Session Breakout Scalper Trading BotHi Traders !
Introduction:
I have recently been exploring the world of automated algorithmic trading (as I prefer more objective trading strategies over subjective technical analysis (TA)) and would like to share one of my automation compatible (PineConnecter compatible) scripts “Session Breakout Scalper”.
The strategy is really simple and is based on time conditional breakouts although has more ”relatively” advanced optional features such as the regime indicators (Regime Filters) that attempt to filter out noise by adding more confluence states and the ATR multiple SL that takes into account volatility to mitigate the down side risk of the trade.
What is Algorthmic Trading:
Firstly what is algorithmic trading? Algorithmic trading also known as algo-trading, is a method of using computer programs (in this case pine script) to execute trades based on predetermined rules and instructions (this trading strategy). It's like having a robot trader who follows a strict set of commands to buy and sell assets automatically, without any human intervention.
Important Note:
For Algorithmic trading the strategy will require you having an essential TV subscription at the minimum (so that you can set alerts) plus a PineConnecter subscription (scroll down to the .”How does the strategy send signals” headings to read more)
The Strategy Explained:
Is the Time input true ? (this can be changed by toggling times under the “TRADE MEDIAN TIMES” group for user inputs).
Given the above is true the strategy waits x bars after the session and then calculates the highest high (HH) to lowest low (LL) range. For this box to form, the user defined amount of bars must print after the session. The box is symmetrical meaning the HH and LL are calculated over a lookback that is equal to the sum of user defined bars before and after the session (+ 1).
The Strategy then simultaneously defines the HH as the buy level (green line) and the LL as the sell level (red line). note the strategy will set stop orders at these levels respectively.
Enter a buy if price action crosses above the HH, and then cancel the sell order type (The opposite is true for a stop order).
If the momentum based regime filters are true the strategy will check for the regime / regimes to be true, if the regime if false the strategy will exit the current trade, as the regime filter has predicted a slowing / reversal of momentum.
The image below shows the strategy executing these trading rules ( Regime filters, "Trades on chart", "Signal & Label" and "Quantity" have been omitted. "Strategy label plots" has been switched to true)
Other Strategy Rules:
If a new session (time session which is user defined) is true (blue vertical line) and the strategy is currently still in a trade it will exit that trade immediately.
It is possible to also set a range of percentage gain per day that the strategy will try to acquire, if at any point the strategy’s profit is within the percentage range then the position / trade will be exited immediately (This can be changed in the “PERCENT DAY GAIN” group for user inputs)
Stops and Targets:
The strategy has either static (fixed) or variable SL options. TP however is only static. The “STRAT TP & TP” group of user inputs is responsible for the SL and TP values (quoted in pips). Note once the ATR stop is set to true the SL values in the above group no longer have any affect on the SL as expected.
What are the Regime Filters:
The Larry Williams Large Trade Index (LWLTI): The Larry Williams Large Trade Index (LWTI) is a momentum-based technical indicator developed by iconic trader Larry Williams. It identifies potential entries and exits for trades by gauging market sentiment, particularly the buying and selling pressure from large market players. Here's a breakdown of the LWTI:
LWLTI components and their interpretation:
Oscillator: It oscillates between 0 and 100, with 50 acting as the neutral line.
Sentiment Meter: Values above 75 suggest a bearish market dominated by large selling, while readings below 25 indicate a bullish market with strong buying from large players.
Trend Confirmation: Crossing above 75 during an uptrend and below 25 during a downtrend confirms the trend's continuation.
The Andean Oscillator (AO) : The Andean Oscillator is a trend and momentum based indicator designed to measure the degree of variations within individual uptrends and downtrends in the prices.
Regime Filter States:
In trading, a regime filter is a tool used to identify the current state or "regime" of the market.
These Regime filters are integrated within the trading strategy to attempt to lower risk (equity volatility and/or draw down). The regime filters have different states for each market order type (buy and sell). When the regime filters are set to true, if these regime states fail to be true the trade is exited immediately.
For Buy Trades:
LWLTI positive momentum state: Quotient of the lagged trailing difference and the ATR > 50
AO positive momentum state: Bull line > Bear line (signal line is omitted)
For Sell Trades:
LWLTI negative momentum stat: Quotient of the lagged trailing difference and the ATR < 50
AO negative momentum state: Bull line < Bear line (signal line is omitted)
How does the Strategy Send Signals:
The strategy triggers a TV alert (you will neet to set a alert first), TV then sends a HTTP request to the automation software (PineConnecter) which receives the request and then communicates to an MT4/5 EA to automate the trading strategy.
For the strategy to send signals you must have the following
At least a TV essential subscription
This Script added to your chart
A PineConnecter account, which is paid and not free. This will provide you with the expert advisor that executes trades based on these strategies signals.
For more detailed information on the automation process I would recommend you read the PineConnecter documentation and FAQ page.
Dashboard:
This Dashboard (top right by defualt) lists some simple trading statistics and also shows when a trade is live.
Important Notice:
- USE THIS STRATEGY AT YOUR OWN RISK AND ALWAYS DO YOUR OWN RESEARCH & MANUAL BACKTESTING !
- THE STRATEGY WILL NOT EXHIBIT THE BACKTEST PERFORMANCE SEEN BELOW IN ALL MARKETS !
Buscar en scripts para "汇丰股票25"
Mike's Crossover BotGreetings! As a newcomer to coding, I've developed a simple trading bot for experimentation purposes. However, it's important to note that this bot has not undergone rigorous testing, so please exercise caution and use it at your own risk.
Bot Overview:
The bot operates by leveraging two technical indicators: Moving Average Convergence Divergence (MACD) with 7-day and 25-day parameters, and the Relative Strength Index (RSI). These indicators help identify potential buying and selling opportunities in the market.
MACD Crossovers:
The MACD is a trend-following momentum indicator that compares short-term and long-term moving averages. In our bot, we look for crossovers between the 7-day and 25-day MACD lines. A crossover occurs when these lines intersect, suggesting a potential change in market direction.
RSI Confirmation:
To refine our signals, we incorporate the Relative Strength Index (RSI). When a MACD crossover happens, the bot checks if the RSI is below 40. If it is, a buy signal is generated, indicating a potential undervalued condition. Conversely, when the RSI is above 60 during a crossover, a sell signal is triggered, suggesting a potentially overvalued condition.
Important Considerations:
New Coder Disclaimer: This bot is designed for educational purposes, especially for those who are new to coding. It serves as a learning tool and is not intended for live trading without proper testing.
Risk Awareness: Trading always involves risks, and the bot's performance has not been thoroughly tested in live market conditions. It's crucial to exercise caution and be aware of the inherent risks associated with financial markets.
Continuous Learning: Coding and algorithmic trading are dynamic fields. As you explore this bot, consider it a starting point for learning and continuously seek to enhance your understanding and skills in coding and trading strategies.
Remember, the success of any trading strategy depends on various factors, and past performance is not indicative of future results. Always conduct thorough testing before considering any automated strategy for live trading.
Adaptive MFT Extremum Pivots [Elysian_Mind]Adaptive MFT Extremum Pivots
Overview:
The Adaptive MFT Extremum Pivots indicator, developed by Elysian_Mind, is a powerful Pine Script tool that dynamically displays key market levels, including Monthly Highs/Lows, Weekly Extremums, Pivot Points, and dynamic Resistances/Supports. The term "dynamic" emphasizes the adaptive nature of the calculated levels, ensuring they reflect real-time market conditions. I thank Zandalin for the excellent table design.
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Chart Explanation:
The table, a visual output of the script, is conveniently positioned in the bottom right corner of the screen, showcasing the indicator's dynamic results. The configuration block, elucidated in the documentation, empowers users to customize the display position. The default placement is at the bottom right, exemplified in the accompanying chart.
The deliberate design ensures that the table does not obscure the candlesticks, with traders commonly situating it outside the candle area. However, the flexibility exists to overlay the table onto the candles. Thanks to transparent cells, the underlying chart remains visible even with the table displayed atop.
In the initial column of the table, users will find labels for the monthly high and low, accompanied by their respective numerical values. The default precision for these values is set at #.###, yet this can be adjusted within the configuration block to suit markets with varying degrees of volatility.
Mirroring this layout, the last column of the table presents the weekly high and low data. This arrangement is part of the upper half of the table. Transitioning to the lower half, users encounter the resistance levels in the first column and the support levels in the last column.
At the center of the table, prominently displayed, is the monthly pivot point. For a comprehensive understanding of the calculations governing these values, users can refer to the documentation. Importantly, users retain the freedom to modify these mathematical calculations, with the table seamlessly updating to reflect any adjustments made.
Noteworthy is the table's persistence; it continues to display reliably even if users choose to customize the mathematical calculations, providing a consistent and adaptable tool for informed decision-making in trading.
This detailed breakdown offers traders a clear guide to interpreting the information presented by the table, ensuring optimal use and understanding of the Adaptive MFT Extremum Pivots indicator.
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Usage:
Table Layout:
The table is a crucial component of this indicator, providing a structured representation of various market levels. Color-coded cells enhance readability, with blue indicating key levels and a semi-transparent background to maintain chart visibility.
1. Utilizing a Table for Enhanced Visibility:
In presenting this wealth of information, the indicator employs a table format beneath the chart. The use of a table is deliberate and offers several advantages:
2. Structured Organization:
The table organizes the diverse data into a structured format, enhancing clarity and making it easier for traders to locate specific information.
3. Concise Presentation:
A table allows for the concise presentation of multiple data points without cluttering the main chart. Traders can quickly reference key levels without distraction.
4. Dynamic Visibility:
As the market dynamically evolves, the table seamlessly updates in real-time, ensuring that the most relevant information is readily visible without obstructing the candlestick chart.
5. Color Coding for Readability:
Color-coded cells in the table not only add visual appeal but also serve a functional purpose by improving readability. Key levels are easily distinguishable, contributing to efficient analysis.
Data Values:
Numerical values for each level are displayed in their respective cells, with precision defined by the iPrecision configuration parameter.
Configuration:
// User configuration: You can modify this part without code understanding
// Table location configuration
// Position: Table
const string iPosition = position.bottom_right
// Width: Table borders
const int iBorderWidth = 1
// Color configuration
// Color: Borders
const color iBorderColor = color.new(color.white, 75)
// Color: Table background
const color iTableColor = color.new(#2B2A29, 25)
// Color: Title cell background
const color iTitleCellColor = color.new(#171F54, 0)
// Color: Characters
const color iCharColor = color.white
// Color: Data cell background
const color iDataCellColor = color.new(#25456E, 0)
// Precision: Numerical data
const int iPrecision = 3
// End of configuration
The code includes a configuration block where users can customize the following parameters:
Precision of Numerical Table Data (iPrecision):
// Precision: Numerical data
const int iPrecision = 3
This parameter (iPrecision) sets the precision of the numerical values displayed in the table. The default value is 3, displaying numbers in #.### format.
Position of the Table (iPosition):
// Position: Table
const string iPosition = position.bottom_right
This parameter (iPosition) sets the position of the table on the chart. The default is position.bottom_right.
Color preferences
Table borders (iBorderColor):
// Color: Borders
const color iBorderColor = color.new(color.white, 75)
This parameters (iBorderColor) sets the color of the borders everywhere within the window.
Table Background (iTableColor):
// Color: Table background
const color iTableColor = color.new(#2B2A29, 25)
This is the background color of the table. If you've got cells without custom background color, this color will be their background.
Title Cell Background (iTitleCellColor):
// Color: Title cell background
const color iTitleCellColor = color.new(#171F54, 0)
This is the background color the title cells. You can set the background of data cells and text color elsewhere.
Text (iCharColor):
// Color: Characters
const color iCharColor = color.white
This is the color of the text - titles and data - within the table window. If you change any of the background colors, you might want to change this parameter to ensure visibility.
Data Cell Background: (iDataCellColor):
// Color: Data cell background
const color iDataCellColor = color.new(#25456E, 0)
The data cells have a background color to differ from title cells. You can configure this is a different parameter (iDataColor). You might even set the same color for data as for the titles if you will.
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Mathematical Background:
Monthly and Weekly Extremums:
The indicator calculates the High (H) and Low (L) of the previous month and week, ensuring accurate representation of these key levels.
Standard Monthly Pivot Point:
The standard pivot point is determined based on the previous month's data using the formula:
PivotPoint = (PrevMonthHigh + PrevMonthLow + Close ) / 3
Monthly Pivot Points (R1, R2, R3, S1, S2, S3):
Additional pivot points are calculated for Resistances (R) and Supports (S) using the monthly data:
R1 = 2 * PivotPoint - PrevMonthLow
S1 = 2 * PivotPoint - PrevMonthHigh
R2 = PivotPoint + (PrevMonthHigh - PrevMonthLow)
S2 = PivotPoint - (PrevMonthHigh - PrevMonthLow)
R3 = PrevMonthHigh + 2 * (PivotPoint - PrevMonthLow)
S3 = PrevMonthLow - 2 * (PrevMonthHigh - PivotPoint)
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Code Explanation and Interpretation:
The table displayed beneath the chart provides the following information:
Monthly Extremums:
(H) High of the previous month
(L) Low of the previous month
// Function to get the high and low of the previous month
getPrevMonthHighLow() =>
var float prevMonthHigh = na
var float prevMonthLow = na
monthChanged = month(time) != month(time )
if (monthChanged)
prevMonthHigh := high
prevMonthLow := low
Weekly Extremums:
(H) High of the previous week
(L) Low of the previous week
// Function to get the high and low of the previous week
getPrevWeekHighLow() =>
var float prevWeekHigh = na
var float prevWeekLow = na
weekChanged = weekofyear(time) != weekofyear(time )
if (weekChanged)
prevWeekHigh := high
prevWeekLow := low
Monthly Pivots:
Pivot: Standard pivot point based on the previous month's data
// Function to calculate the standard pivot point based on the previous month's data
getStandardPivotPoint() =>
= getPrevMonthHighLow()
pivotPoint = (prevMonthHigh + prevMonthLow + close ) / 3
Resistances:
R3, R2, R1: Monthly resistance levels
// Function to calculate additional pivot points based on the monthly data
getMonthlyPivotPoints() =>
= getPrevMonthHighLow()
pivotPoint = (prevMonthHigh + prevMonthLow + close ) / 3
r1 = (2 * pivotPoint) - prevMonthLow
s1 = (2 * pivotPoint) - prevMonthHigh
r2 = pivotPoint + (prevMonthHigh - prevMonthLow)
s2 = pivotPoint - (prevMonthHigh - prevMonthLow)
r3 = prevMonthHigh + 2 * (pivotPoint - prevMonthLow)
s3 = prevMonthLow - 2 * (prevMonthHigh - pivotPoint)
Initializing and Populating the Table:
The myTable variable initializes the table with a blue background, and subsequent table.cell functions populate the table with headers and data.
// Initialize the table with adjusted bgcolor
var myTable = table.new(position = iPosition, columns = 5, rows = 10, bgcolor = color.new(color.blue, 90), border_width = 1, border_color = color.new(color.blue, 70))
Dynamic Data Population:
Data is dynamically populated in the table using the calculated values for Monthly Extremums, Weekly Extremums, Monthly Pivot Points, Resistances, and Supports.
// Add rows dynamically with data
= getPrevMonthHighLow()
= getPrevWeekHighLow()
= getMonthlyPivotPoints()
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Conclusion:
The Adaptive MFT Extremum Pivots indicator offers traders a detailed and clear representation of critical market levels, empowering them to make informed decisions. However, users should carefully analyze the market and consider their individual risk tolerance before making any trading decisions. The indicator's disclaimer emphasizes that it is not investment advice, and the author and script provider are not responsible for any financial losses incurred.
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Disclaimer:
This indicator is not investment advice. Trading decisions should be made based on a careful analysis of the market and individual risk tolerance. The author and script provider are not responsible for any financial losses incurred.
Kind regards,
Ely
Captain Backtest Model [TFO]Created by @imjesstwoone and @mickey1984, this trade model attempts to capture the expansion from the 10:00-14:00 EST 4h candle using just 3 simple steps. All of the information presented in this description has been outlined by its creators, all I did was translate it to Pine Script. All core settings of the trade model may be edited so that users can test several variations, however this description will cover its default, intended behavior using NQ 5m as an example.
Step 1 is to identify our Price Range. In this case, we are concerned with the highest high and the lowest low created from 6:00-10:00 EST.
Step 2 is to wait for either the high or low of said range to be taken out. Whichever side gets taken first determines the long/short bias for the remainder of the Trade Window (i.e. if price takes the range high, bias is long, and vice versa). Bias must be determined by 11:15 EST, otherwise no trades will be taken. This filter is intended to weed out "choppy" trading days.
Step 3 is to wait for a retracement and enter with a close through the previous candle's high (if long biased) or low (if short biased). There are a couple toggleable criteria that we use to define a retracement; one is checking for opposite close candles that indicate a pullback; another is checking if price took the previous candle's low (if long biased) or high (if short biased).
This trade model was initially tested for index futures, particularly ES and NQ, using a 5m chart, however this indicator allows us to backtest any symbol on any timeframe. Creators @imjesstwoone and @mickey1984 specified a 5 point stop loss on ES and a 25 point stop loss on NQ with their testing.
I've personally found some success in backtesting NQ 5m using a 25 point stop loss and 75 point profit target (3:1 R). Enabling the Use Fixed R:R parameter will ensure that these stops and targets are utilized, otherwise it will enter and hold the position until the close of the Trade Window.
Dip & Rip Patterns - The Quant Science🇺🇸
GENERAL OVERVIEW
This indicator detects Dip and Rip patterns by quickly highlighting them on the chart.
These patterns have become popular during the pandemic period mainly in the stock, ETF and cryptocurrency markets on which traders use two interesting strategies:
Buy The Dip
Sell The Rip
Before going into the merits of this technical indicator, let's understand what these two patterns mean and what they identify precisely.
Rip (Rise In Price) : wants to identify a market condition in which the price rises rapidly, for example from $100 to $110 in a few minutes or hours.
Dip (Drop In Price) : wants to identify a market condition in which the price drops rapidly, for example from $100 to $90 in a few minutes or hours.
HOW TO USE
For a better user experience, we recommend choosing a neutral colour for the candles while analysing with this indicator. You can quickly change the colour in Chart Settings > Symbol > Candles .
Depending on the configuration set by the user, the indicator will show Dip (Dip In Price) patterns in red and Rip (Rise In Price) patterns in green.
When the pattern forms, a circle will be displayed and a vertical line will be coloured on the chart along with the body of the candle. The user will then be able to quickly and easily track the configured market conditions.
In this example, we decided to use a 4H timeframe on the BTC/USDT pair (Binance).
Set in the user interface:
Period: 20
Dip (%): -25
Rip (%): 20
Price falls by 25% or more in 80 hours (Dip Pattern).
Price rise by 25% or more in 80 hours (Rip Pattern).
The user can easily configure the parameters via the user interface in the Inputs section (A) and change the indicator design in the Properties section (B).
🇮🇹
PANORAMICA GENERALE
Questo indicatore rileva i Dip e Rip patterns evidenziandoli velocemente sul grafico.
Questi patterns sono diventati famosi durante il periodo pandemico principalmente nel mercato delle azioni, ETF e Criptovalute su cui i trader utilizzano due interessanti strategie:
Buy The Dip
Sell The Rip
Prima di entrare nel merito di questo indicatore tecnico, comprendiamo il significato di questi due pattern e cosa identificano precisamente.
Rip (Rise In Price) : vuole identificare una condizione di mercato in cui il prezzo sale rapidamente, per esempio passando da 100$ a 110$ in pochi minuti o poche ore.
Dip (Drop In Price) : vuole identificare una condizione di mercato in cui il prezzo cala rapidamente, per esempio passando da 100$ a 90$ in pochi minuti o poche ore.
UTILIZZO
Per una migliore esperienza utente consigliamo di scegliere un colore neutro per le candele mentre si analizza con questo indicatore. Puoi cambiare velocemente il colore in Chart Settings > Symbol > Candles .
In base alla configurazione impostata dall'utente l'indicatore mostrerà in rosso i pattern Dip (Dip In Price) e in verde i pattern Rip (Rise In Price).
Quando il pattern si forma verrà visualizzato un cerchio e una linea verticale sul grafico che sarà colorata insieme al corpo della candela. L'utente quindi potrà tracciare facilmente e velocemente le condizioni di mercato configurate.
In questo esempio abbiamo deciso di utilizzare un timeframe 4H con l'obbiettivo di ricercare i patterns sul pair BTC/USDT (Binance).
Impostiamo nell'interfaccia utente:
Period: 20
Dip (%): -25
Rip (%): 20
Il prezzo diminuisce del 25% o più in 80 ore (Dip Pattern).
Il prezzo aumenta del 25% o più in 80 ore (Rip Pattern).
L' utente può configurare facilmente i parametri attraverso l'interfaccia utente nella sezione Inputs (A) e modificare il design dell'indicatore nella sezione Properties (B).
lib_profileLibrary "lib_profile"
a library with functions to calculate a volume profile for either a set of candles within the current chart, or a single candle from its lower timeframe security data. All you need is to feed the
method delete(this)
deletes this bucket's plot from the chart
Namespace types: Bucket
Parameters:
this (Bucket)
method delete(this)
Namespace types: Profile
Parameters:
this (Profile)
method delete(this)
Namespace types: Bucket
Parameters:
this (Bucket )
method delete(this)
Namespace types: Profile
Parameters:
this (Profile )
method update(this, top, bottom, value, fraction)
updates this bucket's data
Namespace types: Bucket
Parameters:
this (Bucket)
top (float)
bottom (float)
value (float)
fraction (float)
method update(this, tops, bottoms, values)
update this Profile's data (recalculates the whole profile and applies the result to this object) TODO optimisation to calculate this incremental to improve performance in realtime on high resolution
Namespace types: Profile
Parameters:
this (Profile)
tops (float ) : array of range top/high values (either from ltf or chart candles using history() function
bottoms (float ) : array of range bottom/low values (either from ltf or chart candles using history() function
values (float ) : array of range volume/1 values (either from ltf or chart candles using history() function (1s can be used for analysing candles in bucket/price range over time)
method tostring(this)
allows debug print of a bucket
Namespace types: Bucket
Parameters:
this (Bucket)
method draw(this, start_t, start_i, end_t, end_i, args, line_color)
allows drawing a line in a Profile, representing this bucket and it's value + it's value's fraction of the Profile total value
Namespace types: Bucket
Parameters:
this (Bucket)
start_t (int) : the time x coordinate of the line's left end (depends on the Profile box)
start_i (int) : the bar_index x coordinate of the line's left end (depends on the Profile box)
end_t (int) : the time x coordinate of the line's right end (depends on the Profile box)
end_i (int) : the bar_index x coordinate of the line's right end (depends on the Profile box)
args (LineArgs type from robbatt/lib_plot_objects/24) : the default arguments for the line style
line_color (color) : the color override for POC/VAH/VAL lines
method draw(this, forced_width)
draw all components of this Profile (Box, Background, Bucket lines, POC/VAH/VAL overlay levels and labels)
Namespace types: Profile
Parameters:
this (Profile)
forced_width (int) : allows to force width of the Profile Box, overrides the ProfileArgs.default_size and ProfileArgs.extend arguments (default: na)
method init(this)
Namespace types: ProfileArgs
Parameters:
this (ProfileArgs)
method init(this)
Namespace types: Profile
Parameters:
this (Profile)
profile(tops, bottoms, values, resolution, vah_pc, val_pc, bucket_buffer)
split a chart/parent bar into 'resolution' sections, figure out in which section the most volume/time was spent, by analysing a given set of (intra)bars' top/bottom/volume values. Then return price center of the bin with the highest volume, essentially marking the point of control / highest volume (poc) in the chart/parent bar.
Parameters:
tops (float ) : array of range top/high values (either from ltf or chart candles using history() function
bottoms (float ) : array of range bottom/low values (either from ltf or chart candles using history() function
values (float ) : array of range volume/1 values (either from ltf or chart candles using history() function (1s can be used for analysing candles in bucket/price range over time)
resolution (int) : amount of buckets/price ranges to sort the candle data into (analyse how much volume / time was spent in a certain bucket/price range) (default: 25)
vah_pc (float) : a threshold percentage (of values' total) for the top end of the value area (default: 80)
val_pc (float) : a threshold percentage (of values' total) for the bottom end of the value area (default: 20)
bucket_buffer (Bucket ) : optional buffer of empty Buckets to fill, if omitted a new one is created and returned. The buffer length must match the resolution
Returns: poc (price level), vah (price level), val (price level), poc_index (idx in buckets), vah_index (idx in buckets), val_index (idx in buckets), buckets (filled buffer or new)
create_profile(start_idx, tops, bottoms, values, resolution, vah_pc, val_pc, args)
split a chart/parent bar into 'resolution' sections, figure out in which section the most volume/time was spent, by analysing a given set of (intra)bars' top/bottom/volume values. Then return price center of the bin with the highest volume, essentially marking the point of control / highest volume (poc) in the chart/parent bar.
Parameters:
start_idx (int) : the bar_index at which the Profile should start drawing
tops (float ) : array of range top/high values (either from ltf or chart candles using history() function
bottoms (float ) : array of range bottom/low values (either from ltf or chart candles using history() function
values (float ) : array of range volume/1 values (either from ltf or chart candles using history() function (1s can be used for analysing candles in bucket/price range over time)
resolution (int) : amount of buckets/price ranges to sort the candle data into (analyse how much volume / time was spent in a certain bucket/price range) (default: 25)
vah_pc (float) : a threshold percentage (of values' total) for the top end of the value area (default: 80)
val_pc (float) : a threshold percentage (of values' total) for the bottom end of the value area (default: 20)
args (ProfileArgs)
Returns: poc (price level), vah (price level), val (price level), poc_index (idx in buckets), vah_index (idx in buckets), val_index (idx in buckets), buckets (filled buffer or new)
history(src, len, offset)
allows fetching an array of values from the history series with offset from current candle
Parameters:
src (int)
len (int)
offset (int)
history(src, len, offset)
allows fetching an array of values from the history series with offset from current candle
Parameters:
src (float)
len (int)
offset (int)
history(src, len, offset)
allows fetching an array of values from the history series with offset from current candle
Parameters:
src (bool)
len (int)
offset (int)
history(src, len, offset)
allows fetching an array of values from the history series with offset from current candle
Parameters:
src (string)
len (int)
offset (int)
Bucket
Fields:
idx (series int) : the index of this Bucket within the Profile starting with 0 for the lowest Bucket at the bottom of the Profile
value (series float) : the value of this Bucket, can be volume or time, for using time pass and array of 1s to the update function
top (series float) : the top of this Bucket's price range (for calculation)
btm (series float) : the bottom of this Bucket's price range (for calculation)
center (series float) : the center of this Bucket's price range (for plotting)
fraction (series float) : the fraction this Bucket's value is compared to the total of the Profile
plot_bucket_line (Line type from robbatt/lib_plot_objects/24) : the line that resembles this bucket and it's valeu in the Profile
ProfileArgs
Fields:
show_poc (series bool) : whether to plot a POC line across the Profile Box (default: true)
show_profile (series bool) : whether to plot a line for each Bucket in the Profile Box, indicating the value per Bucket (Price range), e.g. volume that occured in a certain time and price range (default: false)
show_va (series bool) : whether to plot a VAH/VAL line across the Profile Box (default: false)
show_va_fill (series bool) : whether to fill the 'value' area between VAH/VAL line (default: false)
show_background (series bool) : whether to fill the Profile Box with a background color (default: false)
show_labels (series bool) : whether to add labels to the right end of the POC/VAH/VAL line (default: false)
show_price_levels (series bool) : whether add price values to the labels to the right end of the POC/VAH/VAL line (default: false)
extend (series bool) : whether extend the Profile Box to the current candle (default: false)
default_size (series int) : the default min. width of the Profile Box (default: 30)
args_poc_line (LineArgs type from robbatt/lib_plot_objects/24) : arguments for the poc line plot
args_va_line (LineArgs type from robbatt/lib_plot_objects/24) : arguments for the va line plot
args_poc_label (LabelArgs type from robbatt/lib_plot_objects/24) : arguments for the poc label plot
args_va_label (LabelArgs type from robbatt/lib_plot_objects/24) : arguments for the va label plot
args_profile_line (LineArgs type from robbatt/lib_plot_objects/24) : arguments for the Bucket line plots
args_profile_bg (BoxArgs type from robbatt/lib_plot_objects/24)
va_fill_color (series color) : color for the va area fill plot
Profile
Fields:
start (series int) : left x coordinate for the Profile Box
end (series int) : right x coordinate for the Profile Box
resolution (series int) : the amount of buckets/price ranges the Profile will dissect the data into
vah_threshold_pc (series float) : the percentage of the total data value to mark the upper threshold for the main value area
val_threshold_pc (series float) : the percentage of the total data value to mark the lower threshold for the main value area
args (ProfileArgs) : the style arguments for the Profile Box
h (series float) : the highest price of the data
l (series float) : the lowest price of the data
total (series float) : the total data value (e.g. volume of all candles, or just one each to analyse candle distribution over time)
buckets (Bucket ) : the Bucket objects holding the data for each price range bucket
poc_bucket_index (series int) : the Bucket index in buckets, that holds the poc Bucket
vah_bucket_index (series int) : the Bucket index in buckets, that holds the vah Bucket
val_bucket_index (series int) : the Bucket index in buckets, that holds the val Bucket
poc (series float) : the according price level marking the Point Of Control
vah (series float) : the according price level marking the Value Area High
val (series float) : the according price level marking the Value Area Low
plot_poc (Line type from robbatt/lib_plot_objects/24)
plot_vah (Line type from robbatt/lib_plot_objects/24)
plot_val (Line type from robbatt/lib_plot_objects/24)
plot_poc_label (Label type from robbatt/lib_plot_objects/24)
plot_vah_label (Label type from robbatt/lib_plot_objects/24)
plot_val_label (Label type from robbatt/lib_plot_objects/24)
plot_va_fill (LineFill type from robbatt/lib_plot_objects/24)
plot_profile_bg (Box type from robbatt/lib_plot_objects/24)
MACDVMACDV = Moving Average Convergence Divergence Volume
The MACDV indicator uses stochastic accumulation / distribution volume inflow and outflow formulas to visualize it in a standard MACD type of appearance.
To be able to merge these formulas I had to normalize the math.
Accumulation / distribution volume is a unique scale.
Stochastic is a 0-100 scale.
MACD is a unique scale.
The normalized output scale range for MACDV is -100 to 100.
100 = overbought
-100 = oversold
Everything in between is either bullish or bearish.
Rising = bullish
Falling = bearish
crossover = bullish
crossunder = bearish
convergence = direction change
divergence = momentum
The default input settings are:
7 = K length, Stochastic accumulation / distribution length
3 = D smoothing, smoothing stochastic accumulation / distribution volume weighted moving average
6 = MACDV fast, MACDV fast length line
color = blue
13 = MACDV slow, MACDV slow length line
color = white
4 = MACDV signal, MACDV histogram length
color rising above 0 = bright green
color falling above 0 = dark green
color falling below 0 = bright red
color rising below 0 = dark red
2 = Stretch, Output multiplier for MACDV visual expansion
Horizontal lines:
100
75
50
25
0
-25
-50
-75
-100
Average Range LinesThis Average Range Lines indicator identifies high and low price levels based on a chosen time period (day, week, month, etc.) and then uses a simple moving average over the length of the lookback period chosen to project support and resistance levels, otherwise referred to as average range. The calculation of these levels are slightly different than Average True Range and I have found this to be more accurate for intraday price bounces.
Lines are plotted and labeled on the chart based on the following methodology:
+3.0: 3x the average high over the chosen timeframe and lookback period.
+2.5: 2.5x the average high over the chosen timeframe and lookback period.
+2.0: 2x the average high over the chosen timeframe and lookback period.
+1.5: 1.5x the average high over the chosen timeframe and lookback period.
+1.0: The average high over the chosen timeframe and lookback period.
+0.5: One-half the average high over the chosen timeframe and lookback period.
Open: Opening price for the chosen time period.
-0.5: One-half the average low over the chosen timeframe and lookback period.
-1.0: The average low over the chosen timeframe and lookback period.
-1.5: 1.5x the average low over the chosen timeframe and lookback period.
-2.0: 2x the average low over the chosen timeframe and lookback period.
-2.5: 2.5x the average low over the chosen timeframe and lookback period.
-3.0: 3x the average low over the chosen timeframe and lookback period.
Look for price to find support or resistance at these levels for either entries or to take profit. When price crosses the +/- 2.0 or beyond, the likelihood of a reversal is very high, especially if set to weekly and monthly levels.
This indicator can be used/viewed on any timeframe. For intraday trading and viewing on a 15 minute or less timeframe, I recommend using the 4 hour, 1 day, and/or 1 week levels. For swing trading and viewing on a 30 minute or higher timeframe, I recommend using the 1 week, 1 month, or longer timeframes. I don’t believe this would be useful on a 1 hour or less timeframe, but let me know if the comments if you find otherwise.
Based on my testing, recommended lookback periods by timeframe include:
Timeframe: 4 hour; Lookback period: 60 (recommend viewing on a 5 minute or less timeframe)
Timeframe: 1 day; Lookback period: 10 (also check out 25 if your chart doesn’t show good support/resistance at 10 days lookback – I have found 25 to be useful on charts like SPX)
Timeframe: 1 week; Lookback period: 14
Timeframe: 1 month; Lookback period: 10
The line style and colors are all editable. You can apply a global coloring scheme in the event you want to add this indicator to your chart multiple times with different time frames like I do for the weekly and monthly.
I appreciate your comments/feedback on this indicator to improve. Also let me know if you find this useful, and what settings/ticker you find it works best with!
Also check out my profile for more indicators!
Kernel Regression ToolkitThis toolkit provides filters and extra functionality for non-repainting Nadaraya-Watson estimator implementations made by @jdehorty. For the sake of ease I have nicknamed it "kreg". Filters include a smoothing formula and zero lag formula. The purpose of this script is to help traders test, experiment and develop different regression lines. Regression lines are best used as trend lines and can be an invaluable asset for quickly locating first pullbacks and breaks of trends.
Other features include two J lines and a blend line. J lines are featured in tools like Stochastic KDJ. The formula uses the distance between K and D lines to make the J line. The blend line adds the ability to blend two lines together. This can be useful for several tasks including finding a center/median line between two lines or for blending in the characteristics of a different line. Default is set to 50 which is a 50% blend of the two lines. This can be increased and decreased to taste. This tool can be overlaid on the chart or on top of another indicator if you set the source. It can even be moved into its own window to create a unique oscillator based on whatever sources you feed it.
Below are the standard settings for the kernel estimation as documented by @jdehorty:
Lookback Window: The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars. Recommended range: 3-50
Weighting: Relative weighting of time frames. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel. Recommended range: 0.25-25
Level: Bar index on which to start regression. Controls how tightly fit the kernel estimate is to the data. Smaller values are a tighter fit. Larger values are a looser fit. Recommended range: 2-25
Lag: Lag for crossover detection. Lower values result in earlier crossovers. Recommended range: 1-2
For more information on this technique refer to to the original open source indicator by @jdehorty located here:
Fetch ATR + MA StrategyA trend following indicator that allows traders/investors to enter trades for the long term, as it is mainly tested on the daily chart. The indicator fires off buy and sell signals. The sell signals can be turned off as trader can decide to use this indicator for long term buy signals. The buy signals are indicated by the green diamonds, and the red diamonds show the points on then chart where the asset can be sold.
The indicator uses a couple indicators in order to generate the buy signals:
- ADX
- ATR
- Moving Average of ATR
- 50 SMA
- 200 SMA
The buy signal is generated at the cross overs of the 50 and 200 SMA's while the ATR is lower than then Moving Average of the ATR. The buy signal is fired when these conditions are met and if the ADX is lower than 30.
The thought process is as follows:
When the ATR is lower than its moving average, the price should be in a low volatilty environment. An ADX between 25 and 50 signals a Strong trend. Every value below 25 is an absent or weak trend. So entering a trade when the volatilty is still low but increasing, you'll be entering a trade at the start of a new uptrend. This mechanism also filters out lots of false signals of the simple cross overs.
The sell signals are fired every time the 50 SMA drops below the 200 SMA.
Average Traded MoneyAs its name indicates, this indicator shows us the average amount of money traded in a specific asset.
It is calculated by multiplying the volume by the price (calculated on hl2) on each trading day and from there calculate a moving average of 25 periods.
The indicator only shows this 25 period moving average .
What is it for?
Well, it helps us to find out if there are variations in the amount of money traded and therefore identify areas of accumulation and distribution and thus be able to anticipate changes in trend and enter together with the large funds and thus obtain benefits.
It is something very simple to calculate but strangely no one had published it in TradingView yet. I think it is very useful and shows us information that is hidden in the volatility of a simple volume indicator. The simple volume indicator only shows us the number of shares traded but not the money that has been traded, that's why my indicator can be helpful. By averaging this data, we smooth the highs and lows of money traded and we get a cleaner graphic that gives us a better interpretation of what is happening with the negotiation of the asset.
Zazzamira 50-25-25 Trend System Alerts OnlyPublishing my trading system script. It consist of several conditions to happen in order to open a trade. Work best on ES/MES 5 minute timeframe.
I like to use it with this settings:
- UTC -6 (don't tick Exchange Timezone)
and rest as default
To enter a trade, the following conditions must be met: Entry 1: the opening range (8:30AM - 9:15AM UTC-6) must be defined and the price must close above or below the opening range on the 5-minute timeframe. This entry condition defines the trade direction (above = long / below = short). Once the opening range is defined, the Trend-Based Fib Extension is applied from the range high to the range low (and vice versa). Fib levels are required for Exit conditions. Entry 2: the 8 - 27 - 67 - 97 EMAs must be defined. If the EMAs value order is 8 > 27 > 67 > 97, long-only trades are allowed. If the EMAs value order is 8 < 27 < 67 < 97, short-only trades are allowed. This entry condition filters fake breakouts of Entry 1. Entry 3: no trades are allowed after 12:59 UTC-6 (2PM EST). Entry 4: if Entry 1, Entry 2, and Entry 3 conditions are valid and the price hasn't reached the 23.6% Fib line, an entry order can be set at the range high/long with 4 contracts. To exit a trade, the following conditions must be met: Exit 1 (Stop loss): set a trailing stop based on 2.1x ATR (14) from entry. Exit 2: take 50% profits at the 23.6% Fib and leave trailing stop untouched. Exit 3: if Exit 2 triggers, take 50% (25% of total entry) off at 61.8% Fib, leaving Exit 2 trailing stop values valid. Exit 4: exit the full position at the FIB 100% value. Exit 5: all trades must be closed at 3pm UTC-6 (4PM EST). So basically Take Profit are 50%-25%-25% of position.
Code has been written by © Hiubris_Indicators who has been an amazing coder and gave me the possibility to make this script public so a really big shoutout to him.
This indicator only works for alerts, please check version without alerts to backtest or tweaks. This indicator is meant to be used to automate the system via webhooks
Kimchi Premium StrategyThis strategy is based on the Korea Premium, also known as the “Kimchi Premium,” which indicates how expensive or cheap the price of Bitcoin in Korean Won on a Bitcoin exchange in South Korea is relative to the price of Bitcoin being traded in USD or Tether. Inverse Kimchi Premium RSI was newly defined to create a strategy with Kimchi Premium. Assuming that the larger the kimchi premium, the greater the individual's purchasing power. In this case, if the Inverse Kimchi Premium RSI falls and closes the candle below the bear level, a short is triggered. Long is the opposite.
This strategy defaults to a combination of the traditional RSI and the Inverse Kimchi Premium RSI. If the user wishes to unlock the Inverse Kimchi Premium RSI combination and only use it as a traditional RSI strategy, the following settings can be used.
Use Combination of Inverse Kimchi Premium RSI: Uncheck
Resolution: Chart (4hr Candle)
Source: Close
Length of RSI: 14
Bull Level: 74
Bear Level: 25
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김치프리미엄(김프) 전략은 달러 혹은 테더로 거래되고 있는 비트코인 가격 대비 한국에 있는 비트코인 거래소의 비트코인 원화 가격이 얼마나 비싸고 싼 지를 나타내는 코리아 프리미엄, 일명 "김치 프리미엄" 지표를 기반으로 만들어졌습니다. 김치 프리미엄을 가지고 전략을 만들기위해 Inverse Kimchi Premium RSI를 새롭게 정의하였습니다. 김치 프리미엄이 커질수록 개인의 매수세가 커진다고 가정하고, 이 경우 Inverse Kimchi Premium RSI이 하락하여 Bear Level 아래에서 캔들 마감을 하면 Short을 트리거 합니다. Long은 그 반대입니다.
이 전략은 전통적인 RSI와 Inverse Kimchi Premium RSI을 조합하여 기본값을 설정하였습니다. 유저가 원한다면 Inverse Kimchi Premium RSI의 조합을 해제하고 전통적인 RSI 전략으로만 사용하려면 아래 다음의 설정값을 사용할 수 있습니다.
Use Combination of Inverse Kimchi Premium RSI: 체크 해제
Resolution: Chart (4hr Candle)
Source: Close
Length of RSI: 14
Bull Level: 74
Bear Level: 25
Dynamo
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Overview
Dynamo is built to be the Swiss-knife for price-movement & strength detection, it aims to provide a holistic view of the current price across multiple dimensions. This is achieved by combining 3 very specific indicators(RSI, Stochastic & ADX) into a single view. Each of which serve a different purpose, and collectively provide a simple, yet powerful tool to gauge the true nature of price-action.
Background
Dynamo uses 3 technical analysis tools in conjunction to provide better insights into price movement, they are briefly explained below:
Relative Strength Index(RSI)
RSI is a popular indicator that is often used to measure the velocity of price change & the intensity of directional moves. RSI computes the relative strength of the current price by comparing the security’s bullish strength versus bearish strength for a given period, i.e. by comparing average gain to average loss.
It is a range bound(0-100) variable that generates a bullish reading if average gain is higher, and a bullish reading if average loss is higher. Values over 50 are generally considered bullish & values less than 50 indicate a bearish market. Values over 70 indicate an overbought condition, and values below 30 indicate oversold condition.
Stochastic
Stochastic is an indicator that aims to measure the momentum in the market, by comparing most recent closing price of the security to its price range for a given period. It is based on the assumption that price tends to close near the recent high in an up trend, and it closes near the recent low during a down trend.
It is also range bound(0-100), values over 80 indicate overbought condition and values below 20 indicate oversold condition.
Average Directional Index(ADX)
ADX is an indicator that can quantify trend strength, it is derived from two underlying indices, known as Directional Movement Index(DMI). +DMI represents strength of the up trend, and -DMI represents strength of the down trend, and ADX is the average of the two.
ADX is non-directional or trend-neutral, which means, it does not follow the direction of the price, instead ADX will rise only when there is a strong trend, it does not matter if it’s an up trend or a down trend. Typical ranges of ADX are 25-50 for a strong trend, anything below 25 is considered as no trend or weak trend. ADX can frequently shoot upto higher values, but it generally finds exhaustion levels around the 60-75 range.
About the script
All these indicators are very powerful tools, but just like any other indicator they have their limitations. Stochastic & ADX can generate false signals in volatile markets, meaning price wouldn’t always follow through with what’s being indicated. ADX may even fail to generate a signal in less volatile markets, simply because it is based on moving averages, it tends to react slower to price changes. RSI can also lose it’s effectiveness when markets are trending strong, as it can stay in the overbought or oversold ranges for an extended period of time.
Dynamo aims to provide the trader with a much broader perspective by bringing together these contrasting indicators into a single simplified view. When Stochastic becomes less reliable in highly volatile conditions, one can cross validate their deduction by looking at RSI patterns. When RSI gets stuck in overbought or oversold range, one can refer to ADX to get better picture about the current trend. Similarly, various combinations of rules & setups can be formulated to get a more deterministic view, when working with either of these indicators.
There many possible use cases for a tool like this, and it totally depends on how you want to use it. An obvious option is to use it to trigger signals only after it has been confirmed by two or more indicators, for example, RSI & Stochastic make a great combination for cross-over or cross-under strategies. Some of the other options include trend detection, strength detection, reversals or price rejection points, possible duration of a trend, and all of these can very easily be translated into effective entry and exit points for trades.
How to use it
Dynamo is an easy-to-use tool, just add it to your chart and you’re good to start with your market analysis. Output consists of three overlapping plots, each of which tackle price movement from a slightly different angle.
Stochastic: A momentum indicator that plots the current closing price in relation to the price-range over a given period of time.
Can be used to detect the direction of the price movement, potential reversals, or duration of an up/down move.
Plotted as grey coloured histograms in the background.
Relative Strength Index(RSI): RSI is also a momentum indicator that measures the velocity with which the price changes.
Can be used to detect the speed of the price movement, RSI divergences can be a nice way to detect directional changes.
Plotted as an aqua coloured line.
Average Directional Index(ADX): ADX is an indicator that is used to measure the strength of the current trend.
Can be used to measure how strong the price movement is, both up and down, or to establish long terms trends.
Plotted as an orange coloured line.
Features
Provides a well-rounded view of the market movement by amalgamating some of the best strength indicators, helping traders make better informed decisions with minimal effort.
Simplistic plots that aim to convey clean signals, as a result, reducing clutter on the chart, and hopefully in the trader's head too.
Combines different types of indicators into a single view, which leads to an optimised use of the precious screen real-estate.
Final Note
Dynamo is designed to be minimalistic in functionality and in appearance, as it is being built to be a general purpose tool that is not only beginner friendly, but can also be highly-configurable to meet the needs of pro traders.
Thresholds & default values for the indicators are only suggestions based on industry standards, they may not be an exact match for all markets & conditions. Hence, it is advisable for the user to test & adjust these values according their securities and trading styles.
The chart highlights one of many possible setups using this tool, and it can used to create various types of setups & strategies, but it is also worth noting that the usability & the effectiveness of this tool also depends on the user’s understanding & interpretation of the underlying indicators.
Lastly, this tool is only an indicator and should only be perceived that way. It does not guarantee anything, and the user should do their own research before committing to trades based on any indicator.
Machine Learning: Lorentzian Classification█ OVERVIEW
A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel implementation of an Approximate Nearest Neighbors (ANN) algorithm.
█ BACKGROUND
In physics, Lorentzian space is perhaps best known for its role in describing the curvature of space-time in Einstein's theory of General Relativity (2). Interestingly, however, this abstract concept from theoretical physics also has tangible real-world applications in trading.
Recently, it was hypothesized that Lorentzian space was also well-suited for analyzing time-series data (4), (5). This hypothesis has been supported by several empirical studies that demonstrate that Lorentzian distance is more robust to outliers and noise than the more commonly used Euclidean distance (1), (3), (6). Furthermore, Lorentzian distance was also shown to outperform dozens of other highly regarded distance metrics, including Manhattan distance, Bhattacharyya similarity, and Cosine similarity (1), (3). Outside of Dynamic Time Warping based approaches, which are unfortunately too computationally intensive for PineScript at this time, the Lorentzian Distance metric consistently scores the highest mean accuracy over a wide variety of time series data sets (1).
Euclidean distance is commonly used as the default distance metric for NN-based search algorithms, but it may not always be the best choice when dealing with financial market data. This is because financial market data can be significantly impacted by proximity to major world events such as FOMC Meetings and Black Swan events. This event-based distortion of market data can be framed as similar to the gravitational warping caused by a massive object on the space-time continuum. For financial markets, the analogous continuum that experiences warping can be referred to as "price-time".
Below is a side-by-side comparison of how neighborhoods of similar historical points appear in three-dimensional Euclidean Space and Lorentzian Space:
This figure demonstrates how Lorentzian space can better accommodate the warping of price-time since the Lorentzian distance function compresses the Euclidean neighborhood in such a way that the new neighborhood distribution in Lorentzian space tends to cluster around each of the major feature axes in addition to the origin itself. This means that, even though some nearest neighbors will be the same regardless of the distance metric used, Lorentzian space will also allow for the consideration of historical points that would otherwise never be considered with a Euclidean distance metric.
Intuitively, the advantage inherent in the Lorentzian distance metric makes sense. For example, it is logical that the price action that occurs in the hours after Chairman Powell finishes delivering a speech would resemble at least some of the previous times when he finished delivering a speech. This may be true regardless of other factors, such as whether or not the market was overbought or oversold at the time or if the macro conditions were more bullish or bearish overall. These historical reference points are extremely valuable for predictive models, yet the Euclidean distance metric would miss these neighbors entirely, often in favor of irrelevant data points from the day before the event. By using Lorentzian distance as a metric, the ML model is instead able to consider the warping of price-time caused by the event and, ultimately, transcend the temporal bias imposed on it by the time series.
For more information on the implementation details of the Approximate Nearest Neighbors (ANN) algorithm used in this indicator, please refer to the detailed comments in the source code.
█ HOW TO USE
Below is an explanatory breakdown of the different parts of this indicator as it appears in the interface:
Below is an explanation of the different settings for this indicator:
General Settings:
Source - This has a default value of "hlc3" and is used to control the input data source.
Neighbors Count - This has a default value of 8, a minimum value of 1, a maximum value of 100, and a step of 1. It is used to control the number of neighbors to consider.
Max Bars Back - This has a default value of 2000.
Feature Count - This has a default value of 5, a minimum value of 2, and a maximum value of 5. It controls the number of features to use for ML predictions.
Color Compression - This has a default value of 1, a minimum value of 1, and a maximum value of 10. It is used to control the compression factor for adjusting the intensity of the color scale.
Show Exits - This has a default value of false. It controls whether to show the exit threshold on the chart.
Use Dynamic Exits - This has a default value of false. It is used to control whether to attempt to let profits ride by dynamically adjusting the exit threshold based on kernel regression.
Feature Engineering Settings:
Note: The Feature Engineering section is for fine-tuning the features used for ML predictions. The default values are optimized for the 4H to 12H timeframes for most charts, but they should also work reasonably well for other timeframes. By default, the model can support features that accept two parameters (Parameter A and Parameter B, respectively). Even though there are only 4 features provided by default, the same feature with different settings counts as two separate features. If the feature only accepts one parameter, then the second parameter will default to EMA-based smoothing with a default value of 1. These features represent the most effective combination I have encountered in my testing, but additional features may be added as additional options in the future.
Feature 1 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX".
Feature 2 - This has a default value of "WT" and options are: "RSI", "WT", "CCI", "ADX".
Feature 3 - This has a default value of "CCI" and options are: "RSI", "WT", "CCI", "ADX".
Feature 4 - This has a default value of "ADX" and options are: "RSI", "WT", "CCI", "ADX".
Feature 5 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX".
Filters Settings:
Use Volatility Filter - This has a default value of true. It is used to control whether to use the volatility filter.
Use Regime Filter - This has a default value of true. It is used to control whether to use the trend detection filter.
Use ADX Filter - This has a default value of false. It is used to control whether to use the ADX filter.
Regime Threshold - This has a default value of -0.1, a minimum value of -10, a maximum value of 10, and a step of 0.1. It is used to control the Regime Detection filter for detecting Trending/Ranging markets.
ADX Threshold - This has a default value of 20, a minimum value of 0, a maximum value of 100, and a step of 1. It is used to control the threshold for detecting Trending/Ranging markets.
Kernel Regression Settings:
Trade with Kernel - This has a default value of true. It is used to control whether to trade with the kernel.
Show Kernel Estimate - This has a default value of true. It is used to control whether to show the kernel estimate.
Lookback Window - This has a default value of 8 and a minimum value of 3. It is used to control the number of bars used for the estimation. Recommended range: 3-50
Relative Weighting - This has a default value of 8 and a step size of 0.25. It is used to control the relative weighting of time frames. Recommended range: 0.25-25
Start Regression at Bar - This has a default value of 25. It is used to control the bar index on which to start regression. Recommended range: 0-25
Display Settings:
Show Bar Colors - This has a default value of true. It is used to control whether to show the bar colors.
Show Bar Prediction Values - This has a default value of true. It controls whether to show the ML model's evaluation of each bar as an integer.
Use ATR Offset - This has a default value of false. It controls whether to use the ATR offset instead of the bar prediction offset.
Bar Prediction Offset - This has a default value of 0 and a minimum value of 0. It is used to control the offset of the bar predictions as a percentage from the bar high or close.
Backtesting Settings:
Show Backtest Results - This has a default value of true. It is used to control whether to display the win rate of the given configuration.
█ WORKS CITED
(1) R. Giusti and G. E. A. P. A. Batista, "An Empirical Comparison of Dissimilarity Measures for Time Series Classification," 2013 Brazilian Conference on Intelligent Systems, Oct. 2013, DOI: 10.1109/bracis.2013.22.
(2) Y. Kerimbekov, H. Ş. Bilge, and H. H. Uğurlu, "The use of Lorentzian distance metric in classification problems," Pattern Recognition Letters, vol. 84, 170–176, Dec. 2016, DOI: 10.1016/j.patrec.2016.09.006.
(3) A. Bagnall, A. Bostrom, J. Large, and J. Lines, "The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms." ResearchGate, Feb. 04, 2016.
(4) H. Ş. Bilge, Yerzhan Kerimbekov, and Hasan Hüseyin Uğurlu, "A new classification method by using Lorentzian distance metric," ResearchGate, Sep. 02, 2015.
(5) Y. Kerimbekov and H. Şakir Bilge, "Lorentzian Distance Classifier for Multiple Features," Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods, 2017, DOI: 10.5220/0006197004930501.
(6) V. Surya Prasath et al., "Effects of Distance Measure Choice on KNN Classifier Performance - A Review." .
█ ACKNOWLEDGEMENTS
@veryfid - For many invaluable insights, discussions, and advice that helped to shape this project.
@capissimo - For open sourcing his interesting ideas regarding various KNN implementations in PineScript, several of which helped inspire my original undertaking of this project.
@RikkiTavi - For many invaluable physics-related conversations and for his helping me develop a mechanism for visualizing various distance algorithms in 3D using JavaScript
@jlaurel - For invaluable literature recommendations that helped me to understand the underlying subject matter of this project.
@annutara - For help in beta-testing this indicator and for sharing many helpful ideas and insights early on in its development.
@jasontaylor7 - For helping to beta-test this indicator and for many helpful conversations that helped to shape my backtesting workflow
@meddymarkusvanhala - For helping to beta-test this indicator
@dlbnext - For incredibly detailed backtesting testing of this indicator and for sharing numerous ideas on how the user experience could be improved.
Zazzamira 50-25-25 Trend SystemPublishing my trading system script. It consist of several conditions to happen in order to open a trade. Work best on ES/MES 5 minute timeframe.
I like to use it with this settings:
- UTC -6 (don't tick Exchange Timezone)
and rest as default
To enter a trade, the following conditions must be met: Entry 1: the opening range (8:30AM - 9:15AM UTC-6) must be defined and the price must close above or below the opening range on the 5-minute timeframe. This entry condition defines the trade direction (above = long / below = short). Once the opening range is defined, the Trend-Based Fib Extension is applied from the range high to the range low (and vice versa). Fib levels are required for Exit conditions. Entry 2: the 8 - 27 - 67 - 97 EMAs must be defined. If the EMAs value order is 8 > 27 > 67 > 97, long-only trades are allowed. If the EMAs value order is 8 < 27 < 67 < 97, short-only trades are allowed. This entry condition filters fake breakouts of Entry 1. Entry 3: no trades are allowed after 12:59 UTC-6 (2PM EST). Entry 4: if Entry 1, Entry 2, and Entry 3 conditions are valid and the price hasn't reached the 23.6% Fib line, an entry order can be set at the range high/long with 4 contracts. To exit a trade, the following conditions must be met: Exit 1 (Stop loss): set a trailing stop based on 2.1x ATR (14) from entry. Exit 2: take 50% profits at the 23.6% Fib and leave trailing stop untouched. Exit 3: if Exit 2 triggers, take 50% (25% of total entry) off at 61.8% Fib, leaving Exit 2 trailing stop values valid. Exit 4: exit the full position at the FIB 100% value. Exit 5: all trades must be closed at 3pm UTC-6 (4PM EST). So basically Take Profit are 50%-25%-25% of position.
Code has been written by © Hiubris_Indicators who has been an amazing coder and gave me the possibility to make this script public so a really big shoutout to him.
Strategy Myth-Busting #5 - POKI+GTREND+ADX - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our fifth one we are automating is one of the strategies from "The Best 3 Buy And Sell Indicators on Tradingview + Confirmation Indicators ( The Golden Ones ))" from "Online Trading Signals (Scalping Channel)". No formal backtesting was done by them and resuructo messaged me asking if we could validate their claims.
Originally, we mimic verbatim the settings Online Trading Signals was using however weren't getting promising results. So before we stopped there we thought we might want to see if this could be improved on. So we adjusted the Renko Assignment modifier from ATR to Traditional and adjusted the value to be higher from 30 to 47. We also decided to try adding another signal confirmation to eliminate some of the ranged market conditions so we choose our favorite, ADX . Also, given we are using this on a higher time-frame we adjusted the G-Channel Trend detection source from close to OHLC4 to get better average price action indication and more accurate trend direction.
This strategy uses a combination of 2 open-source public indicators:
poki buy and sell Take profit and stop loss by RafaelZioni
G-Channel Trend Detection by jaggedsoft
Trading Rules
15m - 4h timeframe. We saw best results at the recommended 1 hour timeframe.
Long Entry:
When POKI triggers a buy signal
When G-Channel Trend Detection is in an upward trend (Green)
ADX Is above 25
Short Entry:
When POKI triggers a sell signal
When G-Channel Trend Detection is in an downward trend (red)
ADX Is above 25
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Double RSI + BBRSI stands for Relative Strength Index.
Bollinger Bands stands for a channel open by standard deviation values plotting upper, lower lines.
Double RSI with Bollinger bands adapted Bollinger bands to RSI not using overlay mode. It tries to filter fake signals while giving more good signals according to volatility even below overbought areas or above oversold areas. This way you can use greater values for RSI, like 25 and 100, increasing smoothness with less market noise.
We added an extra gap spacer to smooth Bollinger bands while widening the channel with a lower multiplier.
I found better results when Fast RSI crosses back into Bollinger bands channel.
You can play with the following settings:
• Source
Close is the most used
• Fast RSI length
Default to 25
• Slow RSI length
Default to 100
• RSI Smoothing
To filter out some graphic noise
• RSI Overbought, Oversold
Regular overbought, oversold lines handled by a single value. For 70/30, set it to 20 although with longer RSI something around 15 is enough.
• Bollinger Spacer
Ads thickness to the channel with lower multiplier
• Bollinger Length
Regular Bollinger length applied to slow RSI
• Bollinger Multiplier
Regular Bollinger multiplier applied to slow RSI
Disclaimer:
For study purposes only, trading without a good risk management can be regrettable, do your own research, always add confirmations, use it as is, at your own risk.
Multi-timeframe Harmonic PatternsHello friends. In recent months I have been busy with my academic research and haven't had much time to publish new scripts. To fill the gap of these months, I decided to publish the indicator Multi-timeframe Harmonic Patterns . Harmonic technical chart patterns can predict the next price trend and provide traders with clues to the price direction, which is one of the indicators widely used by professional traders.
(1) Indicator description
This indicator is built on ZigZag Multi Time Frame with Fibonacci Retracement@LonesomeTheBlue . Thanks to LonesomeTheBlue for contributing the awesome indicator
The indicator supports 6 different timeframes , and 25 different harmonic patterns
This indicator supports indicating key indicator prices: entry price, stop loss price, and two take profit prices
(2) Key parameters
timeframe resolution: The timeframe of the harmonic pattern
pivot high/low source: Calculation method of high/low pivot points
timeframe pivot period: Minimum period of high/low pivot points
delay for confirmations: Wait for N candles to confirm the chart pattern
bullish/bearish colors: Bullish/bearish pattern colors
enable harmonic patterns: Enable current harmonic patterns
show harmonic patterns: Show harmonic patterns found
show trading prices of patterns: Show key prices of harmonic patterns
(3) Supported Patterns:
Gartlay
Cypher
Bat
Deepcrab
Crab
Butterfly
Shark
0-5
AB=CD
3-Drives
Anti-Gartlay
Anti-Cypher
Anti-Bat
Anti-Crab
Anti-Butterfly
Anti-Shark
Black-Swan
White-Swan
Descending-Triangle
Ascending-Triangle
Symmetrical-Triangle
Headers&Shoulders
Inverse-Headers&Shoulders
Double-Top
Double-Bottom
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各位朋友大家好。最近几个月我忙于自己的学术研究没有过多时间更新脚本。为弥补这几个月的空缺，我决定发布该 多时间周期的谐波指标 。谐波技术图表形态在一定程度上可以预测下一个价格走势，为交易者提供价格方向的线索，是广大专业交易人员广泛使用的指标之一。
(1) 指标说明
该指标建立于 ZigZag Multi Time Frame with Fibonacci Retracement@LonesomeTheBlue ，感谢LonesomeTheBlue贡献的出色指标
该指标支持 6种不同的时间周期 ，以及 25种不同的谐波形态
该指标支持指示关键的指标价格：入场价格、止损价格、以及两种止盈价格
(2) 关键参数
timeframe resolution: 谐波形态的时间周期
pivot high/low source: 高/低枢纽点的计算方式
timeframe pivot period: 高/低枢纽点的最小周期
delay for confirmations: 等待N个蜡烛以确认图表形态
bullish/bearish colors: 看涨/看跌的形态颜色
enable harmonic patterns: 使能当前的谐波形态
show harmonic patterns: 显示被发现的谐波形态
show trading prices of patterns: 显示谐波形态的关键价格
(3) 支持形态:
Gartlay
Cypher
Bat
Deepcrab
Crab
Butterfly
Shark
0-5
AB=CD
3-Drives
Anti-Gartlay
Anti-Cypher
Anti-Bat
Anti-Crab
Anti-Butterfly
Anti-Shark
Black-Swan
White-Swan
Descending-Triangle
Ascending-Triangle
Symmetrical-Triangle
Headers&Shoulders
Inverse-Headers&Shoulders
Double-Top
Double-Bottom
Manage tradeThis indicator is intended to simulate a second entry to adjust the average price.
INPUTS:
Current price || Coins -> Current price, your first entry || Initial amount of coins
Simulate entry || Coins -> New entry, from this entry the average price will be calculated || new amount of coins
Simulate partial % || Coins -> Percentage over current price or average price || Amount of coins withdrawn
* Currency conversion
Value $ || Target price -> amount or coins, example: 25 dolar or 25 busd || Acquisition target price, returns desired coin amount, visible in table.
Table information:
simbol = current symbol
current price = First entry price
total coins = Total coins from first entry
profit or loss = self explanatory
update value = increases or decreases according to profit or loss
Partial profit = partial simulation result,
$ ⮕ ₿ = total amount of currencies in the conversion
Chef MomentumChef momentum is a simple stochastic indicator that uses the hull moving average (hma). The oscillator can be used like most oscillators available.
Default setting:
%K length: 25
%K smoothing: 100
The user can adapt the parameters to study other values.
how to use :
When the length of the stoch K crossover hline 25 , a green circle appears which indicates the potential arrival of momentum.
When the length of the stock K crossover hline 80 , a red circle appears indicating the potential end of the momentum.
CMOChande Momentum Oscillator with Overbought and Oversold value
If it is above 25 then enter the trade
and if goes below -25 then exit from the trade
Round Numbers and Quarter LevelsThis script is based on "Round Numbers Above and Below" by BitcoinJesus-Not-Roger-Ver, but unlike this script that only shows "Round Numbers" levels, my script also shows "Quarter Number" levels like 25 and 75 that are very important for those who follow the quarters theory.
Also the original script doesn't have different colors for different levels while my script has different colors and different styles for every level, this way it will be much easyer to recognize the levels at first sight.
Finally the origianl script only works with Forex while my script also works with indexes like SP500 and others.
Round Numbers are very important psychological levels in trading but also quarters levels (25 and 75) have a huge importance, so I created this script that shows all these levels with different colors and different lines style.
You can edit the color and the style of the lines as you wish and you can add all the levels you want.
In 1 hour chart 4 levels is usually enough but if you watch a daily chart then 8 levels is way better.
Features:
Personalize color to 00 round levels
Personalize color to 50 round levels
Personalize color to Quarters levels
Personalize line style to 00 round levels
Personalize line style to 50 round levels
Personalize line style to Quarters levels
Choose number of lines above and below price level (4 is default)
