complement, not replacement, for strategic asset allocation. Brinson, Hood, and Beebower (1986) showed in their influential study "Determinants of Portfolio Performance" that strategic asset allocation (long-term policy allocation) explains the majority of portfolio performance, but this leaves room for tactical adjustments based on market timing.
The model can be combined with value and momentum strategies at the individual stock level. While DEAM controls overall market exposure, within-equity decisions can be optimized through stock-picking models. This separation between strategic (market exposure) and tactical (stock selection) levels follows classical portfolio theory.
The model does not replace diversification across asset classes. A complete portfolio should also include bonds, international stocks, real estate, and alternative investments. DEAM addresses only the US equity allocation decision within a broader portfolio.
13. Scientific Foundation and Evaluation
13.1 Theoretical Consistency
DEAM's components are based on established financial theory and empirical evidence. The market regime component follows from regime-switching models (Hamilton, 1989) and trend-following literature. The risk management component implements volatility targeting (Moreira and Muir, 2017) and modern portfolio theory (Markowitz, 1952). The valuation component is based on discounted cash flow theory and empirical value research (Campbell and Shiller, 1988; Fama and French, 1992). The sentiment component integrates behavioral finance (Baker and Wurgler, 2006). The macro component uses established business cycle indicators (Estrella and Mishkin, 1998).
This theoretical grounding distinguishes DEAM from purely data-mining-based approaches that identify patterns without causal theory. Theory-guided models have greater probability of functioning out-of-sample, as they are based on fundamental mechanisms, not random correlations (Lo and MacKinlay, 1990).
13.2 Empirical Validation
While this document does not present detailed backtest analysis, it should be noted that rigorous validation of a tactical asset allocation model should include several elements:
In-sample testing establishes whether the model functions at all in the data on which it was calibrated. Out-of-sample testing is crucial: the model should be tested in time periods not used for development. Walk-forward analysis, where the model is successively trained on rolling windows and tested in the next window, approximates real implementation.
Performance metrics should be risk-adjusted. Pure return consideration is misleading, as higher returns often only compensate for higher risk. Sharpe Ratio, Sortino Ratio, Calmar Ratio, and Maximum Drawdown are relevant metrics. Comparison with benchmarks (Buy-and-Hold S&P 500, 60/40 Stock/Bond portfolio) contextualizes performance.
Robustness checks test sensitivity to parameter variation. If the model only functions at specific parameter settings, this indicates overfitting. Robust models show consistent performance over a range of plausible parameters.
13.3 Comparison with Existing Literature
DEAM fits into the broader literature on tactical asset allocation. Faber (2007) presented a simple momentum-based timing system that goes long when the market is above its 10-month average, otherwise cash. This simple system avoided large drawdowns in bear markets. DEAM can be understood as a sophistication of this approach that integrates multiple information sources.
Ilmanen (2011) discusses various timing factors in "Expected Returns" and argues for multi-factor approaches. DEAM operationalizes this philosophy. Asness, Moskowitz, and Pedersen (2013) showed that value and momentum effects work across asset classes, justifying cross-asset application of regime and valuation signals.
Ang (2014) emphasizes in "Asset Management: A Systematic Approach to Factor Investing" the importance of systematic, rule-based approaches over discretionary decisions. DEAM is fully systematic and eliminates emotional biases that plague individual investors (overconfidence, hindsight bias, loss aversion).
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Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
Candle VolumeScript Based on Volume Based Coloured Bars by KivancOzbilgic
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This indicator turns the candle into a volume-weighted signal, When the price falls, the candle is red, and when the price rises, the candle is green. In addition, we each have two colors Happening:
Dark red: It is dark red when the downtrend trading volume is greater than 200% of its average price (default 20 days), which indicates that our price action is supported by strong bearish trading volume
Red: When the price drops and the trading volume is between 50% and 200% of its average (default 20 days), in this case, we can think that the trading volume is neither strong nor weak
Light red: When the price drops and VOLUME is less than 50% of its average price (default 20 days), the trading volume is weak and there is not much support for price movements
Dark green: When the price rises and the trading volume is greater than 200% of its average price (default 20 days), it indicates that our price movement is supported by a strong bullish trading volume
Green: When the price rises and the trading volume is between 50% and 200% of its average price (the default is 20 days), in this case, we can think that the trading volume is neither strong nor weak
Light green: When the price rises and the trading volume is less than 50% of its average price (default 20 days), the trading volume is weak and does not support the price trend well
Default Low Volume is 50% (0.5) and High 200% (2), but if those values don't suit you, you can change them according to your trading personality
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Esse é um indicador que colore a candlera de acordo com o volume baseado na média, quando o volume está acima da média a candlera fica verde, e quando está abaixo, a candlera fica vermelha, e as cores das candleras funcionam dessa forma :
Vermelho escuro: fica vermelho escuro quando o preço cai e o volume de negociação é superior a 200% do preço médio (padrão 20 dias), o que indica que nossa ação de preço é suportada por um forte volume de negociação de baixa
Vermelho: quando o preço cai e o volume de negociação está entre 50% e 200% de sua média (padrão de 20 dias), nesse caso, podemos pensar que o volume de negociação não é forte nem fraco
Vermelho claro: quando o preço cai e VOLUME é inferior a 50% do preço médio (padrão 20 dias), o volume de negociação é fraco e não há muito suporte para movimentos de preço
Verde escuro: quando o preço aumenta e o volume de negociação é superior a 200% do preço médio (padrão 20 dias), isso indica que nosso movimento de preço é suportado por um forte volume de negociação de alta
Verde: quando o preço aumenta e o volume de negociação está entre 50% e 200% do preço médio (o padrão é 20 dias), nesse caso, podemos pensar que o volume de negociação não é forte nem fraco
Verde claro: quando o preço aumenta e o volume de negociação é inferior a 50% do preço médio (padrão 20 dias), o volume de negociação é fraco e não suporta bem a tendência de preço
O volume baixo padrão é 50% (0,5) e alto 200% (2), mas se esses valores não forem adequados para você, você poderá alterá-los de acordo com sua personalidade de trading
ADX Color Change by BehemothI find this tool to be the most valuable and accurate entry point indicator along with moving averages and the VWAP.
ADX Color Indicator - Controls & Intraday Trading Benefits
Indicator Controls:
1. ADX Length (default: 14)
- Controls the calculation period for ADX
- Lower values (7-10) = more sensitive, faster signals (better for scalping)
- Higher values (14-20) = smoother, fewer false signals (better for swing trades)
- *Intraday tip:* Try 10-14 for most intraday timeframes
2. Show Threshold Levels (default: On)
- Displays the 20 and 25 horizontal lines
- Helps you quickly identify when ADX crosses key strength levels
3. Use Custom Timeframe (default: Off)
- Allows viewing higher timeframe ADX on lower timeframe charts
- *Example:* Trade on 5-min chart but see 15-min or 1-hour ADX
4. Custom Timeframe
- Select any timeframe: 1m, 5m, 15m, 30m, 1H, 4H, D, etc.
- *Intraday tip:* Use 15m or 1H ADX on 5m charts for better trend context
5. Show +DI and -DI (default: Off)
- Shows directional movement indicators
- Green line (+DI) > Red line (-DI) = bullish trend
- Red line (-DI) > Green line (+DI) = bearish trend
6. Show Background Zon es (default: Off)
- Visual background colors for quick trend strength identification
- Green = strong trend (ADX > 25)
- Yellow = moderate trend (ADX 20-25)
Intraday Trading Benefits:
1. Avoid Choppy Markets
- When ADX < 20 (no background color), market is ranging
- Reduces false breakout trades and whipsaws
- Save time and capital by stepping aside during low-quality setups
2. Identify High-Probability Trend Trades
- **Green line + Green zone** = strong trend building, look for pullback entries
- Yellow line crossing above 20 = early trend formation signal
- Catch trends early when ADX starts rising from below 20
3. Multi-Timeframe Analysis
- Use custom timeframe to align with higher timeframe trends
- *Example:* If 1H ADX shows green (strong trend), take breakout trades on 5m chart in same direction
- Increases win rate by trading with the bigger picture
4. Exit Signals
- When ADX turns red (falling), trend is weakening
- Consider tightening stops or taking profits
- Avoid entering new positions when ADX is declining
5. Quick Visual Confirmation
- Color coding eliminates need to analyze numbers
- Instant recognition: Green = go, Yellow = caution, Red = trend dying
- Faster decision-making during fast market moves
6. Scalping Strategy
- Set ADX length to 7-10 for sensitive signals
- Only scalp when ADX is rising (blue, yellow, or green)
- Exit when ADX turns red
7. Breakout Confirmation
- Wait for ADX to rise above 20 after a breakout
- Filters false breakouts in ranging markets
- Yellow or green color confirms momentum behind the move
Optimal Intraday Settings:
- Day Trading (5-15 min charts):** ADX Length = 10-14
- Scalping (1-5 min charts):** ADX Length = 7-10, watch custom 15m timeframe
- Swing Intraday (30min-1H charts):** ADX Length = 14-20
Simple Trading Rules:
✅ Trade: ADX rising + above 20 (yellow or green)
⚠️ Caution: ADX flat or just crossed 20
❌ Avoid:*ADX falling (red) or below 20
The key advantage is staying out of low-quality, choppy price action which is where most intraday traders lose money!
Price Action Brooks ProPrice Action Brooks Pro (PABP) - Professional Trading Indicator
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📊 OVERVIEW
Price Action Brooks Pro (PABP) is a professional-grade TradingView indicator developed based on Al Brooks' Price Action trading methodology. It integrates decades of Al Brooks' trading experience and price action analysis techniques into a comprehensive technical analysis tool, helping traders accurately interpret market structure and identify trading opportunities.
• Applicable Markets: Stocks, Futures, Forex, Cryptocurrencies
• Timeframes: 1-minute to Daily (5-minute chart recommended)
• Theoretical Foundation: Al Brooks Price Action Trading Method
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🎯 CORE FEATURES
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1️⃣ INTELLIGENT GAP DETECTION SYSTEM
Automatically identifies and marks three critical types of gaps in the market.
TRADITIONAL GAP
• Detects complete price gaps between bars
• Upward gap: Current bar's low > Previous bar's high
• Downward gap: Current bar's high < Previous bar's low
• Hollow border design - doesn't obscure price action
• Color coding: Upward gaps (light green), Downward gaps (light pink)
• Adjustable border: 1-5 pixel width options
TAIL GAP
• Detects price gaps between bar wicks/shadows
• Analyzes across 3 bars for precision
• Identifies hidden market structure
BODY GAP
• Focuses only on gaps between bar bodies (open/close)
• Filters out wick noise
• Disabled by default, enable as needed
Trading Significance:
• Gaps signal strong momentum
• Gap fills provide trading opportunities
• Consecutive gaps indicate trend continuation
✓ Independent alert system for all gap types
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2️⃣ RTH BAR COUNT (Trading Session Counter)
Intelligent counting system designed for US stock intraday trading.
FEATURES
• RTH Only Display: Regular Trading Hours (09:30-15:00 EST)
• 5-Minute Chart Optimized: Displays every 3 bars (15-minute intervals)
• Daily Auto-Reset: Counting starts from 1 each trading day
SMART COLOR CODING
• 🔴 Red (Bars 18 & 48): Critical turning moments (1.5h & 4h)
• 🔵 Sky Blue (Multiples of 12): Hourly markers (12, 24, 36...)
• 🟢 Light Green (Bar 6): Half-hour marker (30 minutes)
• ⚫ Gray (Others): Regular 15-minute interval markers
Al Brooks Time Theory:
• Bar 18 (90 min): First 90 minutes determine daily trend
• Bar 48 (4 hours): Important afternoon turning point
• Hourly markers: Track institutional trading rhythm
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3️⃣ FOUR-LINE EMA SYSTEM
Professional-grade configurable moving average system.
DEFAULT CONFIGURATION
• EMA 20: Short-term trend (Al Brooks' most important MA)
• EMA 50: Medium-short term reference
• EMA 100: Medium-long term confirmation
• EMA 200: Long-term trend and bull/bear dividing line
FLEXIBLE CUSTOMIZATION
Each EMA can be independently configured:
• On/Off toggle
• Data source selection (close/high/low/open, etc.)
• Custom period length
• Offset adjustment
• Color and transparency
COLOR SCHEME
• EMA 20: Dark brown, opaque (most important)
• EMA 50/100/200: Blue-purple gradient, 70% transparent
TRADING APPLICATIONS
• Bullish Alignment: Price > 20 > 50 > 100 > 200
• Bearish Alignment: 200 > 100 > 50 > 20 > Price
• EMA Confluence: All within <1% = major move precursor
Al Brooks Quote:
"The EMA 20 is the most important moving average. Almost all trading decisions should reference it."
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4️⃣ PREVIOUS VALUES (Key Prior Price Levels)
Automatically marks important price levels that often act as support/resistance.
THREE INDEPENDENT CONFIGURATIONS
Each group configurable for:
• Timeframe (1D/60min/15min, etc.)
• Price source (close/high/low/open/CurrentOpen, etc.)
• Line style and color
• Display duration (Today/TimeFrame/All)
SMART OPEN PRICE LABELS ⭐
• Auto-displays "Open" label when CurrentOpen selected
• Label color matches line color
• Customizable label size
TYPICAL SETUP
• 1st Line: Previous close (Support/Resistance)
• 2nd Line: Previous high (Breakout target)
• 3rd Line: Previous low (Support level)
Al Brooks Magnet Price Theory:
• Previous open: Price frequently tests opening price
• Previous high/low: Strongest support/resistance
• Breakout confirmation: Breaking prior levels = trend continuation
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5️⃣ INSIDE & OUTSIDE BAR PATTERN RECOGNITION
Automatically detects core candlestick patterns from Al Brooks' theory.
ii PATTERN (Consecutive Inside Bars)
• Current bar contained within previous bar
• Two or more consecutive
• Labels: ii, iii, iiii (auto-accumulates)
• High-probability breakout setup
• Stop loss: Outside both bars
Trading Significance:
"Inside bars are one of the most reliable breakout setups, especially three or more consecutive inside bars." - Al Brooks
OO PATTERN (Consecutive Outside Bars)
• Current bar engulfs previous bar
• Two or more consecutive
• Labels: oo, ooo (auto-accumulates)
• Indicates indecision or volatility increase
ioi PATTERN (Inside-Outside-Inside)
• Three-bar combination: Inside → Outside → Inside
• Auto-detected and labeled
• Tug-of-war pattern
• Breakout direction often very strong
SMART LABEL SYSTEM
• Auto-accumulation counting
• Dynamic label updates
• Customizable size and color
• Positioned above bars
✓ Independent alerts for all patterns
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💡 USE CASES
INTRADAY TRADING
✓ Bar Count (timing rhythm)
✓ Traditional Gap (strong signals)
✓ EMA 20 + 50 (quick trend)
✓ ii/ioi Patterns (breakout points)
SWING TRADING
✓ Previous Values (key levels)
✓ EMA 20 + 50 + 100 (trend analysis)
✓ Gaps (trend confirmation)
✓ iii Patterns (entry timing)
TREND FOLLOWING
✓ All four EMAs (alignment analysis)
✓ Gaps (continuation signals)
✓ Previous Values (targets)
BREAKOUT TRADING
✓ iii Pattern (high-reliability setup)
✓ Previous Values (targets)
✓ EMA 20 (trend direction)
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🎨 DESIGN FEATURES
PROFESSIONAL COLOR SCHEME
• Gaps: Hollow borders + light colors
• Bar Count: Smart multi-color coding
• EMAs: Gradient colors + transparency hierarchy
• Previous Values: Customizable + smart labels
CLEAR VISUAL HIERARCHY
• Important elements: Opaque (EMA 20, bar count)
• Reference elements: Semi-transparent (other EMAs, gaps)
• Hollow design: Doesn't obscure price action
USER-FRIENDLY INTERFACE
• Clear functional grouping
• Inline layout saves space
• All colors and sizes customizable
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📚 AL BROOKS THEORY CORE
READING PRICE ACTION
"Don't try to predict the market, read what the market is telling you."
PABP converts core concepts into visual tools:
• Trend Assessment: EMA system
• Time Rhythm: Bar Count
• Market Structure: Gap analysis
• Trade Setups: Inside/Outside Bars
• Support/Resistance: Previous Values
PROBABILITY THINKING
• ii pattern: Medium probability
• iii pattern: High probability
• iii + EMA 20 support: Very high probability
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⚙️ TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Maximum Objects: 500 lines, 500 labels, 500 boxes
• Alert Functions: 8 independent alerts
• Supported Timeframes: All (5-min recommended for Bar Count)
• Compatibility: All TradingView plans, Mobile & Desktop
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🚀 RECOMMENDED INITIAL SETTINGS
GAPS
• Traditional Gap: ✓
• Tail Gap: ✓
• Border Width: 2
BAR COUNT
• Use Bar Count: ✓
• Label Size: Normal
EMA
• EMA 20: ✓
• EMA 50: ✓
• EMA 100: ✓
• EMA 200: ✓
PREVIOUS VALUES
• 1st: close (Previous close)
• 2nd: high (Previous high)
• 3rd: low (Previous low)
INSIDE & OUTSIDE BAR
• All patterns: ✓
• Label Size: Large
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🌟 WHY CHOOSE PABP?
✅ Solid Theoretical Foundation
Based on Al Brooks' decades of trading experience
✅ Complete Professional Features
Systematizes complex price action analysis
✅ Highly Customizable
Every feature adjustable to personal style
✅ Excellent Performance
Optimized code ensures smooth experience
✅ Continuous Updates
Constantly improving based on feedback
✅ Suitable for All Levels
Benefits beginners to professionals
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📖 RECOMMENDED LEARNING
Al Brooks Books:
• "Trading Price Action Trends"
• "Trading Price Action Trading Ranges"
• "Trading Price Action Reversals"
Learning Path:
1. Understand basic candlestick patterns
2. Learn EMA applications
3. Master market structure analysis
4. Develop trading system
5. Continuous practice and optimization
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⚠️ RISK DISCLOSURE
IMPORTANT NOTICE:
• For educational and informational purposes only
• Does not constitute investment advice
• Past performance doesn't guarantee future results
• Trading involves risk and may result in capital loss
• Trade according to your risk tolerance
• Test thoroughly in demo account first
RESPONSIBLE TRADING:
• Always use stop losses
• Control position sizes reasonably
• Don't overtrade
• Continuous learning and improvement
• Keep trading journal
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📜 COPYRIGHT
Price Action Brooks Pro (PABP)
Author: © JimmC98
License: Mozilla Public License 2.0
Pine Script Version: v6
Acknowledgments:
Thanks to Dr. Al Brooks for his contributions to price action trading. This indicator is developed based on his theories.
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Experience professional-grade price action analysis now!
"The best traders read price action, not indicators. But when indicators help you read price action better, use them." - Al Brooks
Stochastic [Paifc0de]Stochastic — clean stochastic oscillator with visual masking, neutral markers, and basic filters
What it does
This indicator plots a standard stochastic oscillator (%K with smoothing and %D) and adds practical quality-of-life features for lower timeframes: optional visual masking when %K hugs overbought/oversold, neutral K–D cross markers, session-gated edge triangles (K crossing 20/80), and simple filters (minimum %K slope, minimum |K–D| gap, optional %D slope agreement, mid-zone mute, and a cooldown between markers). Display values are clamped to 0–100 to keep the panel scale stable. The tool is for research/education and does not generate entries/exits or financial advice.
Default preset: 20 / 10 / 10
K Length = 20
Classic lookback used in many textbooks. On intraday charts it balances responsiveness and stability: short enough to react to momentum shifts, long enough to avoid constant whipsaws. In practice it captures ~the last 20 bars’ position of close within the high–low range.
K Smoothing = 10
A 10-period SMA applied to the raw %K moderates the “saw-tooth” effect that raw stochastic can exhibit in choppy phases. The smoothing reduces over-reaction to micro spikes while preserving the main rhythm of swings; visually, %K becomes a continuous path that is easier to read.
D Length = 10
%D is the moving average of smoothed %K. With 10, %D becomes a clearly slower guide line. The larger separation between %K(10-SMA) and %D(10-SMA of %K) produces cleaner crosses and fewer spurious toggles than micro settings (e.g., 3/3/3). On M5–M15 this pair often yields readable cross cycles without flooding the chart.
How the 20/10/10 trio behaves
In persistent trends, %K will spend more time near 20 or 80; the 10-period smoothing delays flips slightly and emphasizes only meaningful turn attempts.
In ranges, %K oscillates around mid-zone (40–60). With 10/10 smoothing, cross signals cluster less densely; combining with the |K–D| gap filter helps keep only decisive crosses.
If your symbol is unusually volatile or illiquid, reduce K Length (e.g., 14) or reduce K Smoothing (e.g., 7) to keep responsiveness. If crosses feel late, decrease D Length (e.g., 7). If noise is excessive, increase K Smoothing first, then consider raising D Length.
Visuals
OB/OS lines: default 80/20 reference levels and a midline at 50.
Masking near edges: %K can be temporarily hidden when it is pressing an edge, approaching it with low slope, or going nearly flat near the boundary. This keeps the panel readable during “stuck at the edge” phases.
Soft glow (optional): highlights %K’s active path; can be turned off.
Light/Dark palette: quick toggle to match your chart theme.
Scale safety: all plotted values (lines, fills, markers) are clamped to 0–100 to prevent the axis from expanding beyond the stochastic range.
Markers and filters
Neutral K–D cross markers: circles in the mid-zone when %K crosses %D.
Edge triangles: show when %K crosses 20 or 80; can be restricted to a session window (02:00–12:00 ET).
Filters (optional):
Min %K slope: require a minimum absolute slope so very flat crosses are ignored.
Min |K–D| gap: demand separation between lines at the cross moment.
%D slope agreement: keep crosses that align with %D’s direction.
Mid-zone mute: suppress crosses inside a user-defined 40–60 band (defaults).
Cooldown: minimum bars between successive markers.
Parameters (quick guide)
K Length / K Smoothing / D Length: core stochastic settings. Start with 20/10/10; tune K Smoothing first if you see too much jitter.
Overbought / Oversold (80/20): adjust for assets that tend to trend (raise to 85/15) or mean-revert (lower to 75/25).
Slope & gap filters: increase on very noisy symbols; reduce if you miss too many crosses.
Session window (triangles only): use if you want edge markers only during active hours.
Marker size and offset: cosmetic; they do not affect calculations.
Alerts
K–D Cross Up (filtered) and K–D Cross Down (filtered): fire when a cross passes your filters/cooldown.
Edge Up / Edge Down: fire when %K crosses the 20/80 levels.
All alerts confirm on bar close.
Notes & attribution
Original implementation and integration by Paifc0de; no third-party code is copied.
This indicator is for research/education and does not provide entries/exits or financial advice.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Swing EMAWhat is Swing EMA?
Swing EMA is an exponential moving average crossover-based indicator used for low-risk directional trading.
it's used for different types of Ema 20,50,100 and 200, 3 of them are plotted on chat 20,100,200.
100 and 200 Ema is used for showing support and resistance and it contains highlights area between them and its change color according to market crossover condition.
20 moving average is used for knowing Market Behaviour and changing its color according to crossover conditions of 50 and 20 Ema.
How does it work?
It contains 4 different types of moving averages 20,50,100, 200 out of 3 are plotted on the chart.
20 Ema is used for knowing current market behavior. Its changes its color based on the crossover of 50 Ema and 20 Ema, if 20 Ema is higher than 50 Ema then it changes its color to green, and its opposites are changed their color to red when 20 Ema is lower than 50 Ema.
100 and 200 Ema used as a support and resistance and is also contain highlighted areas between them its change their color based on the crossover if 100 Ema is higher than 200 Ema a then both of them are going to change color to Green and as an opposite, if 200 Ema is higher then 100 Ema is going to change its color to red.
So in simple word 100 and 200 Ema is used as support and resistance zone and 20 Ema is used to know current market behavior.
How to use it?
It is very easy to understand by looking at the example I gave where are the two different types of phrases. phrase bull phrase and bear phrase so 100 and 200 Ema is used as a support and resistance and to tell you which phrase is currently on the market on example there is a bull phrase on the left side and bear phrase on the right side by using your technical analysis you can find out a really good spot to buy your stocks on a bull phrase and too short on the bear phrase. 20 Ema is used as a knowing the current market behavior it doesn't make any difference on buying or selling as much as 100 Ema and 200 Ema.
Tips
Don't trade against the market.
Try trade on trending stocks rather than sideways stock.
The higher the area between 100 Ema and 200 Ema is the stronger the phrase.
Do Backtesting before real trading.
Enjoy Trading.
Smart Money Flow Index (SMFI) - Advanced SMC [PhenLabs]📊Smart Money Flow Index (SMFI)
Version: PineScript™v6
📌Description
The Smart Money Flow Index (SMFI) is an advanced Smart Money Concepts implementation that tracks institutional trading behavior through multi-dimensional analysis. This comprehensive indicator combines volume-validated Order Block detection, Fair Value Gap identification with auto-mitigation tracking, dynamic Liquidity Zone mapping, and Break of Structure/Change of Character detection into a unified system.
Unlike basic SMC indicators, SMFI employs a proprietary scoring algorithm that weighs five critical factors: Order Block strength (validated by volume), Fair Value Gap size and recency, proximity to Liquidity Zones, market structure alignment (BOS/CHoCH), and multi-timeframe confluence. This produces a Smart Money Score (0-100) where readings above 70 represent optimal institutional setup conditions.
🚀Points of Innovation
Volume-Validated Order Block Detection – Only displays Order Blocks when formation candle exceeds customizable volume multiplier (default 1.5x average), filtering weak zones and highlighting true institutional accumulation/distribution
Auto-Mitigation Tracking System – Fair Value Gaps and Order Blocks automatically update status when price mitigates them, with visual distinction between active and filled zones preventing trades on dead levels
Proprietary Smart Money Score Algorithm – Combines weighted factors (OB strength 25%, FVG proximity 20%, Liquidity 20%, Structure 20%, MTF 15%) into single 0-100 confidence rating updating in real-time
ATR-Based Adaptive Calculations – All distance measurements use 14-period Average True Range ensuring consistent function across any instrument, timeframe, or volatility regime without manual recalibration
Dynamic Age Filtering – Automatically removes liquidity levels and FVGs older than configurable thresholds preventing chart clutter while maintaining relevant levels
Multi-Timeframe Confluence Integration – Analyzes higher timeframe bias with customizable multipliers (2-10x) and incorporates HTF trend direction into Smart Money Score for institutional alignment
🔧Core Components
Order Block Engine – Detects institutional supply/demand zones using characteristic patterns (down-move-then-strong-up for bullish, up-move-then-strong-down for bearish) with minimum volume threshold validation, tracks mitigation when price closes through zones
Fair Value Gap Scanner – Identifies price imbalances where current candle's low/high leaves gap with two-candle-prior high/low, filters by minimum size percentage, monitors 50% fill for mitigation status
Liquidity Zone Mapper – Uses pivot high/low detection with configurable lookback to mark swing points where stop losses cluster, extends horizontal lines to visualize sweep targets, manages lifecycle through age-based removal
Market Structure Analyzer – Tracks pivot progression to identify trend through higher-highs/higher-lows (bullish) or lower-highs/lower-lows (bearish), detects Break of Structure and Change of Character for trend/reversal confirmation
Scoring Calculation Engine – Evaluates proximity to nearest Order Blocks using ATR-normalized distance, assesses FVG recency and distance, calculates liquidity proximity with age weighting, combines structure bias and MTF trend into smoothed final score
🔥Key Features
Customizable Display Limits – Control maximum Order Blocks (1-10), Liquidity Zones (1-10), and FVG age (10-200 bars) to maintain clean charts focused on most relevant institutional levels
Gradient Strength Visualization – All zones render with transparency-adjustable coloring where stronger/newer zones appear more solid and weaker/older zones fade progressively providing instant visual hierarchy
Educational Label System – Optional labels identify each zone type (Bullish OB, Bearish OB, Bullish FVG, Bearish FVG, BOS) with color-coded text helping traders learn SMC concepts through practical application
Real-Time Smart Money Score Dashboard – Top-right table displays current score (0-100) with color coding (green >70, yellow 30-70, red <30) plus trend arrow for at-a-glance confidence assessment
Comprehensive Alert Suite – Configurable notifications for Order Block formation, Fair Value Gap detection, Break of Structure events, Change of Character signals, and high Smart Money Score readings (>70)
Buy/Sell Signal Integration – Automatically plots triangle markers when Smart Money Score exceeds 70 with aligned market structure and fresh Order Block detection providing clear entry signals
🎨Visualization
Order Block Boxes – Shaded rectangles extend from formation bar spanning high-to-low of institutional candle, bullish zones in green, bearish in red, with customizable transparency (80-98%)
Fair Value Gap Zones – Rectangular areas marking imbalances, active FVGs display in bright colors with adjustable transparency, mitigated FVGs switch to gray preventing trades on filled zones
Liquidity Level Lines – Dashed horizontal lines extend from pivot creation points, swing highs in bearish color (short targets above), swing lows in bullish color (long targets below), opacity decreases with age
Structure Labels – "BOS" labels appear above/below price when Break of Structure confirmed, colored by direction (green bullish, red bearish), positioned at 1% beyond highs/lows for visibility
Educational Info Panel – Bottom-right table explains key terminology (OB, FVG, BOS, CHoCH) and score interpretation (>70 high probability) with semi-transparent background for readability
📖Usage Guidelines
General Settings
Show Order Blocks – Default: On, toggles visibility of institutional supply/demand zones, disable when focusing solely on FVGs or Liquidity
Show Fair Value Gaps – Default: On, controls FVG zone display including active and mitigated imbalances
Show Liquidity Zones – Default: On, manages liquidity line visibility, disable on lower timeframes to reduce clutter
Show Market Structure – Default: On, toggles BOS/CHoCH label display
Show Smart Money Score – Default: On, controls score dashboard visibility
Order Block Settings
OB Lookback Period – Default: 20, Range: 5-100, controls bars scanned for Order Block patterns, lower values detect recent activity, higher values find older blocks
Min Volume Multiplier – Default: 1.5, Range: 1.0-5.0, sets minimum volume threshold as multiple of 20-period average, higher values (2.0+) filter for strongest institutional candles
Max Order Blocks to Display – Default: 3, Range: 1-10, limits simultaneous Order Blocks shown, lower settings (1-3) maintain focus on most recent zones
Fair Value Gap Settings
Min FVG Size (%) – Default: 0.3, Range: 0.1-2.0, defines minimum gap size as percentage of close price, lower values detect micro-imbalances, higher values focus on significant gaps
Max FVG Age (bars) – Default: 50, Range: 10-200, removes FVGs older than specified bars, lower settings (10-30) for scalping, higher (100-200) for swing trading
Show FVG Mitigation – Default: On, displays filled FVGs in gray providing visual history, disable to show only active untouched imbalances
Liquidity Zone Settings
Liquidity Lookback – Default: 50, Range: 20-200, sets pivot detection period for swing highs/lows, lower values (20-50) mark shorter-term liquidity, higher (100-200) identify major swings
Max Liquidity Age (bars) – Default: 100, Range: 20-500, removes liquidity lines older than specified bars, adjust based on timeframe
Liquidity Sensitivity – Default: 0.5, Range: 0.1-1.0, controls pivot detection sensitivity, lower values mark only major swings, higher values identify minor swings
Max Liquidity Zones to Display – Default: 3, Range: 1-10, limits total liquidity levels shown maintaining chart clarity
Market Structure Settings
Pivot Length – Default: 5, Range: 3-15, defines bars to left/right for pivot validation, lower values (3-5) create sensitive structure breaks, higher (10-15) filter for major shifts
Min Structure Move (%) – Default: 1.0, Range: 0.1-5.0, sets minimum percentage move required between pivots to confirm structure change
Multi-Timeframe Settings
Enable MTF Analysis – Default: On, activates higher timeframe trend analysis incorporation into Smart Money Score
Higher Timeframe Multiplier – Default: 4, Range: 2-10, multiplies current timeframe to determine analysis timeframe (4x on 15min = 1hour)
Visual Settings
Bullish Color – Default: Green (#089981), sets color for bullish Order Blocks, FVGs, and structure elements
Bearish Color – Default: Red (#f23645), defines color for bearish elements
Neutral Color – Default: Gray (#787b86), controls color of mitigated zones and neutral elements
Show Educational Labels – Default: On, displays text labels on zones identifying type (OB, FVG, BOS), disable once familiar with patterns
Order Block Transparency – Default: 92, Range: 80-98, controls Order Block box transparency
FVG Transparency – Default: 92, Range: 80-98, sets Fair Value Gap zone transparency independently from Order Blocks
Alert Settings
Alert on Order Block Formation – Default: On, triggers notification when new volume-validated Order Block detected
Alert on FVG Formation – Default: On, sends alert when Fair Value Gap appears enabling quick response to imbalances
Alert on Break of Structure – Default: On, notifies when BOS or CHoCH confirmed
Alert on High Smart Money Score – Default: On, alerts when Smart Money Score crosses above 70 threshold indicating high-probability setup
✅Best Use Cases
Order Block Retest Entries – After Break of Structure, wait for price retrace into fresh bullish Order Block with Smart Money Score >70, enter long on zone reaction targeting next liquidity level
Fair Value Gap Retracement Trading – When price creates FVG during strong move then retraces, enter as price approaches unfilled gap expecting institutional orders to continue trend
Liquidity Sweep Reversals – Monitor price approaching swing high/low liquidity zones against prevailing Smart Money Score trend, after stop hunt sweep watch for rejection into premium Order Block/FVG
Multi-Timeframe Confluence Setups – Identify alignment when current timeframe Order Block coincides with higher timeframe FVG plus MTF analysis showing matching trend bias
Break of Structure Continuations – After BOS confirms trend direction, trade pullbacks to nearest Order Block or FVG in direction of structure break using Smart Money Score >70 as entry filter
Change of Character Reversal Plays – When CHoCH detected indicating potential reversal, look for Smart Money Score pivot with opposing Order Block formation then enter on structure confirmation
⚠️Limitations
Lagging Pivot Calculations – Pivot-based features (Liquidity Zones, Market Structure) require bars to right of pivot for confirmation, meaning these elements identify levels retrospectively with delay equal to lookback period
Whipsaw in Ranging Markets – During choppy conditions, Order Blocks fail frequently and structure breaks produce false signals as Smart Money Score fluctuates without clear institutional bias, best used in trending markets
Volume Data Dependency – Order Block volume validation requires accurate volume data which may be incomplete on Forex pairs or limited in crypto exchange feeds
Subjectivity in Scoring Weights – Proprietary 25-20-20-20-15 weighting reflects general institutional behavior but may not optimize for specific instruments or market regimes, user cannot adjust factor weights
Visual Complexity on Lower Timeframes – Sub-hour timeframes generate excessive zones creating cluttered charts, requires aggressive display limit reduction and higher minimum thresholds
No Fundamental Integration – Indicator analyzes purely technical price action and volume without incorporating economic events, news catalysts, or fundamental shifts that override technical levels
💡What Makes This Unique
Unified SMC Ecosystem – Unlike indicators displaying Order Blocks OR FVGs OR Liquidity separately, SMFI combines all three institutional concepts plus market structure into single cohesive system
Proprietary Confidence Scoring – Rather than manual setup assessment, automated Smart Money Score quantifies probability by weighting five institutional dimensions into actionable 0-100 rating
Volume-Filtered Quality – Eliminates weak Order Blocks forming without institutional volume confirmation, ensuring displayed zones represent genuine accumulation/distribution
Adaptive Lifecycle Management – Automatically updates mitigation status and removes aged zones preventing trades on dead levels through continuous validity and age monitoring
Educational Integration – Built-in tooltips, labeled zones, and reference panel make indicator functional for both learning Smart Money Concepts and executing strategies
🔬How It Works
Order Block Detection – Scans for patterns where strong directional move follows counter-move creating last down-candle before rally (bullish OB) or last up-candle before sell-off (bearish OB), validates formations only when candle exhibits volume exceeding configurable multiple (default 1.5x) of 20-bar average volume
Fair Value Gap Identification – Compares current candle’s high/low against two-candles-prior low/high to detect price imbalances, calculates gap size as percentage of close and filters micro-gaps below minimum threshold (default 0.3%), monitors whether subsequent price fills 50% triggering mitigation status
Liquidity Zone Mapping – Employs pivot detection using configurable lookback (default 50 bars) to identify swing highs/lows where retail stops cluster, extends horizontal reference lines from pivot creation and applies age-based filtering to remove stale zones
Market Structure Analysis – Tracks pivot progression using structure-specific lookback (default 5 bars) to determine trend, confirms uptrend when new pivot high exceeds previous by minimum move percentage, detects Break of Structure when price breaks recent pivot level, flags Change of Character for potential reversals
Multi-Timeframe Confluence – When enabled, requests security data from higher timeframe (current TF × HTF multiplier, default 4x), compares HTF close against HTF 20-period MA to determine bias, contributes ±50 points to score ensuring alignment with institutional positioning on superior timeframe
Smart Money Score Calculation – Evaluates Order Block component via ATR-normalized distance producing max 100-point contribution weighted at 25%, assesses FVG factor through age penalty and distance at 20% weight, calculates Liquidity proximity at 20%, incorporates structure bias (±50-100 points) at 20%, adds MTF component at 15%, applies 3-period smoothing to reduce volatility
Visual Rendering and Lifecycle – Draws Order Block boxes, Fair Value Gap rectangles with color coding (green/red active, gray mitigated), extends liquidity dashed lines with fade-by-age opacity, plots BOS labels, displays Smart Money Score dashboard, continuously updates checking mitigation conditions and removing elements exceeding age/display limits
💡Note:
The Smart Money Flow Index combines multiple Smart Money Concepts into unified institutional order flow analysis. For optimal results, use the Smart Money Score as confluence filter rather than standalone entry signal – scores above 70 indicate high-probability setups but should be combined with risk management, higher timeframe bias, and market regime understanding.
Opening Range Breakout with Multi-Timeframe Liquidity]═══════════════════════════════════════
OPENING RANGE BREAKOUT WITH MULTI-TIMEFRAME LIQUIDITY
═══════════════════════════════════════
A professional Opening Range Breakout (ORB) indicator enhanced with multi-timeframe liquidity detection, trading session visualization, volume analysis, and trend confirmation tools. Designed for intraday trading with comprehensive alert system.
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WHAT THIS INDICATOR DOES
───────────────────────────────────────
This indicator combines multiple trading concepts:
- Opening Range Breakout (ORB) - Customizable time period detection with automatic high/low identification
- Multi-Timeframe Liquidity - HTF (Higher Timeframe) and LTF (Lower Timeframe) key level detection
- Trading Sessions - Tokyo, London, New York, and Sydney session visualization
- Volume Analysis - Volume spike detection and strength measurement
- Multi-Timeframe Confirmation - Trend bias from higher timeframes
- EMA Integration - Trend filter and dynamic support/resistance
- Smart Alerts - Quality-filtered breakout notifications
───────────────────────────────────────
HOW IT WORKS
───────────────────────────────────────
OPENING RANGE BREAKOUT (ORB):
Concept:
The Opening Range is a period at the start of a trading session where price establishes an initial high and low. Breakouts beyond this range often indicate the direction of the day's trend.
Detection Method:
- Default: 15-minute opening range (configurable)
- Custom Range: Set specific session times with timezone support
- Automatically identifies ORH (Opening Range High) and ORL (Opening Range Low)
- Tracks ORB mid-point for reference
Range Establishment:
1. Session starts (or custom time begins)
2. Tracks highest high and lowest low during the period
3. Range confirmed at end of opening period
4. Levels extend throughout the session
Breakout Detection:
- Bullish Breakout: Close above ORH
- Bearish Breakout: Close below ORL
- Mid-point acts as bias indicator
Visual Display:
- Shaded box during range formation
- Horizontal lines for ORH, ORL, and mid-point
- Labels showing level values
- Color-coded fills based on selected method
Fill Color Methods:
1. Session Comparison:
- Green: Current OR mid > Previous OR mid
- Red: Current OR mid < Previous OR mid
- Gray: Equal or first session
- Shows day-over-day momentum
2. Breakout Direction (Recommended):
- Green: Price currently above ORH (bullish breakout)
- Red: Price currently below ORL (bearish breakout)
- Gray: Price inside range (no breakout)
- Real-time breakout status
MULTI-TIMEFRAME LIQUIDITY:
Two-Tier System for comprehensive level identification:
HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily, Weekly)
- Identifies major institutional levels
- Uses pivot detection with adjustable parameters
- Suitable for swing highs/lows where large orders rest
LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Provides precision entry/exit levels
- Finer granularity for intraday trading
- Captures minor swing points
Calculation Method:
- Pivot high/low detection algorithm
- Configurable left bars (lookback) and right bars (confirmation)
- Timeframe multiplier for accurate multi-timeframe detection
- Automatic level extension
Mitigation System:
- Tracks when levels are swept (broken)
- Configurable mitigation type: Wick or Close-based
- Option to remove or show mitigated levels
- Display limit prevents chart clutter
Asset-Specific Optimization:
The indicator includes quick reference settings for different assets:
- Major Forex (EUR/USD, GBP/USD): Default settings optimal
- Crypto (BTC/ETH): Left=12, Right=4, Display=7
- Gold: HTF=1D, Left=20
TRADING SESSIONS:
Four Major Sessions with Full Customization:
Tokyo Session:
- Default: 04:00-13:00 UTC+4
- Asian trading hours
- Often sets daily range
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional activity
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High-impact news events
Sydney Session:
- Default: 01:00-10:00 UTC+4
- Earliest Asian activity
- Lower volatility
Session Features:
- Shaded background boxes
- Session name labels
- Optional open/close lines
- Session high/low tracking with colored lines
- Each session has independent color settings
- Fully customizable times and timezones
VOLUME ANALYSIS:
Volume-Based Trade Confirmation:
Volume MA:
- Configurable period (default: 20)
- Establishes average volume baseline
- Used for spike detection
Volume Spike Detection:
- Identifies when volume exceeds MA * multiplier
- Default: 1.5x average volume
- Confirms breakout strength
Volume Strength Measurement:
- Calculates current volume as percentage of average
- Shows relative volume intensity
- Used in alert quality filtering
High Volume Bars:
- Identifies bars above 50th percentile
- Additional confirmation layer
- Indicates institutional participation
MULTI-TIMEFRAME CONFIRMATION:
Trend Bias from Higher Timeframes:
HTF 1 (Trend):
- Default: 1H timeframe
- Uses EMA to determine intermediate trend
- Compares current timeframe EMA to HTF EMA
HTF 2 (Bias):
- Default: 4H timeframe
- Uses 50 EMA for longer-term bias
- Confirms overall market direction
Bias Classifications:
- Bullish Bias: HTF close > HTF 50 EMA AND Current EMA > HTF1 EMA
- Bearish Bias: HTF close < HTF 50 EMA AND Current EMA < HTF1 EMA
- Neutral Bias: Mixed signals between timeframes
EMA Stack Analysis:
- Compares EMA alignment across timeframes
- +1: Bullish stack (lower TF EMA > higher TF EMA)
- -1: Bearish stack (lower TF EMA < higher TF EMA)
- 0: Neutral/crossed
Usage:
- Filters false breakouts
- Confirms trend direction
- Improves trade quality
EMA INTEGRATION:
Dynamic EMA for Trend Reference:
Features:
- Configurable period (default: 20)
- Customizable color and width
- Acts as dynamic support/resistance
- Trend filter for ORB trades
Application:
- Above EMA: Favor long breakouts
- Below EMA: Favor short breakouts
- EMA cross: Potential trend change
- Distance from EMA: Momentum gauge
SMART ALERT SYSTEM:
Quality-Filtered Breakout Notifications:
Alert Types:
1. Standard ORB Breakout
2. High Quality ORB Breakout
Quality Criteria:
- Volume Confirmation: Volume > 1.2x average
- MTF Confirmation: Bias aligned with breakout direction
Standard Alert:
- Basic breakout detection
- Price crosses ORH or ORL
- Icon: 🚀 (bullish) or 🔻 (bearish)
High Quality Alert:
- Both volume AND MTF confirmed
- Stronger probability setup
- Icon: 🚀⭐ (bullish) or 🔻⭐ (bearish)
Alert Information Includes:
- Alert quality rating
- Breakout level and current price
- Volume strength percentage (if enabled)
- MTF bias status (if enabled)
- Recommended action
One Alert Per Bar:
- Prevents alert spam
- Uses flag system to track sent alerts
- Resets on new ORB session
───────────────────────────────────────
HOW TO USE
───────────────────────────────────────
OPENING RANGE SETUP:
Basic Configuration:
1. Select time period for opening range (default: 15 minutes)
2. Choose fill color method (Breakout Direction recommended)
3. Enable historical data display if needed
Custom Range (Advanced):
1. Enable Custom Range toggle
2. Set specific session time (e.g., 0930-0945)
3. Select appropriate timezone
4. Useful for specific market opens (NYSE, LSE, etc.)
LIQUIDITY LEVELS SETUP:
Quick Configuration by Asset:
- Forex: Use default settings (Left=15, Right=5)
- Crypto: Set Left=12, Right=4, Display=7
- Gold: Set HTF=1D, Left=20
HTF Liquidity:
- Purpose: Major support/resistance levels
- Recommended: 4H for day trading, 1D for swing trading
- Use as profit targets or reversal zones
LTF Liquidity:
- Purpose: Entry/exit refinement
- Recommended: 1H for day trading, 4H for swing trading
- Use for position management
Mitigation Settings:
- Wick-based: More sensitive (default)
- Close-based: More conservative
- Remove or Show mitigated levels based on preference
TRADING SESSIONS SETUP:
Enable/Disable Sessions:
- Master toggle for all sessions
- Individual session controls
- Show/hide session names
Session High/Low Lines:
- Enable to see session extremes
- Each session has custom colors
- Useful for range trading
Customization:
- Adjust session times for your broker
- Set timezone to match your location
- Customize colors for visibility
VOLUME ANALYSIS SETUP:
Enable Volume Analysis:
1. Toggle on Volume Analysis
2. Set MA length (20 recommended)
3. Adjust spike multiplier (1.5 typical)
Usage:
- Confirm breakouts with volume
- Identify climactic moves
- Filter false signals
MULTI-TIMEFRAME SETUP:
HTF Selection:
- HTF 1 (Trend): 1H for day trading, 4H for swing
- HTF 2 (Bias): 4H for day trading, 1D for swing
Interpretation:
- Trade only with bias alignment
- Neutral bias: Be cautious
- Bias changes: Potential reversals
EMA SETUP:
Configuration:
- Period: 20 for responsive, 50 for smoother
- Color: Choose contrasting color
- Width: 1-2 for visibility
Usage:
- Filter trades: Long above, Short below
- Dynamic support/resistance reference
- Trend confirmation
ALERT SETUP:
TradingView Alert Creation:
1. Enable alerts in indicator settings
2. Enable ORB Breakout Alerts
3. Right-click chart → Add Alert
4. Select this indicator
5. Choose "Any alert() function call"
6. Configure delivery method (mobile, email, webhook)
Alert Filtering:
- All alerts include quality rating
- High Quality alerts = Volume + MTF confirmed
- Standard alerts = Basic breakout only
───────────────────────────────────────
TRADING STRATEGIES
───────────────────────────────────────
CLASSIC ORB STRATEGY:
Setup:
1. Wait for opening range to complete
2. Price breaks and closes above ORH or below ORL
3. Volume > average (if enabled)
4. MTF bias aligned (if enabled)
Entry:
- Bullish: Buy on break above ORH
- Bearish: Sell on break below ORL
- Consider retest entries for better risk/reward
Stop Loss:
- Bullish: Below ORL or range mid-point
- Bearish: Above ORH or range mid-point
- Adjust based on volatility
Targets:
- Initial: Range width extension (ORH + range width)
- Secondary: HTF liquidity levels
- Final: Session high/low or major support/resistance
ORB + LIQUIDITY CONFLUENCE:
Enhanced Setup:
1. Opening range established
2. HTF liquidity level near or beyond ORH/ORL
3. Breakout occurs with volume
4. Price targets the liquidity level
Entry:
- Enter on ORB breakout
- Target the HTF liquidity level
- Use LTF liquidity for position management
Management:
- Partial profits at ORB + range width
- Move stop to breakeven at LTF liquidity
- Final exit at HTF liquidity sweep
ORB REJECTION STRATEGY (Counter-Trend):
Setup:
1. Price breaks above ORH or below ORL
2. Weak volume (below average)
3. MTF bias opposite to breakout
4. Price closes back inside range
Entry:
- Failed bullish break: Short below ORH
- Failed bearish break: Long above ORL
Stop Loss:
- Beyond the failed breakout level
- Or beyond session extreme
Target:
- Opposite end of opening range
- Range mid-point for partial profit
SESSION-BASED ORB TRADING:
Tokyo Session:
- Typically narrower ranges
- Good for range trading
- Wait for London open breakout
London Session:
- Highest volume and volatility
- Strong ORB setups
- Major liquidity sweeps common
New York Session:
- Strong trending moves
- News-driven volatility
- Good for momentum trades
Sydney Session:
- Quieter conditions
- Suitable for range strategies
- Sets up Tokyo session
EMA-FILTERED ORB:
Rules:
- Only take bullish breaks if price > EMA
- Only take bearish breaks if price < EMA
- Ignore counter-trend breaks
Benefits:
- Reduces false signals
- Aligns with larger trend
- Improves win rate
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CONFIGURATION GUIDE
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OPENING RANGE SETTINGS:
Time Period:
- 15 min: Standard for most markets
- 30 min: Wider range, fewer breakouts
- 60 min: For slower markets or swing trades
Custom Range:
- Use for specific market opens
- NYSE: 0930-1000 EST
- LSE: 0800-0830 GMT
- Set timezone to match exchange
Historical Display:
- Enable: See all previous session data
- Disable: Cleaner chart, current session only
LIQUIDITY SETTINGS:
Left Bars (5-30):
- Lower: More frequent, sensitive levels
- Higher: Fewer, more significant levels
- Recommended: 15 for most markets
Right Bars (1-25):
- Confirmation period
- Higher: More reliable, less frequent
- Recommended: 5 for balance
Display Limit (1-20):
- Number of active levels shown
- Higher: More context, busier chart
- Recommended: 7 for clarity
Extension Options:
- Short: Levels visible near formation
- Current: Extended to current bar (recommended)
- Max: Extended indefinitely
VOLUME SETTINGS:
MA Length (5-50):
- Shorter: More responsive to spikes
- Longer: Smoother baseline
- Recommended: 20 for balance
Spike Multiplier (1.0-3.0):
- Lower: More sensitive spike detection
- Higher: Only extreme spikes
- Recommended: 1.5 for day trading
MULTI-TIMEFRAME SETTINGS:
HTF 1 (Trend):
- 5m chart: Use 15m or 1H
- 15m chart: Use 1H or 4H
- 1H chart: Use 4H or 1D
HTF 2 (Bias):
- One level higher than HTF 1
- Provides longer-term context
- Don't use same as HTF 1
EMA SETTINGS:
Length:
- 20: Responsive, more signals
- 50: Smoother, stronger filter
- 200: Long-term trend only
Style:
- Choose contrasting color
- Width 1-2 for visibility
- Match your trading style
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BEST PRACTICES
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Chart Timeframe Selection:
- ORB Trading: Use 5m or 15m charts
- Session Review: Use 1H or 4H charts
- Swing Trading: Use 1H or 4H charts
Quality Over Quantity:
- Wait for high-quality alerts (volume + MTF)
- Avoid trading every breakout
- Focus on confluence setups
Risk Management:
- Position size based on range width
- Wider ranges = smaller positions
- Use stop losses always
- Take partial profits at targets
Market Conditions:
- Best results in trending markets
- Reduce position size in choppy conditions
- Consider session overlaps for volatility
- Avoid trading near major news if inexperienced
Continuous Improvement:
- Track win rate by session
- Note which confluence factors work best
- Adjust settings based on market volatility
- Review performance weekly
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PERFORMANCE OPTIMIZATION
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This indicator is optimized with:
- max_bars_back declarations for efficient processing
- Conditional calculations based on enabled features
- Proper memory management for drawing objects
- Minimal recalculation on each bar
Best Practices:
- Disable unused features (sessions, MTF, volume)
- Limit historical display to reduce rendering
- Use appropriate timeframe for your strategy
- Clear old drawing objects periodically
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EDUCATIONAL DISCLAIMER
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This indicator combines established trading concepts:
- Opening Range Breakout theory (price action)
- Liquidity level detection (pivot analysis)
- Session-based trading (time-of-day patterns)
- Volume analysis (confirmation technique)
- Multi-timeframe analysis (trend alignment)
All calculations use standard technical analysis methods:
- Pivot high/low detection algorithms
- Moving averages for trend and volume
- Session time filtering
- Timeframe security functions
The indicator identifies potential trading setups but does not predict future price movements. Success requires proper application within a complete trading strategy including risk management, position sizing, and market context.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Opening Range Breakout trading involves substantial risk. The alert system and quality filters are designed to identify potential setups but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results. Trading intraday breakouts requires experience and discipline.
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CREDITS & ATTRIBUTION
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ORIGINAL SOURCE:
This indicator builds upon concepts from LuxAlgo's-ORB
Linh Index Trend & Exhaustion SuitePurpose: One overlay to judge trend, reversal risk, overextension, and volatility squeezes on indexes (built for VNINDEX/VN30, works on any symbol & timeframe).
What it shows
Trend state: Bull / Bear / Transition via 20/50/200 EMAs + slope check.
Overextension heatmap: Background paints when price is stretched vs the 20-EMA by ATR or % (you set the thresholds).
Squeeze detection:
Squeeze ON (yellow dot): Bollinger Bands (20,2) inside Keltner Channels (20,1.5).
Squeeze OFF + Release: White dot; script confirms direction only when close > BB upper (up) or close < BB lower (down).
52-week context: Distance to 52-week high/low (%).
Higher-TF alignment: Optional weekly trend reading shown on the label while you’re on the daily.
Anchored VWAP(s): Two optional AVWAPs from dates you choose (e.g., YTD open, last big gap/earnings).
Plots & labels
EMAs 20/50/200 (toggle on/off).
Optional BB & KC bands for diagnostics.
AVWAP #1 / #2 (optional).
Status label with: Trend, EMAs, Dist to 20-EMA (%, ATR), 52-week distances, HTF state.
Built-in alerts (set “Once per bar close”)
EMA10 ↔ EMA20 cross (early momentum shift)
EMA20 ↔ EMA50 cross (trend confirmation/negation)
Price ↔ EMA200 cross (long-term regime)
Squeeze Release UP / DOWN (BB breakout after squeeze)
Overextension Cool-off UP / DN (stretched vs 20-EMA + momentum rolling)
Near 52-week High (within your % threshold)
How to use (playbook)
Map regime: Prefer trades when Daily = Bull and HTF (Weekly) = Bull (shown on label).
Hunt expansion: Yellow → White dot and close beyond BB = fresh move.
Avoid chasing stretch: If background is painted (overextended vs 20-EMA), wait for a pullback or intraday base.
Locations matter: 52-week proximity + HTF Bull improves breakout quality.
Anchors: Add AVWAP from YTD open or last major gap to frame support/resistance.
Suggested settings
Overextension: ATR = 2.0, % = 4.0 to start; tune per index volatility.
Squeeze bands: BB(20,2) & KC(20,1.5) default are balanced; tighten KC (1.3) for more signals, widen (1.8) for fewer/higher quality.
Timeframes: Daily for signals, Weekly for bias. Optional 65-min for entries.
EMA Crossover Strategy with Take Profit and Candle HighlightingStrategy Overview:
This strategy is based on the Exponential Moving Averages (EMA), specifically the EMA 20 and EMA 50. It takes advantage of EMA crossovers to identify potential trend reversals and uses multiple take-profit levels and a stop-loss for risk management.
Key Components:
EMA Crossover Signals:
Buy Signal (Uptrend): A buy signal is generated when the EMA 20 crosses above the EMA 50, signaling the start of a potential uptrend.
Sell Signal (Downtrend): A sell signal is generated when the EMA 20 crosses below the EMA 50, signaling the start of a potential downtrend.
Take Profit Levels:
Once a buy or sell signal is triggered, the strategy calculates multiple take-profit levels based on the range of the previous candle. The user can define multipliers for each take-profit level.
Take Profit 1 (TP1): 50% of the previous candle's range above or below the entry price.
Take Profit 2 (TP2): 100% of the previous candle's range above or below the entry price.
Take Profit 3 (TP3): 150% of the previous candle's range above or below the entry price.
Take Profit 4 (TP4): 200% of the previous candle's range above or below the entry price.
These levels are adjusted dynamically based on the previous candle's high and low, so they adapt to changing market conditions.
Stop Loss:
A stop-loss is set to manage risk. The default stop-loss is 3% from the entry price, but this can be adjusted in the settings. The stop-loss is triggered if the price moves against the position by this amount.
Trend Direction Highlighting:
The strategy highlights the bars (candles) with colors:
Green bars indicate an uptrend (when EMA 20 crosses above EMA 50).
Red bars indicate a downtrend (when EMA 20 crosses below EMA 50).
These visual cues help users easily identify the market direction.
Strategy Entries and Exits:
Entries: The strategy enters a long (buy) position when the EMA 20 crosses above the EMA 50 and a short (sell) position when the EMA 20 crosses below the EMA 50.
Exits: The strategy exits the positions at any of the defined take-profit levels or the stop-loss. Multiple exit levels provide opportunities to take profit progressively as the price moves in the favorable direction.
Entry and Exit Conditions in Detail:
Buy Entry Condition (Uptrend):
A buy position is opened when EMA 20 crosses above EMA 50, signaling the start of an uptrend.
The strategy calculates take-profit levels above the entry price based on the previous bar's range (high-low) and the multipliers for TP1, TP2, TP3, and TP4.
Sell Entry Condition (Downtrend):
A sell position is opened when EMA 20 crosses below EMA 50, signaling the start of a downtrend.
The strategy calculates take-profit levels below the entry price, similarly based on the previous bar's range.
Exit Conditions:
Take Profit: The strategy attempts to exit the position at one of the take-profit levels (TP1, TP2, TP3, or TP4). If the price reaches any of these levels, the position is closed.
Stop Loss: The strategy also has a stop-loss set at a default value (3% below the entry for long trades, and 3% above for short trades). The stop-loss helps to protect the position from significant losses.
Backtesting and Performance Metrics:
The strategy can be backtested using TradingView's Strategy Tester. The results will show how the strategy would have performed historically, including key metrics like:
Net Profit
Max Drawdown
Win Rate
Profit Factor
Average Trade Duration
These performance metrics can help users assess the strategy's effectiveness over historical periods and optimize the input parameters (e.g., multipliers, stop-loss level).
Customization:
The strategy allows for the adjustment of several key input values via the settings panel:
Take Profit Multipliers: Users can customize the multipliers for each take-profit level (TP1, TP2, TP3, TP4).
Stop Loss Percentage: The user can also adjust the stop-loss percentage to a custom value.
EMA Periods: The default periods for the EMA 50 and EMA 20 are fixed, but they can be adjusted for different market conditions.
Pros of the Strategy:
EMA Crossover Strategy: A classic and well-known strategy used by traders to identify the start of new trends.
Multiple Take Profit Levels: By taking profits progressively at different levels, the strategy locks in gains as the price moves in favor of the position.
Clear Trend Identification: The use of green and red bars makes it visually easier to follow the market's direction.
Risk Management: The stop-loss and take-profit features help to manage risk and optimize profit-taking.
Cons of the Strategy:
Lagging Indicators: The strategy relies on EMAs, which are lagging indicators. This means that the strategy might enter trades after the trend has already started, leading to missed opportunities or less-than-ideal entry prices.
No Confirmation Indicators: The strategy purely depends on the crossover of two EMAs and does not use other confirming indicators (e.g., RSI, MACD), which might lead to false signals in volatile markets.
How to Use in Real-Time Trading:
Use for Backtesting: Initially, use this strategy in backtest mode to understand how it would have performed historically with your preferred settings.
Paper Trading: Once comfortable, you can use paper trading to test the strategy in real-time market conditions without risking real money.
Live Trading: After testing and optimizing the strategy, you can consider using it for live trading with proper risk management in place (e.g., starting with a small position size and adjusting parameters as needed).
Summary:
This strategy is designed to identify trend reversals using EMA crossovers, with customizable take-profit levels and a stop-loss to manage risk. It's well-suited for traders looking for a systematic way to enter and exit trades based on clear market signals, while also providing flexibility to adjust for different risk profiles and trading styles.
Market Analysis Assistant This indicator uniquely maps and interprets key market conditions using Moving Averages, MACD, RSI, and Bollinger Bands. Unlike traditional indicators that only display visual signals, this tool provides written analysis directly on your chart as soon as specific conditions are met. This feature makes it easier to understand the market’s current state and anticipate potential moves.
Why Moving Averages? Moving Averages are essential for identifying the overall trend of the market. By analyzing the 200, 20, and 9-period Moving Averages, this indicator helps traders quickly determine whether the market is in an uptrend, downtrend, or sideways phase. The integration of multiple averages offers a comprehensive view, allowing for more accurate trend identification.
Why MACD? The MACD is a powerful tool for spotting trend reversals and momentum shifts. By monitoring MACD crossovers, divergences, and the position of the MACD line relative to the zero line, this indicator helps you identify potential changes in the trend direction before they fully develop, giving you a critical edge.
Why RSI? RSI is crucial for understanding the market's overbought and oversold conditions. By tracking RSI levels and its crossover with its moving average, this indicator provides early warnings for potential trend reversals or continuations, helping you time your entries and exits more effectively.
Why Bollinger Bands? Bollinger Bands are used to measure market volatility and identify breakout opportunities. By analyzing the price’s relationship with the upper and lower bands, this indicator helps traders spot potential overbought or oversold conditions, as well as possible breakout scenarios, offering a clear view of market dynamics.
Trend Identification (getTrend()): Detects whether the market is in an uptrend, downtrend, or sideways phase by analyzing the position of the price relative to the 200, 20, and 9-period moving averages.
MACD Analysis (analyzeMACD()): Identifies potential trend reversals or continuations through MACD divergence, crossovers, and the MACD signal line's position relative to the zero line.
RSI Monitoring (analyzeRSI()): Detects overbought and oversold conditions and anticipates trend continuation or corrections based on RSI crossings with its moving average.
Trap Zone Detection (analyzeTrapZone()): Highlights areas of potential price consolidation between the 20 and 200-period moving averages, indicating possible breakouts.
Bollinger Bands Analysis (analyzeBollingerBands()): Analyzes the price’s relationship with Bollinger Bands to identify overbought/oversold conditions, breakouts, and potential trend continuations or correction.
Fibonacci retracement will also check the moment the price tests a monthly or daily weekly Fibonacci retracement
What Makes This Indicator Unique?
This indicator stands out by transforming complex technical analysis into clear, written insights directly on your chart. As soon as specific conditions are met—such as a MACD crossover or an RSI overbought/oversold level—this tool immediately displays a written summary of the event, helping traders to quickly understand and act on market developments.
How to Use My Indicator:
The indicator is designed to provide detailed, real-time market condition analysis using Moving Averages, MACD, RSI, and Bollinger Bands. When certain market conditions are met, such as the price testing a specific moving average or the MACD indicating a potential reversal, the indicator displays this information in written form directly on the chart, in both English and Portuguese.
How to Interpret the Displayed Information:
The information displayed by the indicator can be used for:
Identifying Support and Resistance: The indicator can help identify when the price is testing an important support or resistance level, such as a moving average or a Fibonacci level, allowing the user to decide whether to enter or exit a position.
Trend Detection: If the indicator shows that the price is above the 200, 20, and 9-period moving averages, this may be a sign of an uptrend, indicating that the user should consider maintaining or opening buy positions.
Correction Signals: When the MACD indicates a potential correction, the user may decide to protect their profits by adjusting stops or even exiting the position to avoid losses.
Identifying Overbought/Oversold Conditions: Based on the RSI, the indicator can alert to overbought or oversold conditions, helping the user avoid entering a trade at an unfavorable time.
Example of Use:
the indicator shows several important pieces of information, such as:
"US100 Price is at the 50.0% Fibonacci level (Last Monthly)."
This suggests that the price is testing a significant Fibonacci level, which could be a point of reversal or continuation. A trader can use this information to adjust their entry or exit strategy.
"DXY RSI below 30: Indication of oversold condition"
This indicates that the DXY is in an oversold condition, which might suggest an upcoming bullish reversal. A trader could consider this when trading DXY-related assets.
"Bullish Trend: Price is above the 200, 20, and 9-period moving averages."
This confirms an uptrend, giving the user more confidence to hold long positions.
Availability:
This indicator is available in two languages: English and Portuguese. It is ideal for traders who prefer analysis in English as well as those who prefer it in Portuguese, making it a versatile and accessible tool for traders from different backgrounds
Este indicador mapeia e interpreta de forma única as principais condições de mercado utilizando Médias Móveis, MACD, RSI e Bandas de Bollinger. Ao contrário dos indicadores tradicionais que apenas exibem sinais visuais, esta ferramenta oferece uma análise escrita diretamente no seu gráfico assim que determinadas condições são atendidas. Isso facilita o entendimento do estado atual do mercado e a antecipação de possíveis movimentos.
Por que Médias Móveis? As Médias Móveis são essenciais para identificar a tendência geral do mercado. Ao analisar as Médias Móveis de 200, 20 e 9 períodos, este indicador ajuda os traders a determinarem rapidamente se o mercado está em tendência de alta, baixa ou em fase lateral. A integração de múltiplas médias oferece uma visão abrangente, permitindo uma identificação mais precisa das tendências.
Por que MACD? O MACD é uma ferramenta poderosa para identificar reversões de tendência e mudanças de momentum. Monitorando os cruzamentos do MACD, divergências e a posição da linha MACD em relação à linha zero, este indicador ajuda você a identificar possíveis mudanças na direção da tendência antes que elas se desenvolvam completamente, dando-lhe uma vantagem crítica.
Por que RSI? O RSI é crucial para entender as condições de sobrecompra e sobrevenda do mercado. Acompanhando os níveis do RSI e seu cruzamento com sua média móvel, este indicador fornece avisos antecipados para possíveis reversões ou continuações de tendência, ajudando você a cronometrar suas entradas e saídas de forma mais eficaz.
Por que Bandas de Bollinger? As Bandas de Bollinger são usadas para medir a volatilidade do mercado e identificar oportunidades de rompimento. Ao analisar a relação do preço com as bandas superior e inferior, este indicador ajuda os traders a identificar condições de sobrecompra ou sobrevenda, bem como possíveis cenários de rompimento, oferecendo uma visão clara da dinâmica do mercado.
Identificação de Tendências (getTrend()): Detecta se o mercado está em tendência de alta, baixa ou em fase lateral, analisando a posição do preço em relação às médias móveis de 200, 20 e 9 períodos.
Análise de MACD (analyzeMACD()): Identifica possíveis reversões ou continuações de tendência através de divergências do MACD, cruzamentos, e a posição da linha de sinal do MACD em relação à linha zero.
Monitoramento do RSI (analyzeRSI()): Detecta condições de sobrecompra e sobrevenda e antecipa a continuação da tendência ou correções com base nos cruzamentos do RSI com sua média móvel.
Detecção de Zona de Armadilha (analyzeTrapZone()): Destaca áreas de possível consolidação de preços entre as médias móveis de 20 e 200 períodos, indicando possíveis rompimentos.
Análise das Bandas de Bollinger (analyzeBollingerBands()): Analisa a relação do preço com as Bandas de Bollinger para identificar condições de sobrecompra/sobrevenda, rompimentos e possíveis continuações de tendência ou correção.
A retração de Fibonacci também verificará o momento em que o preço testa uma retração de Fibonacci semanal mensal ou diária
O que Torna Este Indicador Único?
Este indicador se destaca por transformar análises técnicas complexas em insights escritos claros diretamente no seu gráfico. Assim que condições específicas são atendidas—como um cruzamento do MACD ou um nível de sobrecompra/sobrevenda do RSI—esta ferramenta exibe imediatamente um resumo escrito do evento, ajudando os traders a entenderem e agirem rapidamente sobre as mudanças do mercado.
Como Utilizar o Meu Indicador:
O indicador foi desenvolvido para oferecer uma análise detalhada e em tempo real das condições de mercado, utilizando os conceitos de Médias Móveis, MACD, RSI e Bandas de Bollinger. Quando certas condições de mercado são atingidas, como o preço testando uma média móvel específica ou o MACD indicando uma possível reversão, o indicador exibe essas informações de forma escrita diretamente no gráfico, em inglês e português.
Como Interpretar as Informações Exibidas:
As informações exibidas pelo indicador podem ser usadas para:
Identificação de Suportes e Resistências: O indicador pode ajudar a identificar quando o preço está testando um nível de suporte ou resistência importante, como uma média móvel ou um nível de Fibonacci, permitindo ao usuário decidir se deve entrar ou sair de uma posição.
Detecção de Tendências: Se o indicador mostra que o preço está acima das médias móveis de 200, 20 e 9 períodos, isso pode ser um sinal de uma tendência de alta, indicando que o usuário deve considerar manter ou abrir posições de compra.
Sinais de Correção: Quando o MACD indica uma possível correção, o usuário pode decidir proteger seus lucros ajustando os stops ou até mesmo saindo da posição para evitar perdas.
Identificação de Condições de Sobrecompra/Sobrevenda: Com base no RSI, o indicador pode alertar sobre condições de sobrecompra ou sobrevenda, ajudando o usuário a evitar entrar em uma operação em um momento desfavorável.
Exemplo de Utilização:
o indicador mostra várias informações importantes, como:
"O preço do US100 está no nível de Fibonacci de 50,0% (mês passado)."
Isso sugere que o preço está testando um nível significativo de Fibonacci, o que pode ser um ponto de reversão ou continuação. Um trader pode usar essa informação para ajustar sua estratégia de entrada ou saída.
DXY RSI abaixo de 30: Indicação de condição de sobrevenda"
Isso indica que o DXY está em uma condição de sobrevenda, o que pode sugerir uma reversão de alta em breve. Um trader pode considerar isso ao fazer operações relacionadas ao DXY.
"Tendência de alta: o preço está acima das médias móveis de 200, 20 e 9 períodos."
Isso confirma uma tendência de alta, dando ao usuário mais confiança para manter posições longas.
Disponibilidade:
Este indicador está disponível em dois idiomas: inglês e português. Ele é ideal tanto para traders que preferem análises em inglês quanto para aqueles que preferem em português. Isso o torna uma ferramenta versátil e acessível para traders de diferentes origens.
Turtle Trade Channels Indicator TUTCILegendary trade system which proved that great traders can be made, not born.
Turtle Trade Experiment made 80% annual return for 4 years and made 150 million $
Turtle Trade trend following system is a complete opposite to the "buy low and sell high" approach.
This trend following system was taught to a group of average and normal individuals, and almost everyone turned into a profitable trader.
They used the basis logic of well known DONCHIAN CHANNELS which developed by Richard Donchian.
The main rule is "Trade an 20-day breakout and take profits when an 10-day high or low is breached ". Examples:
Buy a 20-day breakout and close the trade when price action reaches a 10-day low.
Go short a 20-day breakout and close the trade when price action reaches a 10-day high.
In this indicator,
The red line is the trading line which indicates the trend directio n:
Price bars over the trend line indicates uptrend
Price bars under the trend line means downtrend
The dotted blue line is the exit line.
Original system is:
Go long when the price High is equal to or above previous 20 day Highest price.
Go short when the price Low is equal to or below previous 20 day Lowest price.
Exit long positions when the price touches the exit line
Exit short positions when the price touches the exit line
Recommended initial stop-loss is ATR * 2 from the opening price.
Default system parameters were 20,10 and 55,20.
Original Turtle Rules:
To trade exactly like the turtles did, you need to set up two indicators representing the main and the failsafe system.
Set up the main indicator with EntryPeriod = 20 and ExitPeriod = 10 (A.k.a S1)
Set up the failsafe indicator with EntryPeriod = 55 and ExitPeriod = 20 using a different color. (A.k.a S2)
The entry strategy using S1 is as follows
Buy 20-day breakouts using S1 only if last signaled trade was a loss.
Sell 20-day breakouts using S1 only if last signaled trade was a loss.
If last signaled trade by S1 was a win, you shouldn't trade -Irregardless of the direction or if you traded last signal it or not-
The entry strategy using S2 is as follows:
Buy 55-day breakouts only if you ignored last S1 signal and the market is rallying without you
Sell 55-day breakouts only if you ignored last S1 signal and the market is pluging without you
You can Highlight the chart with provided trade signals:
Green background color when Long
Red background color when Short
No background color when flat
WARNING: TURTLE TRADE STOP or ADDING more UNITS RULES ARE NOT INCLUDED.
Author: Kıvanç Özbilgiç
Also you can show or hide trade signals with the button on the settings menu
S&P Merval Index Volume Indicator (Shares, ARS, U$S CCL GGAL)S&P Merval Index Volume Indicator (Shares, ARS, U$S CCL GGAL)
◾ This indicator reflects a close estimate of the traded volume in the S&P Merval Index BCBA:IMV for nominal shares, traded money in ARS & USD using a financial FX rate.
◾ The constituents of the index "must meet minimum size and liquidity requirements" as it is been declared by S&P Dow Jones Indexes. On this version of the indicator were reflected the current set of stocks for the Index as of Monday, July 27, 2020 for actual and historical sessions.
◾ Eventually, there could be changes in consitutents as per the S&P Dow Jones Indexes classification and re-balance that will be reflected on this script or a new one.
◾ Aggregated volume of nominal shares for each of the stocks constitutents is multiplied by their closing prices to estimates the effective volume in ARS & adjusted by the FX rate with "Contado con Liquidación" FX rate closing session price.
◾ It serves as a dynamical volume indicator available for standard and customized timeframes. Provides an assertive look over trading activity which allows the analyst to measure effectively either resistance or support zones in Bull / Flat or Bear markets.
◾ Output of 10 trading days of effective volume was cross-checked with "IAMC Informe diario" www.iamc.com.ar the official daily report by the exchange ByMA (Bolsas y Mercados de Argentina).
1) Trading Sessions Dates
7/27/20; 7/23/20; 7/22/20; 7/21/20; 7/20/20; 7/16/20; 7/15/20; 7/14/20; 7/13/20
2) IAMC Informe Diario S&P Merval Index Effective volume (ARS) for each of 1)
$1309.4M; $1999.3M; $1691.1M; $1585.6M; $949.7M; $818.6M; $1010.4M; $962.3M; $1515.7M
3) Pine indicator S&P Merval Index Effective volume (ARS) for each 1)
$1294.6M; $1911.7M; $1691.3M; $1526.6M; $901.4M; $796.7M; $961.9M; $939.7M; $1404.7 M
4) Variance 3) | 2)
-1%; -4%; 0%; -4%; -5%; -3%; -5%; -2%; -7%
Average Deviation: -4%
Standard Deviation: 2%
* This quick analysis depicts that effective volume displayed may (or not) have a non significance variance over the real data reported by the National Exchange due to the script calculation.
* Thanks to Alan who helped me a lot with the code!
