Simple RSI Strategy - Rule Based Higher Timeframe Trading
HOW IT WORKS
With the default settings, the strategy buys when RSI reaches 30 and closes when RSI reaches 40 .
That’s it.
A simple, rule-based mean reversion strategy designed for higher timeframes , where market noise is lower and trading becomes easier to manage.
Core logic:
Long when RSI moves into oversold territory
Exit when RSI mean-reverts upward
Optional short trades from overbought levels
One position at a time (no pyramiding)
No filters.
No discretion.
Just clear, testable rules.
MARKETS & TIMEFRAMES
This strategy is intended for:
Indices (Nasdaq, S&P 500, DAX, etc.)
Liquid futures and CFDs
Higher timeframes: 2H, 4H and Daily
The published example is Nasdaq (NDX) on the 2-hour timeframe .
Higher timeframes are strongly recommended.
HOW TO USE IT
Apply the strategy on a higher timeframe
Adjust RSI levels per market if needed
Use TradingView alerts to avoid constant screen-watching
Focus on execution, risk control, and consistency
This strategy is meant to be a building block , not a complete trading business on its own.
For long-term consistency, it works best when combined with other uncorrelated, rule-based systems.
IMPORTANT
This is not financial advice
All results are historical and not indicative of future performance
Always forward-test and apply proper risk management
For additional notes, setups and related systems, visit my TradingView profile page .
Indicadores y estrategias
ABCD Harmonic Pattern Strategy (Bull + Bear) This script is a strategy implementation of the classic ABCD Harmonic Pattern, designed for market structure analysis, backtesting, and educational research.
The ABCD pattern is one of the foundational harmonic price patterns in technical analysis. Its Fibonacci ratio relationships were formalized and standardized within harmonic trading theory by Scott M. Carney, whose work helped define modern harmonic pattern rules.
This strategy is conceptually inspired by educational ABCD pattern logic shared by the TradingView author theEccentricTrader.
The code, structure, execution logic, filters, and risk management have been independently developed, reconstructed, and extended into a complete TradingView strategy.
What this strategy does
Detects bullish and bearish ABCD harmonic patterns based on price structure and Fibonacci ratios.
Reconstructs ABCD market structure logic for both directions instead of using a simple visual inversion.
Draws the ABCD legs, structure labels (A, B, C, D), and projection levels directly on the chart.
Generates long and short trade entries using confirmed ABCD structures.
Includes optional confluence filters, such as:
Higher-timeframe EMA trend filter
RSI strength filter
ATR volatility filter
Volume confirmation
Candle body confirmation
Minimum bounce distance from point D
Provides built-in risk management, including:
Configurable Stop Loss
Configurable Take Profit
Optional trailing stop
Designed for backtesting, parameter optimization, and analytical research.
Why this strategy is different
This script is not a simple indicator conversion nor a basic bullish/bearish mirror.
The ABCD pattern logic has been recreated at the structural level to better reflect how bullish and bearish market formations behave in real price action.
Key differences
Reconstructed bullish and bearish structures
Bullish and bearish ABCD patterns are independently defined using market structure logic, not just inverted visually.
Each direction has its own pivot relationships and validation rules to produce a more faithful representation of the ABCD pattern.
Structure-aware pattern validation
Pattern confirmation is based on price swings, structure continuity, and Fibonacci alignment, helping reduce distorted or forced patterns.
Strategy-based execution
Unlike indicator-only ABCD tools that only visualize patterns, this script uses strategy.entry and strategy.exit, enabling full backtesting and performance analysis.
Confluence-driven entries
Trade entries can require multiple confirmation layers beyond the pattern itself, helping reduce low-quality signals and overtrading.
Integrated risk management
Stop Loss, Take Profit, and optional trailing logic are applied consistently for both long and short positions.
Non-repainting design
Pattern detection and entries rely on confirmed bars (barstate.isconfirmed) and higher-timeframe data with lookahead_off, ensuring signals do not repaint historically.
Improved and controlled visualization
Pattern drawings, projections, and entry markers are managed with strict object limits to comply with TradingView performance and publishing requirements.
How to use
Add the strategy to a chart and select a symbol and timeframe.
Enable or disable filters under “Entry Filters (Confluence)”.
Configure Stop Loss, Take Profit, and trailing behavior under “TP/SL”.
Use pattern drawings and entry markers as visual and analytical confirmation, not as standalone trade signals.
Important notes
This script is provided for educational and research purposes only.
It does not provide financial or investment advice.
No profitability or performance is implied or guaranteed.
Past performance does not indicate future results.
Always test across multiple markets and timeframes and apply proper risk management.
Credits
ABCD Harmonic Pattern: Harmonic trading principles as formalized by Scott M. Carney.
Conceptual inspiration: Educational ABCD pattern logic shared by @theEccentricTrader on TradingView.
Pattern reconstruction, strategy logic, and risk management: Independent development.
Bullish Engulfing at Daily Support (Pivot Low) - R Target (v6)1. What this strategy really is (in human terms)
This strategy is not about predicting the market.
It’s about waiting for proof that buyers are stepping in at a price where they already should.
Think of it like this:
“I only buy when price falls into a known ‘floor’ and buyers visibly take control.”
That’s it.
Everything in the script enforces that idea.
2. The two ingredients (nothing else)
Ingredient #1: Daily Support (the location)
Support is an area where price previously fell and then reversed upward.
In the script:
Support is defined as the most recent confirmed daily swing low
A swing low means:
Price went down
Stopped
Then went up enough to prove that buyers defended that level
This matters because:
You’re not guessing where support might be
You’re using a level where buyers already proved themselves
“At support” doesn’t mean exact
Markets don’t bounce off perfect lines.
So the script allows a small zone (the “support tolerance”):
Example: 0.5% tolerance
If support is at 100
Anywhere between ~99.5–100.5 counts
This prevents missing good trades just because price was off by a few ticks.
Ingredient #2: Bullish Engulfing Candle (the trigger)
This is the confirmation.
A bullish engulfing candle means:
Sellers were in control
Buyers stepped in hard enough to fully overpower them
The bullish candle’s body “swallows” the previous candle
Psychologically, it says:
“Sellers tried, failed, and buyers just took control.”
That’s why this candle works only at support.
A bullish engulfing in the middle of nowhere means nothing.
3. Why daily timeframe matters
The daily chart:
Filters out noise
Reflects decisions made by institutions, not random scalpers
Produces fewer but higher-quality signals
That’s why:
The script uses daily data
You typically get very few trades per month
Most days: no trade
That “boredom” is the edge.
4. When a trade is taken (exact conditions)
A trade happens only if ALL are true:
Price drops into a recent daily support zone
A bullish engulfing candle forms on the daily chart
Risk is clearly defined (entry, stop, target)
If any one is missing → no trade
5. How risk is controlled (this is crucial)
The stop loss (where you admit you’re wrong)
The stop is placed:
Below the support level
Or below the low of the engulfing candle
With a small ATR buffer so normal noise doesn’t stop you out
Meaning:
“If price breaks below this area, buyers were wrong. I’m out.”
No hoping. No moving stops. No exceptions.
Position sizing (why this strategy survives losing streaks)
Each trade risks a fixed % of your account (default 1%).
So:
Big stop = smaller position
Small stop = larger position
This keeps every trade equal in risk, not equal in size.
That’s professional behavior.
6. The take-profit logic (why 2.8R matters)
Instead of guessing targets:
The strategy uses a multiple of risk (R)
Example:
Risk = $1
Target = $2.80
You can lose many times and still come out ahead.
This is why:
Win rate ≈ 60% is more than enough
Even 40–45% could still work if discipline is perfect
7. Why patience is the real edge (not the pattern)
The bullish engulfing is common.
Bullish engulfing at daily support is rare.
Most people fail because they:
Trade engulfings everywhere
Ignore location
Lower standards when bored
Add “just one more indicator”
Your edge is:
Saying no 95% of the time
Taking only trades that look obvious after they work
8. How to use this strategy effectively (rules to follow)
Rule 1: Only take “clean” setups
Skip trades when:
Support is messy or unclear
Price is chopping sideways
The engulfing candle is tiny
The market is news-chaotic (earnings, FOMC, etc.)
If you have to convince yourself, skip it.
Rule 2: One trade at a time
This strategy works best when:
You’re not stacked in multiple correlated trades
You treat each setup like it matters
Quality > quantity.
Rule 3: Journal screenshots, not just numbers
After each trade, save:
Daily chart screenshot
Support level marked
Entry / stop / target
After 50–100 trades, patterns jump out:
Best tolerance %
Best stop buffer
Markets that behave well vs poorly
That’s how the original trader refined it.
Rule 4: Expect boredom and drawdowns
You will have:
Weeks with zero trades
Clusters of losses
Long flat periods
That’s normal.
If you “fix” it by adding more trades:
You destroy the edge.
9. Who this strategy is perfect for
This fits you if:
You don’t want screen addiction
You prefer process over excitement
You’re okay being wrong often
You want something you can execute for years
It is not for:
Scalpers
Indicator collectors
People who need action every day
10. The mindset shift (the real lesson of that story)
The money didn’t come from bullish engulfings.
It came from:
Defining one repeatable behavior
Removing everything else
Trusting math + patience
Doing nothing most of the time
If you want, next we can:
Walk through real example trades bar-by-bar
Optimize settings for a specific market you trade
Add filters that increase quality without adding complexity
MDZ Strategy v4.2 - Multi-factor trend strategyWhat This Strategy Does
MDZ (Momentum Divergence Zones) v4.2 is a trend-following strategy that enters long positions when multiple momentum and trend indicators align. It's designed for swing trading on higher timeframes (2H-4H) and uses ATR-based position management.
The strategy waits for strong trend confirmation before entry, requiring agreement across five different filters. This reduces trade frequency but aims to improve signal quality.
Entry Logic
A long entry triggers when ALL of the following conditions are true:
1. EMA Stack (Trend Structure)
Price > EMA 20 > EMA 50 > EMA 200
This "stacked" alignment indicates a strong established uptrend
2. RSI Filter (Momentum Window)
RSI between 45-75 (default)
Confirms momentum without entering overbought territory
3. ADX Filter (Trend Strength)
ADX > 20 (default)
Ensures the trend has sufficient strength, not a ranging market
4. MACD Confirmation
MACD line above signal line
Histogram increasing (momentum accelerating)
5. Directional Movement
+DI > -DI
Confirms bullish directional pressure
Exit Logic
Positions are managed with ATR-based levels:
ParameterDefaultDescriptionStop Loss2.5 × ATRBelow entry priceTake Profit6.0 × ATRAbove entry priceTrailing Stop2.0 × ATROptional, activates after entry
The default configuration produces a 1:2.4 risk-reward ratio.
Presets
The strategy includes optimized presets based on historical testing:
PresetTimeframeNotes1H Standard1 HourMore frequent signals2H Low DD2 HourConservative settings3H Optimized3 HourBalanced approach4H Swing4 HourWider stops for swing tradesCustomAnyFull manual control
Select "Custom" to adjust all parameters manually.
Inputs Explained
EMAs
Fast EMA (20): Short-term trend
Slow EMA (50): Medium-term trend
Trend EMA (200): Long-term trend filter
RSI
Length: Lookback period (default 14)
Min/Max: Entry window to avoid extremes
ADX
Min ADX: Minimum trend strength threshold
Risk
Stop Loss ATR: Multiplier for stop distance
Take Profit ATR: Multiplier for target distance
Trail ATR: Trailing stop distance (if enabled)
Session (Optional)
Filter entries by time of day
Recommended OFF for 3H+ timeframes
What's Displayed
Info Panel (Top Right)
Current preset
Trend status (Strong/Wait)
ADX, RSI, MACD readings
Position status
Risk-reward ratio
Stats Panel (Top Left)
Net P&L %
Total trades
Win rate
Profit factor
Maximum drawdown
Chart
EMA lines (20 blue, 50 orange, 200 purple)
Green background during strong uptrend
Triangle markers on entry signals
Important Notes
⚠️ This is a long-only strategy. It does not take short positions.
⚠️ Historical results do not guarantee future performance. Backtests show what would have happened in the past under specific conditions. Markets change, and any strategy can experience drawdowns or extended losing periods.
⚠️ Risk management is your responsibility. The default settings risk 100% of equity per trade for backtesting purposes. In live trading, appropriate position sizing based on your risk tolerance is essential.
⚠️ Slippage and commissions matter. The backtest includes 0.02% commission and 1 tick slippage, but actual execution costs vary by broker and market conditions.
Best Practices
Test on your specific market — Results vary significantly across different instruments
Use appropriate position sizing — Never risk more than you can afford to lose
Combine with your own analysis — No indicator replaces understanding market context
Paper trade first — Validate the strategy matches your trading style before risking capital
Alerts
Two alerts are available:
MDZ Long Entry: Fires when all entry conditions are met
Uptrend Started: Fires when EMA stack first aligns bullish
Methodology
This strategy is based on the principle that trend continuation has better odds than reversal when multiple timeframe momentum indicators agree. By requiring five independent confirmations, it filters out weak setups at the cost of fewer total signals.
The ATR-based exits adapt to current volatility rather than using fixed pip/point targets, which helps the strategy adjust to different market conditions.
Questions? Leave a comment below.
Multi KI Agenten Strategie (Final V2)What's included in the Pine Script (Technical Analysis)
These features are mathematically implemented in the script and function as "agent logic":
• Trend Following: Integrated via EMAs (50, 100, 200).
• Volume Analysis: An agent checks for institutional volume spikes.
• Supply & Demand: Zones are calculated based on price extremes.
• RSI & Fibonacci: Both are built in as decision criteria for the agents.
• Controlling AI: The "veto logic" in the code acts as a controlling instance, blocking signals if the risk is too high or divergences exist.
• Alerts: The "LONG" and "SHORT" alerts are only triggered after approval by the controlling mechanism.
BTC Scalping 3m | Supertrend + MACD Squeeze (NY) [v6 FINAL]BTC 3-Minute Scalping Strategy
Supertrend Bias + MACD Squeeze (New York Session)
This is a fully mechanical BTC scalping strategy designed to capture short momentum bursts that occur when volatility expands in the direction of the higher-timeframe trend.
The strategy combines trend confirmation, volatility compression/expansion, and strict session filtering to reduce noise and improve consistency.
How It Works
Trend Bias
Uses a 15-minute Supertrend to define market direction.
Trades are taken only in the direction of the higher-timeframe trend.
Counter-trend signals are ignored.
Timing & Entry
Executes on the 3-minute chart.
Waits for volatility compression using a LazyBear-style MACD Squeeze.
Enters only when the squeeze releases and momentum turns positive.
Entry occurs on candle close above the execution-timeframe Supertrend.
Session Filter
Trades only during the New York session (13:00–21:00 UTC).
This avoids low-liquidity periods and reduces false breakouts.
Risk & Exits
Dynamic stop-loss placed at the execution-timeframe Supertrend.
Risk is calculated using the actual filled entry price for accurate R-based exits.
Primary profit target is 0.5R, optimized for scalping.
Positions are exited immediately if:
Price closes against Supertrend
Supertrend flips direction
Momentum (MACD histogram) turns negative
Trades are typically short-lived (1–3 candles), keeping exposure minimal.
Key Characteristics
Non-repainting logic
Fully rule-based (no discretion)
High win-rate, low-RR scalping profile
Designed for BTC futures/perpetuals
Optimized for New York session volatility
Usage Notes
Run on BTC 3-minute charts
Best results during active NY hours
Performance will vary by exchange, fees, and slippage
This strategy is intended for education and testing, not financial advice
Summary
This strategy focuses on trading volatility expansion aligned with trend, using Supertrend for structure and MACD Squeeze for timing. By restricting trades to high-liquidity hours and enforcing strict exits, it aims for consistent, repeatable scalps rather than large directional bets.
lww Crossover Strategy Strategy Description
This strategy is based on the confluence of VWAP, MVWAP, and EMA crossover structure, designed to identify short-term trend continuation opportunities in both long and short directions.
A trade signal is generated only when the fast EMA, slow EMA, and smoothed VWAP are all positioned on the same side of the MVWAP, indicating directional alignment and structural confirmation. Entries occur only at the moment the condition first becomes true, which helps reduce overtrading during ranging or choppy market conditions.
The strategy enforces a one-trade-at-a-time rule, ensuring that no new positions are opened while an existing trade is active.
Risk management is handled through predefined take-profit and stop-loss levels, which are automatically placed upon entry to maintain clear and consistent risk control. An optional setting allows positions to be closed early if an opposite signal appears.
This strategy is suitable for short-term and intraday trading, emphasizing disciplined execution, structural confirmation, and controlled risk exposure.
proof quant model v1team, this is the model for our class. It is public but yeah its not like there will be specific ip or stuff like that. Get to work
MACD Bounce Strategy for CryptohopperSell and Buy alerts based on MACD crossover values for automated triggers in Cryptohopper
ronismc333 דור בן שימול: //+------------------------------------------------------------------+
//| SMC GBP PRO EA – FTMO Ready 30M עם חצים |
//+------------------------------------------------------------------+
#property strict
input double RiskPercent = 1.0;
input int RSIPeriod = 14;
input int StopLossPoints = 200;
input int TakeProfitPoints = 400;
input int MagicNumber = 202630;
input bool EnableAlerts = true;
int rsiHandle;
//+------------------------------------------------------------------+
int OnInit()
{
rsiHandle = iRSI(_Symbol, PERIOD_M30, RSIPeriod, PRICE_CLOSE);
Comment("SMC GBP PRO EA Status: CONNECTED Account: ", AccountNumber());
return(INIT_SUCCEEDED);
}
//+------------------------------------------------------------------+
void OnTick()
{
if(PositionsTotal() > 0)
{
UpdateStatus();
return;
}
double rsi ;
CopyBuffer(rsiHandle,0,0,1,rsi);
double high1 = iHigh(_Symbol, PERIOD_M30,1);
double low1 = iLow(_Symbol, PERIOD_M30,1);
double close1= iClose(_Symbol, PERIOD_M30,1);
double high2 = iHigh(_Symbol, PERIOD_M30,2);
double low2 = iLow(_Symbol, PERIOD_M30,2);
//==== HTF TREND (1H EMA50) ====
double emaHTF = iMA(_Symbol, PERIOD_H1, 50, 0, MODE_EMA, PRICE_CLOSE, 0);
double closeHTF = iClose(_Symbol, PERIOD_H1, 0);
bool htfBull = closeHTF > emaHTF;
bool htfBear = closeHTF < emaHTF;
//==== LIQUIDITY SWEEP ====
bool sweepBuy = low1 < low2 && close1 > low2;
bool sweepSell = high1 > high2 && close1 < high2;
//==== BOS ====
bool bosBuy = sweepBuy && close1 > high2;
bool bosSell = sweepSell && close1 < low2;
//==== BUY/SELL CONDITIONS ====
bool buy = bosBuy && rsi > 50 && htfBull;
bool sell = bosSell && rsi < 50 && htfBear;
double lot = CalculateLot(StopLossPoints, RiskPercent);
if(buy)
{
OpenTrade(ORDER_TYPE_BUY, lot, StopLossPoints, TakeProfitPoints, "BUY GBP");
DrawArrow("BUY", 0, low1 - 10*_Point, clrLime, "BUY GBP");
}
if(sell)
{
OpenTrade(ORDER_TYPE_SELL, lot, StopLossPoints, TakeProfitPoints, "SELL GBP");
DrawArrow("SELL", 0, high1 + 10*_Point, clrRed, "SELL GBP");
}
UpdateStatus();
}
//+------------------------------------------------------------------+
double CalculateLot(int slPoints, double riskPercent)
{
double riskMoney = AccountBalance() * riskPercent / 100.0;
double lot = riskMoney / (slPoints * _Point * 10);
lot = MathMax(lot,0.01);
return(NormalizeDouble(lot,2));
}
//+------------------------------------------------------------------+
void OpenTrade(ENUM_ORDER_TYPE type,double lot,int sl,int tp,string comment)
{
double price = (type==ORDER_TYPE_BUY) ? SymbolInfoDouble(_Symbol,SYMBOL_ASK)
: SymbolInfoDouble(_Symbol,SYMBOL_BID);
double slPrice = (type==ORDER_TYPE_BUY) ? price - sl*_Point
: price + sl*_Point;
double tpPrice = (type==ORDER_TYPE_BUY) ? price + tp*_Point
: price - tp*_Point;
MqlTradeRequest req;
MqlTradeResult res;
ZeroMemory(req);
req.action = TRADE_ACTION_DEAL;
req.symbol = _Symbol;
req.volume = lot;
req.type = type;
req.price = price;
req.sl = slPrice;
req.tp = tpPrice;
req.deviation= 20;
req.magic = MagicNumber;
req.comment = comment;
if(!OrderSend(req,res))
{
Print("Trade failed: ",res.retcode);
if(EnableAlerts) Alert("Trade failed: ",res.retcode);
}
else
{
if(EnableAlerts) Alert(comment," opened at ",price);
Print(comment," opened at ",price);
}
}
//+------------------------------------------------------------------+
void UpdateStatus()
{
string text = "SMC GBP PRO EA Status: CONNECTED Account: "+IntegerToString(AccountNumber());
if(PositionsTotal()>0) text += " Trade Open!";
Comment(text);
}
//+------------------------------------------------------------------+
void DrawArrow(string name, int shift, double price, color clr, string text)
{
string objName = name + IntegerToString(TimeCurrent());
if(ObjectFind(0,objName) >=0) ObjectDelete(0,objName);
ObjectCreate(0,objName,OBJ_ARROW,0,Time ,price);
ObjectSetInteger(0,objName,OBJPROP_COLOR,clr);
ObjectSetInteger(0,objName,OBJPROP_WIDTH,2);
ObjectSetInteger(0,objName,OBJPROP_ARROWCODE,233); // חץ
ObjectSetString(0,objName,OBJPROP_TEXT,text);
}
------------------------------------------------------------------+
//| SMC GBP PRO EA – FTMO 30M + TP/SL + Trailing Stop |
//+------------------------------------------------------------------+
#property strict
input double RiskPercent = 1.0;
input int RSIPeriod = 14;
input int StopLossPoints = 200;
input int TakeProfitPoints = 400;
input int MagicNumber = 202630;
input bool EnableAlerts = true;
int rsiHandle;
//+------------------------------------------------------------------+
int OnInit()
{
rsiHandle = iRSI(_Symbol, PERIOD_M30, RSIPeriod, PRICE_CLOSE);
Comment("SMC GBP PRO EA Status: CONNECTED Account: ", AccountNumber());
return(INIT_SUCCEEDED);
}
//+------------------------------------------------------------------+
void OnTick()
{
//
UpdateStatus();
// Trailing Stop
ManageTrailing();
if(PositionsTotal() > 0) return;
double rsi ;
CopyBuffer(rsiHandle,0,0,1,rsi);
double high1 = iHigh(_Symbol, PERIOD_M30,1);
double low1 = iLow(_Symbol, PERIOD_M30,1);
double close1= iClose(_Symbol, PERIOD_M30,1);
double high2 = iHigh(_Symbol, PERIOD_M30,2);
double low2 = iLow(_Symbol, PERIOD_M30,2);
//==== HTF TREND (1H EMA50) ====
double emaHTF = iMA(_Symbol, PERIOD_H1, 50, 0, MODE_EMA, PRICE_CLOSE, 0);
double closeHTF = iClose(_Symbol, PERIOD_H1, 0);
bool htfBull = closeHTF > emaHTF;
bool htfBear = closeHTF < emaHTF;
//==== LIQUIDITY SWEEP ====
bool sweepBuy = low1 < low2 && close1 > low2;
bool sweepSell = high1 > high2 && close1 < high2;
//==== BOS ====
bool bosBuy = sweepBuy && close1 > high2;
bool bosSell = sweepSell && close1 < low2;
//==== BUY/SELL CONDITIONS ====
bool buy = bosBuy && rsi > 50 && htfBull;
bool sell = bosSell && rsi < 50 && htfBear;
double lot = CalculateLot(StopLossPoints, RiskPercent);
if(buy)
{
OpenTrade(ORDER_TYPE_BUY, lot, StopLossPoints, TakeProfitPoints, "BUY GBP");
DrawArrow("BUY", 0, low1 - 10*_Point, clrLime, "BUY GBP");
}
if(sell)
{
OpenTrade(ORDER_TYPE_SELL, lot, StopLossPoints, TakeProfitPoints, "SELL GBP");
DrawArrow("SELL", 0, high1 + 10*_Point, clrRed, "SELL GBP");
}
}
//+------------------------------------------------------------------+
double CalculateLot(int slPoints, double riskPercent)
{
double riskMoney = AccountBalance() * riskPercent / 100.0;
double lot = riskMoney / (slPoints * _Point * 10);
lot = MathMax(lot,0.01);
return(NormalizeDouble(lot,2));
}
//+------------------------------------------------------------------+
void OpenTrade(ENUM_ORDER_TYPE type,double lot,int sl,int tp,string comment)
{
double price = (type==ORDER_TYPE_BUY) ? SymbolInfoDouble(_Symbol,SYMBOL_ASK)
: SymbolInfoDouble(_Symbol,SYMBOL_BID);
double slPrice = (type==ORDER_TYPE_BUY) ? price - sl*_Point
: price + sl*_Point;
double tpPrice = (type==ORDER_TYPE_BUY) ? price + tp*_Point
: price - tp*_Point;
MqlTradeRequest req;
MqlTradeResult res;
ZeroMemory(req);
req.action = TRADE_ACTION_DEAL;
req.symbol = _Symbol;
req.volume = lot;
req.type = type;
req.price = price;
req.sl = slPrice;
req.tp = tpPrice;
req.deviation= 20;
req.magic = MagicNumber;
req.comment = comment;
if(!OrderSend(req,res))
{
Print("Trade failed: ",res.retcode);
if(EnableAlerts) Alert("Trade failed: ",res.retcode);
}
else
{
if(EnableAlerts) Alert(comment," opened at ",price);
Print(comment," opened at ",price);
}
}
//+------------------------------------------------------------------+
void UpdateStatus()
{
string text = "SMC GBP PRO EA Status: CONNECTED Account: "+IntegerToString(AccountNumber());
if(PositionsTotal()>0) text += " Trade Open!";
Comment(text);
}
//+------------------------------------------------------------------+
void DrawArrow(string name, int shift, double price, color clr, string text)
{
string objName = name + IntegerToString(TimeCurrent());
if(ObjectFind(0,objName) >=0) ObjectDelete(0,objName);
ObjectCreate(0,objName,OBJ_ARROW,0,Time ,price);
ObjectSetInteger(0,objName,OBJPROP_COLOR,clr);
ObjectSetInteger(0,objName,OBJPROP_WIDTH,2);
ObjectSetInteger(0,objName,OBJPROP_ARROWCODE,233); // חץ
ObjectSetString(0,objName,OBJPROP_TEXT,text);
}
//+------------------------------------------------------------------+
void ManageTrailing()
{
for(int i=PositionsTotal()-1;i>=0;i--)
{
ulong ticket = PositionGetTicket(i);
if(PositionSelectByTicket(ticket))
{
double price = PositionGetDouble(POSITION_PRICE_OPEN);
double sl = PositionGetDouble(POSITION_SL);
double tp = PositionGetDouble(POSITION_TP);
ENUM_POSITION_TYPE type = (ENUM_POSITION_TYPE)PositionGetInteger(POSITION_TYPE);
double newSL = 0;
if(type == POSITION_TYPE_BUY)
{
double trail = SymbolInfoDouble(_Symbol,SYMBOL_BID) - StopLossPoints*_Point;
if(trail > sl) newSL = trail;
}
else if(type == POSITION_TYPE_SELL)
{
double trail = SymbolInfoDouble(_Symbol,SYMBOL_ASK) + StopLossPoints*_Point;
if(trail < sl) newSL = trail;
}
if(newSL != 0)
{
MqlTradeRequest req;
MqlTradeResult res;
ZeroMemory(req);
req.action = TRADE_ACTION_SLTP;
req.symbol = _Symbol;
req.position = ticket;
req.sl = newSL;
req.tp = tp;
OrderSend(req,res);
}
}
}
}
BE-QuantFlow: Adaptive Momentum Trading█ Overview: QuantFlow: Adaptive Momentum Trading
QuantFlow is a sophisticated algorithmic momentum trading method designed specifically for indices and high-beta stocks. However, its logic is universal; with appropriate parameter tuning, it adapts to various asset classes and timeframes.
While the standard momentum indicators (like RSI or MACD) simply measure how fast price is moving (Velocity), QuantFlow analyzes the quality and conviction of the trend . Features like Dynamic Volatility Filtering and Trend Shielding, combined with volatility weighting and a "Dual-Line" approach to distinguish between a sustainable institutional trend and a temporary retail spike, make the indicator unique and more powerful.
█ Why QuantFlow ?
Quant (The Engine): This replaces subjective guessing with objective math.
Instead of just seeing that the price is "up," we measure "how it got there". For example, a stock that rises 1 currency value every day for 10 days (smooth trend) gets a much higher score than a stock that jumps 10 currency value in one minute and does nothing else (erratic noise). This mathematical rigor provides the structure.
█ Core Logic & Philosophy
To understand how QuantFlow calculates momentum, imagine a "Tug-of-War" between Buyers (Bulls) and Sellers (Bears). Most indicators (like RSI) use a single line. If RSI is at 50, it means "Neutral." But "Neutral" can mean two very different things:
Peace: Nothing is happening. No one is buying or selling.
War: Buyers are pushing hard, but Sellers are pushing back equally hard. Volatility is massive.
A single line hides this reality. QuantFlow splits the market into two separate scores:
Bull Score (Green Line): How hard are the buyers pushing?
Bear Score (Red Line): How hard are the sellers pushing?
The Layman's Advantage:
If both lines are low = Sleepy Market (Avoid).
If Green is high and Red is low = Clean Uptrend (Buy).
If Red is high and Green is low = Clean Downtrend (Sell).
If both lines are high = Chaos/War Zone (Wait).
█ How it Weight "Sustenance" (The Critical Quality Check)
This is the most unique aspect of QuantFlow: Trend direction alone is not enough; Sustenance is weighed equally . Standard indicators treat every 10 currency value movements the same way with no distinction. However, QuantFlow asks, "Did you hold the ground you gained?"
Scenario A (High Sustenance) : A stock opens at 100, marches to 110, and closes at 110.
Verdict : Buyers pushed up and sustained the price.
QuantFlow Weight : 100%. This is a high-quality move.
Scenario B (Low Sustenance) : A stock opens at 100, spikes to 110, but gets sold off to close at 102.
Verdict : Buyers pushed up (Trend is Up), but failed to sustain it (Long Wick).
QuantFlow Weight : 20%. This is treated as "Noise" or a trap.
By mathematically weighing the Close Location Value (where the candle closes relative to its high/low), QuantFlow filters out "Gap-and-Fade" traps and exhaustion spikes that fool traditional indicators.
Comparisons: QuantFlow vs. The Rest
Calculation Logic : Standard RSI/MACD measures simple price change over time. QuantFlow measures Price Change 'times (x)' Conviction (Sustenance Weighting).
Visual Output : Standard tools show a single line (0-100), often hiding market conflict. QuantFlow displays Dual Lines (Bull vs Bear Intensity) to reveal the true state of the battle.
Trap Handling : Standard indicators are often fooled by sharp spikes. QuantFlow ignores "Gap-and-Fade" moves with poor closing conviction.
Adaptability : Standard tools use static levels (e.g., Overbought > 70). QuantFlow uses Dynamic Bands that adjust automatically to recent volatility.
█ Dynamic Volatility Filtering
Unlike standard indicators that use fixed levels (e.g., "Buy if RSI > 50"), QuantFlow acknowledges that "50" means something different in a quiet market versus a crashing market. This section explains the statistical engine driving the signals.
The Problem with Static Levels : In a low-volatility environment, a momentum score of 55 might indicate a massive breakout. In a high-volatility environment, a score of 55 might just be random noise. A fixed threshold cannot handle both scenarios.
The Solution: Adaptive Statistics : The script maintains a memory of the Momentum Events. It doesn't just look at price; it looks at where the momentum occurred in the past and draws a "Noise Zone" (Grey Band). This logic acts as a "Smart Gatekeeper" for trade entries:
Scenario A: Inside the Noise (The Filter)
If a new momentum signal happens inside the Noise Zone, the script assumes it is likely chop or noise.
Action : It forces a wait period. The signal is delayed until the trend sustains itself for Confirm Bars; else the signal is cancelled. This filters out ~70% of false signals in sideways markets.
Scenario B: Outside the Noise (The Breakout)
If a new momentum signal happens outside the Noise Zone (or the momentum score smashes through the Upper Band), it is statistically significant (an outlier event).
Action: It triggers an Immediate Entry. No waiting is required because the move is powerful enough to escape the historical noise zone.
█ The ⚠️ "Warning" System (Heads-up for Smart Reversals)
While you are directional if there is potential reversal signal, it provides the heads-up warning for a better decision-making
█ Special Utility: Ghost Mode
For intraday traders, the biggest disruption to "Flow" is the mandatory broker square-off at 3:15 PM (considering Indian Market). Often, a trend continues overnight, and the trader misses the gap-up opening the next morning because their algo was flat.
Ghost Mode is a unique feature that runs silently in the background:
At Square-off: The strategy closes your official position to satisfy the broker.
In the Background: It keeps the trade "alive" virtually (Ghost).
Next Morning: If the market opens in the trend's favor, the strategy re-enters the trade automatically. This approach ensures you capture the full swing of the trend, even if you are forced to exit at the previous session.
█ Advice on this indicator:
Parameter Calibration: The default settings are optimized for BankNifty on 5-minute charts. If you trade stocks, crypto, commodities, or any higher timeframes (e.g., 15-min or hourly), you must adjust these.
Low Volatility Assets: Reduce Stop Multiplier to 2.0.
High Volatility Assets: Increase Momentum Lookback to 50 to filter noise.
Confluence (Additional Confirmation): While QuantFlow is a complete system, using it alongside Key Support/Resistance Levels or Volume Profile provides the highest probability setups.
EMA Multi-Type StrategyThis is a price-action + EMA trend strategy that:
Uses EMA as trend filter
Looks for pullbacks and structure shifts near the EMA
Trades 3 different entry patterns (TYPE 1 / 2 / 3)
Allows:
Fixed SL–TP (RR based)
OR ATR trailing stop
Optionally blocks opposite trades until the current trade exits
Think of it as:
“Trade continuation after pullback in EMA trend, with multiple confirmation strengths.”
ML-Inspired Adaptive Momentum Strategy (TradingView v6)This strategy demonstrates an adaptive momentum approach using volatility-normalized trend strength. It is designed for educational and analytical purposes and uses deterministic, fully transparent logic compatible with Pine Script v6.
ML-Inspired Concept (Educational Context)
Pine Script cannot train or execute real machine-learning models.
Instead, this strategy demonstrates ML-style thinking by:
Converting price data into features
Normalizing features to account for volatility differences
Producing a bounded confidence score
Applying thresholds for decision making
This is not predictive AI and does not claim forecasting capability.
Strategy Logic
EMA is used to measure directional bias
EMA slope represents momentum change
ATR normalizes the slope (feature scaling)
A clamped score between −1 and +1 is generated
Trades trigger only when the score exceeds defined thresholds
Risk & Execution
Position size capped at 5% equity
Commission and slippage included for realistic testing
Signals are calculated on closed bars only
Purpose
This script is intended to help traders explore adaptive momentum concepts and understand how feature normalization can be applied in systematic trading strategies.
Supertrend + OBV AND Logic (long only)Supertrend + OBV Regime Filter (Long-Only) is a rule-based trend regime detection script that combines ATR-based Supertrend structure with volume-confirmed momentum using On-Balance Volume (OBV). The Supertrend (ATR 10, multiplier 3) defines the primary market regime and acts as the absolute authority for trend direction, while OBV—manually calculated for robustness and smoothed using EMA(20) with a signal EMA(20)—is used to confirm participation and momentum.
A long signal is generated only on confirmed bar close when the Supertrend is bullish (price above the Supertrend line) and OBV momentum turns positive via an EMA crossover, enforcing strict AND-logic confirmation and preventing entries during low-volume or transitional phases.
The strategy maintains a single long position per trend, with no pyramiding, averaging, or discretionary overrides. A full exit is triggered immediately when the Supertrend flips bearish, serving as a hard regime exit rather than a profit-target-based stop.
Additionally, an OBV downside crossover generates a non-executable “Protect” signal (visual only), intended for risk-management actions such as reducing exposure or pausing position additions, particularly for grid or DCA implementations.
This script is not designed as a grid, scalping, or buy-and-hold strategy; instead, it functions as a conservative trend and regime filter suitable for discretionary trading or as a signal layer to control automated long-bias execution systems. Forward testing and proper risk management are strongly recommended.
SMA Strategy [MK]Overview
This strategy is a momentum-based trend-following system designed to capture sustained market moves while minimizing "whipsaws" often found in sideways markets. It utilizes a dual-SMA filter for trend direction, a precise price-crossover trigger for entry, and the Average Directional Index (ADX) to gauge market strength.
How It Works
The strategy follows a strict "Trend + Momentum + Strength" hierarchy:
1. Trend Identification (The Filter) The script uses a Fast SMA (20) and a Slow SMA (50).
Long Bias: SMA-20 > SMA-50.
Short Bias: SMA-20 < SMA-50.
2. Precise Entry (The Trigger) Unlike strategies that enter simply because the price is above a line, this script requires a Price Crossover.
Long Entry: Price must actively cross from below to above the SMA-20.
Short Entry: Price must actively cross from above to below the SMA-20.
3. Trend Strength (The ADX Gatekeeper) To solve the problem of sideways markets where moving averages run parallel, we’ve integrated the ADX (Average Directional Index). The strategy will only trigger a trade if the ADX is above a user-defined threshold (default is 25), ensuring we only enter when the market is trending.
4. RSI Safety Filter To prevent "buying the top" or "selling the bottom," the RSI checks for overextended conditions. It prevents long entries if the RSI is already overbought and short entries if it is oversold.
Exit Logic
The strategy features three layers of protection:
Trend Reversal Exit: Closes the position if the price crosses back over the SMA-20 while the macro trend (SMA-20/SMA-50) has flipped.
Fixed Take Profit: A percentage-based target to lock in gains during sharp moves.
Fixed Stop Loss: A percentage-based safety net to protect capital.
Key Features
Directional Selector: Choose between "Long Only," "Short Only," or "Both."
Visual Feedback: Background colors highlight "Trending" (Green) vs "Sideways" (Red) market regimes.
Fully Customizable: All lengths and thresholds for SMAs, RSI, and ADX can be adjusted to fit different assets and timeframes.
Instructions for Use
Timeframe: This strategy is optimized for trending timeframes such as the 1-Hour (1H), 4-Hour (4H), or Daily (D). Using it on very low timeframes (1-minute or 5-minute) may increase the number of false signals due to market noise.
Asset Classes: Best suited for high-volume assets like Major Forex Pairs, Large-Cap Stocks, and Blue-Chip Cryptocurrencies.
Parameter Tuning: Use the "Strategy Tester" to find the ideal ADX Threshold for your specific asset. Volatile assets usually require a higher ADX (30+) to filter out fake breakouts.
Disclaimer
Financial Risk Warning: The script provided is for educational and informational purposes only. Trading involves significant risk, and there is always the potential for loss. Past performance, whether simulated or real, is not a guarantee of future results.
The author of this script is not a financial advisor. This indicator is not a signal service or a recommendation to buy or sell any security. Always perform your own due diligence and test any strategy thoroughly on a demo account before risking live capital. By using this script, you acknowledge that you are solely responsible for your trading decisions and any resulting financial outcomes.
Smart Trader,Episode 1, by Ata Sabanci | Unified Matrix⚠️ **CRITICAL: READ BEFORE USING** ⚠️
This strategy is **100% VOLUME-BASED** and requires **Lower Timeframe (LTF) intrabar data** for accurate calculations. Please understand the following limitations before using:
**📊 DATA ACCURACY LEVELS:**
• **1T (Tick)** — Most accurate, real volume distribution per tick
• **1S (1 Second)** — Reasonably accurate approximation
• **15S (15 Seconds)** — Good approximation, longer historical data available
• **1M (1 Minute)** — Rough approximation, maximum historical data range
**⚠️ BACKTEST & REPLAY LIMITATIONS:**
• TradingView's Strategy Tester uses historical LTF data which may be limited depending on your subscription plan
• Replay mode results may differ from live trading due to data availability
• For longer backtest periods, use higher LTF settings (15S or 1M)
• Not all symbols/exchanges support tick-level data
• Crypto and Forex typically have better LTF data availability than stocks
**💡 A NOTE ON TOOLS:**
Successful trading requires proper tools. Higher TradingView plans provide access to more historical intrabar data, which directly impacts the accuracy of volume-based calculations. More precise volume data leads to more reliable signals. Consider this when evaluating your trading infrastructure.
**WHY "EPISODE 1"?**
This strategy is titled "Episode 1" because it focuses exclusively on **Highest Buyers (HB)** — a single but powerful concept in volume analysis.
**The Philosophy:**
A single high-volume buying event can tell us a story about market psychology:
• Where did the biggest buyers enter?
• How much of their power remains?
• Are sellers consuming their advantage?
• At what rate is the balance shifting?
By focusing on just ONE aspect of volume analysis, traders can deeply understand how a buying surge affects future price action before moving to more complex multi-factor analysis.
**The Reality:**
This script alone is approximately **2000 lines of code** — and it only analyzes buyers. A comprehensive system covering all aspects (sellers, combined analysis, multi-timeframe correlation) would be significantly larger and computationally heavier. Breaking this into focused modules allows for:
• Deeper understanding of each component
• Lighter, more responsive scripts
• Educational progression from simple to complex
**OVERVIEW**
Smart Trader EP1 is a volume-based trading strategy that tracks the balance of power between buyers and sellers through the lens of the **Highest Buyers event**. Unlike traditional indicators that rely on price patterns or mathematical formulas, this strategy analyzes *actual volume flow* to identify who is in control of the market.
The core philosophy is simple: **markets move when one side (buyers or sellers) exhausts their power while the opposing side accumulates strength.** By measuring this power shift in real-time, the strategy identifies high-probability entry and exit points.
**HOW IT WORKS**
**1. Volume Engine**
The strategy splits each candle's volume into buying volume and selling volume using intrabar data. In *Intrabar (Precise)* mode, it uses actual tick-by-tick or second-by-second data to calculate the exact buy/sell distribution. In *Geometry* mode, it approximates based on candle structure (close position within the range).
**2. Event Detection**
Within the lookback window, the strategy identifies key events:
• **HB (Highest Buyers)** — The candle with maximum buying volume (potential resistance when exhausted)
• **HS (Highest Sellers)** — The candle with maximum selling volume (potential support when exhausted)
• **LB (Lowest Buyers)** — The candle with minimum buying volume (buyer absence)
• **LS (Lowest Sellers)** — The candle with minimum selling volume (seller absence)
These events create dynamic support and resistance levels based on actual volume, not arbitrary price levels.
**3. Power Tracking (Attrition Model)**
For the Highest Buyers event (HB), the strategy tracks:
• **Start Power (X)** — The initial buying volume at the HB event
• **Consumed Power (Y)** — How much selling volume has accumulated since the event
• **Remaining Power (Z)** — Start Power minus Consumed Power (X - Y)
• **Opponent Dominance** — When Remaining Power goes negative (Z < 0), sellers have overtaken buyers
Think of it like a battle: buyers establish a position (HB), and sellers gradually consume their power. When buyers' power is exhausted (Remaining Power ≤ 0), sellers have taken control.
**4. Depletion Markers**
Visual markers appear on the chart when power reaches critical thresholds:
• **🔋** — Buyers consumed 100% (Remaining = 0)
• **🚨** — Buyers consumed 200% (Opponent Dominance = 100%)
• **🪫** — Sellers consumed 100%
• **⚠️** — Sellers consumed 200%
**5. Cumulative Delta**
Beyond tracking power at specific events, the strategy calculates the cumulative buy volume minus sell volume since the HB event. This shows the *net flow* of money:
• **Positive Delta** — More buying than selling since HB (bullish pressure)
• **Negative Delta** — More selling than buying since HB (bearish pressure)
**6. Trend Channel**
A 5-point linear regression channel identifies the current trend:
• **UPTREND** — Both upper and lower channel lines slope upward
• **DOWNTREND** — Both lines slope downward
• **RANGING** — Mixed or flat slopes
The strategy also tracks where the HB event occurred within this channel (TOP, UPPER, MIDDLE, LOWER, BOTTOM) to contextualize the signal.
**7. Nearest Event Analysis**
The strategy identifies which event is closest to the current candle and analyzes the price action *after* that event:
• How many bullish vs bearish candles followed?
• Does post-event momentum confirm or contradict the event type?
This prevents false signals when, for example, a bearish event occurs but is immediately followed by strong bullish candles.
**SIGNAL LOGIC**
**🟢 LONG Signal Conditions:**
• Uptrend with positive cumulative delta and buyers accumulating
• At channel bottom/lower with strong buyer power remaining
• After a bearish event (HS) with bullish post-event momentum (reversal signal)
• Ranging market with positive delta and strong power
**🔴 SHORT Signal Conditions:**
• Downtrend with negative cumulative delta and sellers in control
• Opponent Dominance (buyer power exhausted) with bearish momentum
• Buyer Trap: HB at TOP in uptrend but power exhausted and delta negative
• After a bullish event (HB) with bearish post-event momentum (trap signal)
**⏳ NO_TRADE Conditions:**
• Conflicting signals (e.g., bearish event but bullish post-momentum)
• Ranging market without clear direction
• Mixed power readings
• Price position contradicts signal direction
**STRATEGY EXECUTION**
**Entry Rules:**
• Enter LONG when signal is "LONG" and conditions are valid
• Enter SHORT when signal is "SHORT" and conditions are valid
• **Pyramid**: Up to 2 entries allowed in the same direction (configurable)
• Each entry uses 10% of equity by default
• Only one entry per confirmed candle (prevents multiple fills)
**Stop Loss (Event Line Based):**
• **LONG positions**: Stop Loss placed below the HS line (seller support level)
• **SHORT positions**: Stop Loss placed above the HB line (buyer resistance level)
• A small buffer percentage is added to prevent premature stops
**Take Profit (Event Line Based):**
• **LONG positions**: Take Profit near the HB line (buyer resistance target)
• **SHORT positions**: Take Profit near the HS line (seller support target)
• A small buffer percentage ensures realistic fill expectations
**Exit Rules:**
• Exit LONG when signal changes to SHORT
• Exit SHORT when signal changes to LONG
• **NO_TRADE signal = HOLD** (do not exit, wait for clear direction)
• SL/TP orders remain active regardless of signal changes
**SETTINGS GUIDE**
**⚙️ General Settings:**
• *Calculation Method* — Choose between Intrabar (Precise) or Geometry (approximation)
• *Intrabar Resolution* — LTF for volume data (1T, 1S, 15S, 1M)
• *Lookback Length* — Window for scanning events (10-150 bars)
• *Timezone Offset* — Adjust clock display to your local time
**📊 Matrix Display Settings:**
• *Show Unified Matrix* — Toggle the information dashboard
• *Show Event Lines* — Toggle horizontal lines at event prices
• *Panel Size/Position* — Customize dashboard appearance
• *Projection Bars* — Extend event lines into the future
• *Depletion Threshold* — Percentage for depletion markers (default: 100%)
**🏷️ Rank Labels Settings:**
• *Show Rank Labels (HB/HS)* — Display labels on highest volume candles
• *Show Low Labels (LB/LS)* — Display labels on lowest volume candles
• *Ranks Count* — Number of rankings to display (1-5)
**📐 Trend Channel Settings:**
• *Show Trend Channel* — Toggle the 5-point regression channel
• *Line Color/Fill/Width/Style* — Customize channel appearance
**🎯 Trade Signal Settings:**
• *Long: Min Remaining Power %* — Minimum buyer power for LONG signal (default: 50%)
• *Short: Max Remaining Power %* — Maximum power for SHORT signal (default: 30%)
• *Opponent Dominance Threshold* — When to consider power "exhausted" (default: 0%)
• *Max Decay Angle* — Maximum consumption rate for valid entries (default: 60°)
**📈 Strategy Execution Settings:**
• *Enable Strategy* — Turn automatic trading on/off
• *Allow LONG/SHORT* — Enable or disable specific directions
• *Max Pyramid Entries* — Maximum entries in same direction (1-3)
• *SL Buffer %* — Distance below/above event line for stop loss (default: 0.15%)
• *TP Buffer %* — Distance from event line for take profit (default: 0.05%)
**VISUAL ELEMENTS**
**Chart Labels:**
• **#1 HB** — Highest Buyers (rank label on candle high)
• **#1 HS** — Highest Sellers (rank label on candle low)
• **#1 LB** — Lowest Buyers (rank label on candle high)
• **#1 LS** — Lowest Sellers (rank label on candle low)
• **🔋 / 🚨** — Buyer power depletion markers
• **🪫 / ⚠️** — Seller power depletion markers
**Event Lines:**
• **Blue horizontal lines** — HB price levels (buyer entry points)
• **Red horizontal lines** — HS price levels (seller entry points)
• **Cyan lines** — LB price levels
• **Orange lines** — LS price levels
• **Dashed extensions** — Projected levels into future bars
**Trend Channel:**
• **Orange lines** — Upper and lower channel boundaries (5-point regression)
• **Orange fill** — Channel area (90% transparency)
**Matrix Dashboard (6 rows):**
• Row 1: Header with symbol, LTF setting, and local clock
• Row 2: Volume snapshot (Total, Buy, Sell, Delta)
• Row 3: Column headers
• Row 4: Highest Buyers data (Age, Start Power, Consumed, Remaining, Decay, ETA)
• Row 5: Highest Sellers data
• Row 6: Signal Evaluation (Trend, Zone, Nearest Event, Signal, Reason)
**Strategy Markers:**
• **Green triangle up** — LONG entry
• **Red triangle down** — SHORT entry
• **Faded triangles** — Pyramid entries
• **Colored lines** — SL (red) and TP (green) levels when in position
**BEST PRACTICES**
**For Maximum Accuracy:**
1. Use **1T (tick)** or **1S** intrabar resolution when available
2. Trade liquid markets with good volume data (crypto majors, forex majors, high-volume stocks)
3. Use smaller lookback length (20-30) to ensure all bars have valid LTF data
4. Monitor the "Intrabar Valid Bars" counter in the matrix header
5. If you see data warnings, reduce lookback or increase LTF resolution
**For Longer Backtests:**
1. Use **15S or 1M** intrabar resolution for more historical data
2. Increase lookback length if needed
3. Understand that accuracy decreases with higher LTF settings
4. Consider using Geometry mode for very long backtests (approximation but always available)
**Understanding the Signals:**
• Pay attention to the signal *reasoning* shown in the matrix — it explains WHY
• **NO_TRADE** means the system sees conflicting factors — respect this caution
• Event lines act as dynamic S/R — they update as new volume events occur
• Cumulative Delta (Δ) often provides early warning of trend changes
**Risk Management:**
• The default 10% per entry with max 2 pyramids = 20% maximum exposure
• Event-line-based SL/TP provides logical levels based on actual volume events
• Always verify signals with your own analysis before trading
**INTERPRETING THE MATRIX**
**Power Status Examples:**
• *Remaining Power: 75%* — Buyers still have most of their strength
• *Remaining Power: 25%* — Buyers nearly exhausted, watch for reversal
• *Opponent Dominance: -50%* — Sellers have consumed 150% of buyer power (strong bearish)
**Decay Angle:**
• *Low angle (0-30°)* — Slow consumption, power lasting longer
• *High angle (60-90°)* — Rapid consumption, expect quick exhaustion
**ETA to Parity:**
• Shows estimated bars until Remaining Power reaches zero
• *"Overtaken"* with 🚨 means sellers have already dominated
**LIMITATIONS & DISCLAIMER**
**Technical Limitations:**
• Requires sufficient historical LTF data (varies by TradingView plan and symbol)
• Intrabar (Precise) mode may show invalid data warnings on symbols with limited history
• Strategy tester may not have access to the same LTF data as live trading
• Maximum 500 lines and 500 labels (TradingView platform limits)
**Important Notes:**
• This strategy focuses on **Highest Buyers only** — it does not analyze all market factors
• Past performance does not guarantee future results
• Volume data quality varies significantly between symbols and exchanges
• The strategy's signals are analytical tools, not trading recommendations
**Risk Disclaimer:**
This strategy is provided for **educational and informational purposes only**. Trading involves substantial risk of loss and is not suitable for all investors.
• Always use proper risk management
• Never risk more than you can afford to lose
• Backtest results may differ significantly from live trading
• You are solely responsible for your trading decisions
**TECHNICAL SPECIFICATIONS**
• Pine Script Version: 6
• Calculation: calc_on_every_tick=true, use_bar_magnifier=true
• Default Capital: 10,000
• Default Position Size: 10% of equity
• Maximum Lines: 500
• Maximum Labels: 500
• External Library: TradingView/ta/10 (for requestUpAndDownVolume)
*Smart Trader EP1 — Understanding Volume, One Event at a Time*
ORB Breakout Strategy with VWAP and Volume FiltersOverview
This strategy implements the classic Opening Range Breakout (ORB) methodology, a well-documented approach in trading literature that has been used by institutional and retail traders for decades. The strategy identifies the high and low of the first 15 minutes of the trading session, then trades breakouts with defined risk management.
This implementation includes multiple customizable filters (VWAP, Volume, Candle Strength) that traders can enable, disable, and tune to find configurations that work for their specific markets and trading style.
How It Works
Opening Range Calculation
The strategy captures the high and low of the first N bars after the session open (default: 3 bars on a 5-minute chart = 15 minutes). These levels become the breakout triggers for the session.
Entry Logic
Long Entry: When a bar closes above the ORB High and all enabled filters pass
Short Entry: When a bar closes below the ORB Low and all enabled filters pass
Exit Logic
Take Profit: Configurable multiple of the ORB range (default: 1x = full range beyond breakout level)
Stop Loss: Opposite side of the ORB range
Breakeven: Optional stop adjustment to entry price when trade reaches configurable profit threshold
Session Close: All positions automatically closed at end of trading session
Configurable Filters
All filters can be independently enabled or disabled:
1. VWAP Filter
Requires price above/below session-anchored VWAP
Requires VWAP slope confirmation (configurable lookback and minimum slope)
Purpose: Align trades with intraday trend direction
2. Volume Filter
Requires minimum volume on the breakout bar
Purpose: Confirm institutional participation in the breakout
3. Candle Strength Filter
Requires close in upper/lower portion of the bar range
Purpose: Filter out weak breakouts with poor conviction
Strategy Properties
Initial Capital - $50.000USD
Position Size - 1 contract (fixed)
Commission - $4.00 per contract
Slippage - 2 ticks
Margin - 1%
Pyramiding - Disabled
Backtest Results (NQ)
Recent Performance (Jan 2025 - Jan 2026)
Total Trades - 243
Win Rate - 39.09%
Profit Factor - 1.03
Net P&L - $3,581 (+7.16%)
Max Drawdown - $25,447 (39.96%)
Long-Term Performance (2010 - 2026)
Total Trades - 1699
Win Rate - 37.61%
Profit Factor - 0.756
Net P&L - ($49,632) (-99.26%)
Max Drawdown - $50,262 (99.27%)
Important: Long-term results show negative expectancy with default settings. This strategy is published as a research framework, not a ready-to-trade system. Users are encouraged to experiment with different configurations to find their edge.
Settings Guide
Main Settings
ORB Bars: Number of bars for opening range (3 = 15 min on 5-min chart)
Trading Session: Time window for trading (e.g., 0930-1200 for morning only)
Timezone: Your market's timezone
Take Profit: Multiple of ORB range for target
Breakeven Trigger: Distance to move stop to entry
Max Trades Per Day: Daily trade limit
VWAP Filter
Use VWAP Filter: Enable/disable
VWAP Slope Lookback: Bars to measure VWAP direction
Min VWAP Slope: Minimum slope threshold
Volume Filter
Use Volume Filter: Enable/disable
Min Breakout
Volume: Minimum contracts required
Candle Strength Filter
Use Candle Strength Filter: Enable/disable
Min Candle Strength: Required close position (0.7 = top/bottom 30%)
Research Suggestions
This strategy provides a foundation for exploring ORB-based approaches. Consider testing:
Different ORB periods: 5, 10, 15, or 30 minutes
Session variations: Morning only (0930-1200), afternoon, or full day
Direction bias: Long-only or short-only based on daily trend
Filter combinations: Different mixes of VWAP, volume, and candle filters
Take profit ratios: 0.5x, 1x, 1.5x, or 2x ORB range
Market regimes: Performance may vary in trending vs ranging markets
Different instruments: Test on ES, NQ, MNQ, or other futures
Visual Elements
Orange Background: ORB forming period
Green Background: Active trading session
Green Line: ORB High level
Red Line: ORB Low level
VWAP Line: Green = upslope, Red = downslope, Gray = flat
White Line: Trade entry price
Lime Line: Take profit level
Red Line: Stop loss level
Orange Line: Breakeven trigger level
Blue Background: Breakeven activated
Triangles: Entry signals (only appear when trade executes)
Limitations
Negative long-term expectancy: Default settings do not produce profitable results over extended periods
Parameter sensitivity: Results highly dependent on filter settings and market conditions
Market regime dependent: May perform differently in trending vs choppy markets
Commission impact: Frequent trading accumulates significant transaction costs
Curve fitting risk: Optimized settings may not persist in future markets
Disclaimer
This strategy is provided for educational and research purposes only. It does not constitute financial advice.
Past performance does not guarantee future results
Backtested results may not reflect actual trading conditions
The long-term backtest shows significant negative returns
Always paper trade before risking real capital
Never risk more than you can afford to lose
Conduct your own research and due diligence
This is a research framework designed for traders to explore and customize, not a plug-and-play trading system.
VIOP Scalping - OriginalVIOP Scalping – Original is a rule-based scalping strategy ported from an original C# logic set. It aims to trade only when trend direction, momentum, and trend strength align, then manages the position using fixed take-profit/stop-loss percentages with an optional trailing mechanism to protect gains during favorable moves.
This strategy is provided for educational and backtesting purposes only. It is not financial advice and does not guarantee profitability. Always test thoroughly before any live usage.
Core Concept
Follow the dominant WMA trend, confirm momentum with EMA separation, filter conditions with RSI + ADX, then exit using fixed TP/SL with trailing behavior after a defined profit threshold.
How the Strategy Works
Trend Direction is defined by WMA: above WMA = long bias, below WMA = short bias.
Momentum is measured via Fast EMA vs Slow EMA and the EMA difference.
Trend Strength is confirmed using ADX (must exceed a threshold).
RSI filters trades to avoid entering when momentum is likely overextended or weak.
A no-trade session blocks entries during a predefined time window (default 09:30–10:05).
Exit logic uses fixed percent TP/SL, with an optional trailing mechanism that activates after a profit threshold.
Inputs and Settings
Trend and Indicator Settings
Main Trend WMA: Determines directional bias (price above = long, price below = short).
Fast EMA / Slow EMA: Used to measure momentum and directional separation.
RSI Period: Filters entries based on RSI range constraints.
ADX Period: Measures trend strength (must exceed threshold to allow entries).
Threshold Settings
EMA Difference Threshold: Minimum EMA separation required to validate momentum.
ADX Threshold: Minimum ADX required to confirm trend strength.
RSI Long Ceiling: RSI must remain below this value for long entries.
RSI Short Floor: RSI must remain above this value for short entries.
Risk Management Settings
Take Profit %: Default TP distance in percent.
Strong Trend Take Profit %: Higher TP used when a “strong trend” condition is detected.
Stop Loss %: Fixed SL distance in percent.
Trailing Activation %: Profit threshold at which trailing starts.
Trailing Distance %: Trailing offset distance used once trailing is active.
Time Filter
No-Trade Hours: Default session is 09:30–10:05. During this window, the strategy does not open new trades.
Entry Logic
No-Trade Time Filter
If the current bar falls inside the no-trade session, entries are blocked.
Long Entry Conditions
Price is above the WMA trend line.
EMA difference is positive and greater than the EMA Difference Threshold.
EMA momentum is increasing (current EMA diff > previous EMA diff).
RSI is within the defined range (RSI > 48 and RSI < RSI Long Ceiling).
Close is higher than the previous close.
ADX is above the ADX Threshold.
Short Entry Conditions
Price is below the WMA trend line.
EMA difference is negative and lower than -EMA Difference Threshold.
Bearish momentum is increasing (current EMA diff < previous EMA diff).
RSI is within the defined range (RSI < 52 and RSI > RSI Short Floor).
Close is lower than the previous close.
ADX is above the ADX Threshold.
Strong Trend Logic (Dynamic TP Selection)
If price is far from the WMA (absolute distance > 20 points) AND EMA separation is strong (absolute EMA diff > 1.5 points), the strategy treats the environment as a strong trend.
In strong trend mode, the strategy uses “Strong Trend Take Profit %” instead of the default “Take Profit %”.
Exit Management (TP/SL + Trailing)
The strategy uses fixed percentage-based TP and SL levels.
Trailing logic is enabled via strategy.exit and activates only after price moves in profit by the defined Trailing Activation %.
Once activated, trailing follows price using the defined Trailing Distance % offset.
This is designed to secure partial gains during extended moves while still allowing room for continuation.
What You See on the Chart
WMA Trend Line (Main Trend Filter).
Fast EMA and Slow EMA (Momentum Confirmation).
Strategy entry/exit markers generated by TradingView.
Recommended Use
Scalping systems that rely on trend-following and momentum confirmation.
Markets where ADX filtering helps avoid choppy conditions.
Traders who want a simple, parameter-driven TP/SL system with trailing after confirmation.
Important Notes
The no-trade session depends on your chart/session settings. Ensure your symbol/session configuration matches your intended market hours.
Percent-based exits scale with price; results will vary across instruments and volatility regimes.
Always validate behavior using bar replay, forward testing, and realistic commission/slippage assumptions.
VIOP Scalping - ATR SNIPERVIOP Scalping – ATR SNIPER is a momentum-based scalping strategy designed to capture short, high-probability moves while keeping risk strictly defined using ATR-based stop-loss and fixed risk/reward targets. The strategy trades only when trend direction, momentum, and strength are aligned.
This script is provided for educational and testing purposes only. It does not guarantee profitability and must be used with proper risk management.
Core Idea
Trade in the direction of the dominant trend, confirm momentum acceleration, and manage risk using ATR-based dynamic stops and targets.
How the Strategy Works
The main trend is defined using a Weighted Moving Average (WMA).
Momentum is measured by the distance and direction between a fast EMA and a slow EMA.
Trend strength is confirmed using ADX.
RSI is used as a filter to avoid weak or overextended market conditions.
Entries are blocked during a predefined no-trade time window to avoid high-noise periods.
Long Entry Conditions
Fast EMA is above Slow EMA and the EMA difference is greater than the minimum threshold.
EMA momentum is increasing compared to the previous bar.
RSI is within the user-defined long range.
Current close is higher than the previous close.
ADX is above the minimum strength threshold.
Price is above the WMA trend line.
The current bar is not inside the no-trade session.
Short Entry Conditions
Fast EMA is below Slow EMA and the EMA difference is below the negative threshold.
Bearish EMA momentum is increasing.
RSI is within the user-defined short range.
Current close is lower than the previous close.
ADX is above the minimum strength threshold.
Price is below the WMA trend line.
The current bar is not inside the no-trade session.
Risk Management – ATR Sniper Logic
Stop-loss distance is calculated as ATR multiplied by the ATR Multiplier.
Take-profit distance is calculated using the defined Risk/Reward ratio.
Stop-loss and take-profit levels are dynamically calculated per trade.
Only one position can be open at any given time.
What You See on the Chart
Weighted Moving Average (WMA) trend line.
Fast EMA and Slow EMA lines.
Dynamic stop-loss line during active trades.
Dynamic take-profit line during active trades.
Recommended Use
Intraday scalping on VİOP instruments.
Momentum-based short-term trading.
Traders who prefer rule-based systems with strict risk control.
Always backtest and forward-test on your own instruments and timeframes before using this strategy in live markets.
Algomist - Adaptive Velocity Cross🚀 Algomist: The Adaptive Velocity Cross (AVC)
Automate Your Edge
This strategy transcends the limitations of classic Moving Average (MA) crossovers. The Adaptive Velocity Cross (AVC) is a state-of-the-art trend-following system designed for automated execution, filtering out low-probability whipsaws and prioritizing high-momentum breakouts in volatile markets.
It's not just a signal generator; it's a fully automated, risk-managed trading plan that delivers structured trade signals directly to your Algomist account.
🔥 Key Features & Technology
Adaptive Hull Moving Averages (HMA): Utilizes the Hull MA to significantly reduce lag compared to standard EMAs and SMAs. The faster and slower HMAs provide a highly responsive gauge of short-term and medium-term trend direction.
Multi-Layer Volatility Filtering: Trades are strictly prohibited during flat, low-volatility market conditions.
Current Timeframe Filter (ATRMinFilter): Ensures trades only fire when current market momentum is strong enough to carry the trend.
Higher Timeframe Filter: Checks the ATR on a higher timeframe (e.g., 1H) to confirm the structural trend strength, preventing entries during tight squeezes.
Visual Trend Velocity: The space between the Fast (Blue) and Slow (Pink) HMAs is colored and filled, providing an immediate visual cue for trend direction and strength (width of the band).
Asymmetric Risk Management: Uses the dynamic Average True Range (ATR) to calculate Stop Loss and Take Profit levels, ensuring risk and reward are proportional to current market volatility.
⚙️ How It Works (The Logic)
The AVC only executes a trade when all three high-conviction criteria are met:
Trend Signal: The Fast $\text{HMA}$ crosses the Slow $\text{HMA}$ (Crossover).
Volatile Market Confirmation: The market must be sufficiently volatile on both the current timeframe and the higher structural timeframe ($\text{ATR}$ filters passed).
Risk Management: A defined $\text{SL}$ (Stop Loss) and $\text{TP}$ (Take Profit) are calculated based on the current market $\text{ATR}$ to manage the position before entry.
🤖 Automation Ready
The strategy is built with automation as the priority. Upon a confirmed entry, the script sends a cleanly formatted JSON string via a TradingView Webhook alert to Algomist. Create your account and get your own web hook @ www.algomist.app
Example Alert Output:
{
"symbol": "ETHUSDC",
"side": "LONG",
"entry_price": 67500.0,
"stop_loss": 66000.0,
"take_profit": 70000.0,
"timestamp": 1766715660462
}
This signal is ready for immediate consumption by your Algomist execution engine, ensuring lightning-fast and error-free order placement.
📊 Recommended Use
Asset Class: Highly effective on high-liquidity, high-volatility assets (e.g., Crypto Majors, Forex Pairs, Indices).
Timeframes: Works best on 1m to 15 min charts.
Risk Profile: Medium-to-High frequency trend-following system.
Disclaimer: The strategy code provided is for informational and educational purposes. Past performance is not indicative of future results. Always backtest and forward-test any automated strategy extensively before using real capital.
Golder/Silter SetupsGolden/Silver Strategy
Overview
The Tony Rago Golden/Silver Strategy is a high-precision mean-reversion system specifically engineered for the Nasdaq (NQ/MNQ). It leverages the psychological 100-point price blocks to identify institutional exhaustion and reversal points.
Unlike standard "grid" bots, this strategy uses a sophisticated "Arm & Fire" logic: it requires a specific price "touch" to arm the setup, followed by a retracement to a "Golden" entry level to execute.
Key Logic: The 100-Point Grid
The strategy divides price action into 100-point blocks (e.g., 19500 to 19600).
Golden Setup (Long): Triggered when price touches the 50 level (mid-point). The order is placed at the 26 level on the retracement.
Silver Setup (Short): Triggered when price touches the 00 or 100 levels (block boundaries). The order is placed at the 77 or 26 levels on the retracement.
Professional Risk Management
This edition features a Dual-Contract Management system designed for Prop Firm consistency:
Contract 1 (The Scalp): Aims for a quick 24-point target (TP1) to secure realized gains and cover costs.
Contract 2 (The Runner): Stays in the trade for an extended 51-point target (TP2).
Automated Break-Even (BE): The moment TP1 is hit, the Stop Loss for the Runner is automatically moved to the entry price (plus a small offset). This ensures a "risk-free" environment for the remainder of the trade.
Independent Stop Losses: The Scalp and the Runner use different SL distances to account for Nasdaq volatility, preventing a single "noise" wick from wiping out the entire position.
Intelligent Filters
ADX Range Filter: The strategy monitors market trend strength. It only allows trades when the ADX is below a user-defined threshold (default 25), ensuring you only play mean-reversion during ranging or "choppy" markets.
MA Visual Semaphor: The 50 EMA changes color dynamically based on ADX (Lime/Green for Range, Orange/Red for Trend), giving you an instant visual "Go/No-Go" signal.
Time-Session Filtering: Optimized for three custom sessions (NY Open, Mid-Day Reversal, and Late Night). Outside these sessions, the strategy can "Arm" setups in memory but will not "Fire" orders.
How to Use
Timeframe: Optimized for 1-Minute or 2-Minute charts for precision entry.
Asset: Nasdaq 100 (NQ, MNQ) or similar high-volatility indices.
Setup: * Enable Session Filters to avoid news volatility.
Adjust TP/SL in Points (1 Point = 4 Ticks) to suit your specific risk appetite.
Watch for the "Armados" labels—these indicate the system is ready and waiting for the Golden/Silver entry.
Visual Interface
Dynamic Boxes: Real-time visual representation of your TP1, TP2, and SL levels.
Activation Labels: Clear indications of when a Long or Short setup has been "Armed" in memory.
Status Dashboard: A clean top-right table showing current ADX values, Session status, and Risk settings.
Disclaimer
Trading involves significant risk. This strategy is a tool for decision support and backtesting. Past performance does not guarantee future results. Always test on a demo account before risking live capital.
BTC Pro High-Win Scalper w/ % Risk Hello,
I have been working on this 15min scalper for bitcoin. Its still in progress but is showing some promising results.
Check it out and let me know your thoughts
Thanks
