[Volume Profile] Signal Clean Up Analysis with Backtest (TSO) This is a full-cycle trading system indicator, which uses Volume Profile for generating signals using a custom developed algorithm, TP (Take Profit) and SL (Stop Loss) levels. There are 2 SOURCES for signals (each can be used separately or both can be used at the same time, each signal SOURCE is using Volume Profile levels to open optimal trade direction) with chained (NOTE: You can select several or ALL of the features, this is not limited to either one) signal cleanup and analysis approach with scheduling and alerting capabilities. Works with most popular timeframes: 1M, 5M, 15M, 1H, 4H, D, great for intraday trading!
NOTE: Every calculation is done on a confirmed closed candle bar state, so the indicator will never repaint!
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Explanation of all the Features | Configuration Guide | Indicator Settings | Signal Cleanup Analysis
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>>> Customizable Backtesting for a specific date range, results via TradingView strategy, which includes “Deep Backtesting” for largest amounts of data on trading results.
>>> Trading Schedule with customizable trading daily time range, automatic closing/alert trades before Power Hour or right before market closes or leave it open until next day.
>>> 3 Trading Systems.
>>> Multiple Signal SOURCEs for opening trades, either SOURCE can be used or both at the same time!
>>> Static/Dynamic Stop-Loss setups (HIGHLIGHT: Stop-Loss will be moved to Entry after TP1 is taken, which minimizes risk).
>>> Single or Multiple profit targets (up to 3).
>>> Take-Profit customizable offset feature (set your Take-Profit targets slightly before everyone is expecting it!).
>>> Candle bar signal analysis (matching candle color, skip opposite structured and/or doji candle uncertain signals).
>>> Additional analysis of VWAP/EMA/ATR/EWO (Elliot Wave Oscillator)/Divergence MACD+RSI/Volume signal confirmation (clean up your chart with indicator showing only the best potential signals!).
>>> Advanced Alerts setup, which can be potentially setup with a trading bot over TradingView Webhook (NOTE: This will require advanced programming knowledge).
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Labels, plots, colors explanations:
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>>>>> Signal SOURCE(s): Green/Red arrows, which will be shown unconditionally, outside of trade engine and can be hidden if desired.
>>>>> LONG open: green "house" looking arrow below candle bar.
>>>>> SHORT open: red "house" looking arrow above candle bar.
>>>>> LONG/SHORT take-profit target: green/red circles (multi-profit > TP2/3/4/5 smaller circles).
>>>>> LONG/SHORT take-profit hits: green/red diamonds.
>>>>> LONG/SHORT stop-loss target: green/red + crosses.
>>>>> LONG/SHORT stop-loss hits: green/red X-crosses.
>>>>> LONG/SHORT EOD close (profitable trade): green/red squares.
>>>>> LONG/SHORT EOD close (loss trade): green/red PLUS(+)-crosses.
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Date Range and Trading Schedule Settings
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>>>>> Date Range: Select your start and/or end dates (uncheck “End” for indicator to show results up to the very moment and to use for LIVE trading) for backtesting results, if not using backtesting – uncheck “Start”/“End” to turn it off.
>>>>> Use TradingView “Strategy Tester” to see backtesting results
NOTE: If Strategy Tester does not show any results with Date Ranged fully unchecked, there may be an issue where a script opens a trade, but there is not enough TradingView power to set the Take-Profit and Stop-Loss and somehow an open trade gets stuck and never closes, so there are “no trades present”. In such case you will need to manually check “Start”/“End” dates or use “Depp Backtesting” feature!
>>>>> Trading Schedule: This is where you can setup Intraday Session or any custom session schedule you wish. Turn it ON. Select trading hours. Select EOD (End of Day) setting (NOTE: If it will be OFF, the indicator will assume you are holding your position open until next day!).
>>> Trading Systems: 1) "Open Until Closed by TP or SL": the signal will only open a trade if no trades are currently open/trunning, a trade can only be closed by Take Profit, Stop Loss or End of Day close (if turned on) | 2) "Open Until Closed by TP or SL + OCA": Same as 1), but if there is an opposite signal to the trade which is currently open > it will immediately be closed with new trade open or End of Day close (if turned on) | 3) "OCA (no TP or SL)": There are is Take Profit or Stop Loss, only an opposite signal will close current trade and open an opposite one or End of Day close (if turned on)
>>>>> MULTIPROFIT | TP (Take-Profit) System: Once the trade is open, all Take-Profit target(s) are immediately calculated and set for the trade > once the target(s) is hit > trade will be partially closed (if candle bar closes beyond several Take-Profit targets > trade will be reduced accordingly to the amount of how many Take-Profit targets were hit)
>>>>> MULTIPROFIT | SL (Stop-Loss) System: 1) Static – Once the trade is open, Stop-Loss is calculated and set for the remaining of the trade ||| 2) Dynamic – At trade open, Stop-Loss is calculated and set the same way, however once 1st Take-Profit is taken > Stop-Loss is moved to Entry, reducing the risk.
>>>>> # of TPs (number of take profit targets): Just like it is named, this is where you select the number of Take-Profit targets for your trading system (NOTE: If "OCA (no TP or SL)" Trading System is selected, this setting won’t do anything, since there are no TP or SLs for that system).
>>>>> TP(s) offset: This is a special feature for all Take-Profit targets, where you can turn on a customizable offset, so that if the price is almost hitting the Take-Profit target, but never actually touches it > you will capture it. This is good to use with HHLL (Highest High Lowest Low), which is pretty much a Support/Resistance as often the price will nearly touch these strong areas and turn around…
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Take-Profit and Stop-Loss visual example:
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1) A simply nice intraday trading day for SPY (S&P500 ETF TRUST) with a single Take-Profit target on each trade.
See how Take-Profit distances increase with price momentum and how Stop-Loss is following the trade reducing the risk!
2) Same intraday trading day for SPY (S&P500 ETF TRUST) with 3 Take-Profit targets with static Stop-Loss.
3) Same intraday trading day for SPY (S&P500 ETF TRUST) with 3 Take-Profit targets with dynamic Stop-Loss.
You can see how Stop-Loss was moved once TP1 is taken!
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Trade Analysis and Cleanup Settings
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>>>>> Candle Analysis | Candle Color signal confirmation: If closed candle bar color does not match the signal direction > no trade will be open.
>>>>> Candle Analysis | Skip opposite candle signals: If closed candle bar color will match the signal direction, but candle structure will be opposite (for example: bearish green hammer, long high stick on top of a small green square) > no trade will be open.
>>>>> Candle Analysis | Skip doji candle signals: If closed candle bar will be the uncertain doji > no trade will be open.
>>>>> Divergence/Oscillator Analysis | EWO (Elliot Wave Oscillator) signal confirmation: LONG will only be open if at signal, EWO is green or will be at bullish slope (you can select which setting you desire), SHORT if EWO is red or will be at bearish slope.
>>>>> Divergence/Oscillator Analysis | VWAP signal confirmation: LONG will only be open if at signal, the price will be above VWAP, SHORT if below.
>>>>> Divergence/Oscillator Analysis | Moving Average signal confirmation: LONG will only be open if at signal, the price will be above selected Moving Average, SHORT if below.
>>>>> Divergence/Oscillator Analysis | ATR signal confirmation: LONG will only be open if at signal, the price will be above ATR, SHORT if below.
>>>>> Divergence/Oscillator Analysis | RSI + MACD signal confirmation: LONG will only be open if at signal, RSI + MACD will be bullish, SHORT if RSI + MACD will be bearish.
>>>>> Volume signal confirmation: LONG/SHORT will only be open if closing candle volume is 150% above average Volume based on the Volume Length.
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Alert Settings (you don’t have to touch this section unless you will be using TradingView alerts through a Webhook to use with trading bot)
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Here is how a LONG OPEN alert looks like (each label is customizable + I can add up more items/labels if needed):
COIN: BTCUSD
TIMEFRAME: 15M
LONG: OPEN
ENTRY: 20000
TP1: 20500
TP2: 21000
TP3: 21500
SL: 19000
Leverage: 0
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Adding Alerts in TradngView
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-Right-click anywhere on the TradingView chart
-Click on Add alert
-Condition: Select this indicator by it’s name
-Alert name: Whatever you want
-Hit “Create”
-Note: If you change ANY Settings within the indicator – you must DELETE the current alert and create a new one per steps above, otherwise it will continue triggering alerts per old Settings!
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If you have any questions or issues with the indicator, please message me directly via TradingView.
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Good Luck! (NOTE: Trading is very risky, past performance is not necessarily indicative of future results, so please trade responsibly!)
在腳本中搜尋"volume profile"
Liquidity Sweep Filter Strategy [AlgoAlpha X PineIndicators]This strategy is based on the Liquidity Sweep Filter developed by AlgoAlpha. Full credit for the concept and original indicator goes to AlgoAlpha.
The Liquidity Sweep Filter Strategy is a non-repainting trading system designed to identify liquidity sweeps, trend shifts, and high-impact price levels. It incorporates volume-based liquidation analysis, trend confirmation, and dynamic support/resistance detection to optimize trade entries and exits.
This strategy helps traders:
Detect liquidity sweeps where major market participants trigger stop losses and liquidations.
Identify trend shifts using a volatility-based moving average system.
Analyze volume distribution with a built-in volume profile visualization.
Filter noise by differentiating between major and minor liquidity sweeps.
How the Liquidity Sweep Filter Strategy Works
1. Trend Detection Using Volatility-Based Filtering
The strategy applies a volatility-adjusted moving average system to determine trend direction:
A central trend line is calculated using an EMA smoothed over a user-defined length.
Upper and lower deviation bands are created based on the average price deviation over multiple periods.
If price closes above the upper band, the strategy signals an uptrend.
If price closes below the lower band, the strategy signals a downtrend.
This approach ensures that trend shifts are confirmed only when price significantly moves beyond normal market fluctuations.
2. Liquidity Sweep Detection
Liquidity sweeps occur when price temporarily breaks key levels, triggering stop-loss liquidations or margin call events. The strategy tracks swing highs and lows, marking potential liquidity grabs:
Bearish Liquidity Sweeps – Price breaks a recent high, then reverses downward.
Bullish Liquidity Sweeps – Price breaks a recent low, then reverses upward.
Volume Integration – The strategy analyzes trading volume at each sweep to differentiate between major and minor sweeps.
Key levels where liquidity sweeps occur are plotted as color-coded horizontal lines:
Red lines indicate bearish liquidity sweeps.
Green lines indicate bullish liquidity sweeps.
Labels are displayed at each sweep, showing the volume of liquidated positions at that level.
3. Volume Profile Analysis
The strategy includes an optional volume profile visualization, displaying how trading volume is distributed across different price levels.
Features of the volume profile:
Point of Control (POC) – The price level with the highest traded volume is marked as a key area of interest.
Bounding Box – The profile is enclosed within a transparent box, helping traders visualize the price range of high trading activity.
Customizable Resolution & Scale – Traders can adjust the granularity of the profile to match their preferred time frame.
The volume profile helps identify zones of strong support and resistance, making it easier to anticipate price reactions at key levels.
Trade Entry & Exit Conditions
The strategy allows traders to configure trade direction:
Long Only – Only takes long trades.
Short Only – Only takes short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish trend shift is confirmed.
A bullish liquidity sweep occurs (price sweeps below a key level and reverses).
The trade direction setting allows long trades.
Short Entry:
A bearish trend shift is confirmed.
A bearish liquidity sweep occurs (price sweeps above a key level and reverses).
The trade direction setting allows short trades.
Exit Conditions
Closing a Long Position:
A bearish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Closing a Short Position:
A bullish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Customization Options
The strategy offers multiple adjustable settings:
Trade Mode: Choose between Long Only, Short Only, or Long & Short.
Trend Calculation Length & Multiplier: Adjust how trend signals are calculated.
Liquidity Sweep Sensitivity: Customize how aggressively the strategy identifies sweeps.
Volume Profile Display: Enable or disable the volume profile visualization.
Bounding Box & Scaling: Control the size and position of the volume profile.
Color Customization: Adjust colors for bullish and bearish signals.
Considerations & Limitations
Liquidity sweeps do not always result in reversals. Some price sweeps may continue in the same direction.
Works best in volatile markets. In low-volatility environments, liquidity sweeps may be less reliable.
Trend confirmation adds a slight delay. The strategy ensures valid signals, but this may result in slightly later entries.
Large volume imbalances may distort the volume profile. Adjusting the scale settings can help improve visualization.
Conclusion
The Liquidity Sweep Filter Strategy is a volume-integrated trading system that combines liquidity sweeps, trend analysis, and volume profile data to optimize trade execution.
By identifying key price levels where liquidations occur, this strategy provides valuable insight into market behavior, helping traders make better-informed trading decisions.
Key use cases for this strategy:
Liquidity-Based Trading – Capturing moves triggered by stop hunts and liquidations.
Volume Analysis – Using volume profile data to confirm high-activity price zones.
Trend Following – Entering trades based on confirmed trend shifts.
Support & Resistance Trading – Using liquidity sweep levels as dynamic price zones.
This strategy is fully customizable, allowing traders to adapt it to different market conditions, timeframes, and risk preferences.
Full credit for the original concept and indicator goes to AlgoAlpha.
TradeCreator Pro - Moving Averages, RSI, Volume, Trends, Levels█ Overview
TradeCreator Pro is designed to help you build successful trades by streamlining the processes of trade planning, evaluation, and execution. With a focus on data accuracy, speed, precision, and ease of use, this all-in-one tool assists in identifying optimal entry and exit points, calculating risk/reward ratios, and executing trades efficiently. Whether you’re a beginner or an experienced trader, TradeCreator Pro empowers you to make informed, data-driven decisions with real-time signals and fully customizable settings.
█ Key Benefits & Use Cases
TradeCreator Pro is designed to help you effortlessly discover profitable trades by evaluating and testing multiple setups across different assets and timeframes. Key use cases include:
Quick Strategy Testing: Rapidly test multiple setups and strategies, gaining immediate insights into their potential outcomes.
Risk/Reward Evaluation: Quickly identify which trade ideas are worth pursuing based on their profitability and associated risk.
Multi-Timeframe Testing: Seamlessly test the same trading setup across various timeframes and tickers.
Backtesting: Analyze the historical performance of specific setups to gauge their effectiveness.
Key Level Identification: Instantly spot critical support and resistance levels, improving your decision-making process.
Custom Alerts: Set personalized notifications for key levels, ensuring timely action on potential trade opportunities.
█ Core Features
Dashboard: A real-time view of critical metrics such as trend strength, support/resistance levels, volume profiles, RSI divergence, and trade scoring. Designed to provide a comprehensive snapshot of your trading environment and potential trading outcome.
Trend Analysis: Detect prevailing trends by analyzing multiple moving averages, support/resistance zones, volume profile and linear regressions for RSI and closing prices.
Support & Resistance Identification: Automatically identify support and resistance levels.
Volume Profile: Visualize volume profile and its point of control across support/resistance ranges, helping you spot key consolidation areas.
RSI & Price Divergence Detection: Identify potential divergences between RSI and price through linear regressions, providing valuable trade signals.
Risk Management Tools: Set equity loss levels based on specified leverage, allowing you to manage risk effectively for both long and short trades.
Entry & Exit Recommendations: Identify multiple options for optimal entry and exit levels based on current market conditions.
Trade Scoring: Score each trade setup on a 0-100 scale, factoring in potential ROI, ROE, P&L, and Risk-Reward Ratios to ensure high-quality trade execution.
Dynamic Execution & Monitoring: Benefit from multi-stage exit strategies, dynamic trailing stop losses, and the ability to backtest setups with historical data.
Alerts & Automation: Customize alerts for key market movements and opt for manual or automated trading through TradingView’s supported partners.
█ How to Use
Installation: Add TradeCreator Pro to your TradingView chart.
Trend Adjustment: The system automatically detects the current market trend, but you can fine-tune all trend detection parameters as needed.
Trading Parameter Configuration: Customize entry, exit, profitability, and risk-reward settings to match your trading style.
Entry and Exit Level Refinement: Use the automated suggestions, or choose from conceptual or arbitrary levels for greater control.
Stop Loss and Profit Target Fine-Tuning: Apply the system’s recommendations or adjust them by selecting from multiple available options.
Backtest Setup: Run the backtester to analyze past performance and assess how the strategy would have performed historically.
Set Alerts: Stay informed by setting alerts to notify you when a trade setup is triggered.
█ Notes
The first time you apply the indicator to a chart, it may take a few moments to compile. If it takes too long, switch timeframes temporarily to restart the process.
█ Risk Disclaimer
Trading in financial markets involves significant risk and is not suitable for all investors. The use of TradeCreator Pro, as well as any other tools provided by AlgoTrader Pro, is purely for informational and educational purposes. These tools are not intended to provide financial advice, and past performance is not indicative of future results. It is essential to do your own research, practice proper risk management, and consult with a licensed financial advisor before making any trading decisions. AlgoTrader Pro is not responsible for any financial losses you may incur through the use of these tools.
DVPOOverview
The DVPO (Dynamic Volume Profile Oscillator) Strategy is a comprehensive and highly customizable trading tool designed for precision and control. It is built around a unique, volume-driven oscillator that identifies potential market entries by analyzing the relationship between price, volume, and volatility.
This strategy is not just another signal generator; it's a complete framework that includes dynamic entry logic, adaptive risk management (ATR Stop Loss and R:R-based Take Profit), and a powerful dashboard of 10+ optional confirmation filters to help you tailor the strategy to your specific instrument, timeframe, and trading style.
The Core Concept: The DVPO Oscillator
The heart of this strategy is the DVPO oscillator. Unlike standard oscillators like RSI or Stochastics, the DVPO's primary goal is to quantify how far the current price has deviated from its recent volume-weighted "fair value."
Here’s how it works conceptually:
Micro Volume Profile: The indicator first analyzes a recent period of bars (defined by Lookback Period) to build a mini-profile of price and volume.
Volume-Weighted Mean: From this profile, it calculates a volume-weighted average price (VWAP) and the average deviation from that mean. This establishes the central point of value for the recent period.
Deviation Measurement: The oscillator's value is derived from how far the current price is from this calculated mean, scaled by the observed price deviation and a user-defined Sensitivity. A value above the midline suggests the price is trading at a premium, while a value below suggests it's at a discount.
Adaptive Volatility Zones: Instead of using fixed overbought/oversold levels (e.g., 70/30), the DVPO calculates dynamic upper and lower zones using the standard deviation of the oscillator itself. These zones expand and contract based on recent market volatility.
An entry signal is triggered not just when the oscillator is "overbought" or "oversold," but when it breaks out of these adaptive volatility zones, signaling that a statistically significant price movement is underway.
📈 Long Entry Condition : The oscillator crosses above the dynamic upper zone.
📉 Short Entry Condition : The oscillator crosses below the dynamic lower zone.
Integrated Risk & Trade Management
A signal is useless without proper risk management. This strategy has professional-grade risk management built directly into its logic.
Stop Loss (ATR-Based): The Stop Loss is not a fixed percentage. It is calculated using the Average True Range (ATR), allowing it to adapt automatically to the market's current volatility. In volatile periods, the stop will be wider; in quiet periods, it will be tighter.
Take Profit (Risk/Reward Ratio): The Take Profit level is calculated based on a user-defined Risk/Reward Ratio. If you set a ratio of 2.0, the Take Profit target will be placed at twice the distance of the Stop Loss from your entry price.
Dynamic Position Sizing: The strategy can automatically calculate the trade quantity for you. It determines the position size based on your specified Capital Size and the % Risk Per Trade you are willing to accept, ensuring disciplined risk control on every trade.
The Filter Dashboard : Enhance Your Signal Quality
To help reduce false signals and adapt to different market conditions, the strategy includes a comprehensive dashboard of optional confirmation filters. An entry signal will only be executed if it aligns with all the filters you have activated.
Trend & Momentum Filters :
T3, VMA, & VWAP Trend Filters: Utilize a suite of advanced moving averages (T3, Variable Moving Average, and a session-based VWAP) to ensure your trades are aligned with the dominant trend.
ADX Filter: Confirms that the market has sufficient directional strength for a trend-following trade, helping to avoid entries during choppy conditions.
Kaufman Efficiency Filter: Uses the Kaufman Efficiency Ratio to measure market noise. It only allows trades when the market is trending efficiently.
Volume & Market State Filters :
Volume Flow (VFI): A sophisticated volume-based filter that confirms whether volume is supporting the price move.
TDFI (Trader's Dynamic Index): A market state indicator designed to identify when the market is primed for a strong, directional move.
Flat Market Detector: A unique filter that identifies and avoids trading in sideways or ranging markets where trend strategies typically underperform.
Trade Condition Filters :
Min TP / Max SL %: Filter out trades where the risk/reward profile doesn't meet your minimum requirements (e.g., ignore a trade if the ATR-based stop loss is more than 10% away from the price).
Session Filters: Allows you to enable or disable trading on specific days of the week and to set a Cooldown Period (a set number of bars to wait after a trade closes before looking for a new entry).
How To Use This Strategy
Start with the Core: Begin by configuring the DVPO Oscillator settings (Lookback Period, Sensitivity, Zone Width) and your Risk Management parameters (ATR Multiplier, RR Ratio, % Risk Per Trade). These form the foundation of the strategy.
Backtest and Observe: Use TradingView's Strategy Tester to see how the core signals perform on your chosen asset and timeframe.
Layer Filters Intelligently: Enable the confirmation filters one by one and re-run your backtest. Observe how each filter impacts performance (e.g., does the T3 filter increase profitability but reduce the number of trades?). The goal is to find the optimal balance between signal quality and frequency.
Visualize and Analyze: Use the Show Risk/Reward Area option to plot your entry, stop loss, and take profit levels directly on the chart for every trade, providing a clear visual representation of your trade plan.
Disclaimer: This strategy is provided for educational and analytical purposes only. Past performance is not indicative of future results. All trading involves risk, and you should conduct your own thorough backtesting and analysis before deploying any strategy in a live market.
SigmaKernel - AdaptiveSigmaKernel - Adaptive Self-Optimizing Multi-Factor Trading System
SigmaKernel - Adaptive is a self-learning algorithmic trading strategy that combines four distinct analytical dimensions—momentum, market structure, volume flow, and reversal patterns—within a machine-learning-inspired framework that continuously adjusts its own parameters based on realized trading performance. Unlike traditional fixed-parameter strategies that maintain static weightings regardless of market conditions or results, this system implements a feedback loop that tracks which signal types, directional biases, and market conditions produce profitable outcomes, then mathematically adjusts component weightings, minimum score thresholds, position sizing multipliers, and trade spacing requirements to optimize future performance.
The strategy is designed for futures traders operating on prop firm accounts or live capital, incorporating realistic execution mechanics including configurable entry modes (stop breakout orders, limit pullback entries, or market-on-open), commission structures calibrated to retail futures contracts ($0.62 per contract default), one-tick slippage modeling, and professional risk controls including trailing drawdown guards, daily loss limits, and weekly profit targets. The system features universal futures compatibility—it automatically detects and adapts to any futures contract by reading the instrument's tick size and point value directly from the chart, eliminating the need for manual configuration across different markets.
What Makes This Approach Different
Adaptive Weight Optimization System
The core differentiation is the adaptive learning architecture. The strategy maintains four independent scoring components: momentum analysis (using RSI multi-timeframe, MACD histogram, and DMI/ADX), market structure detection (breakout identification via pivot-based support/resistance and moving average positioning), volume flow analysis (Volume Price Trend indicator with standard deviation confirmation), and reversal pattern recognition (oversold/overbought conditions combined with structural levels).
Each component generates a directional score that is multiplied by its current weight. After every closed trade, the system performs a retrospective analysis on the last N trades (configurable Learning Period, default 15 trades) to calculate win rates for each signal type independently. For example, if momentum-driven trades won 65% of the time while reversal trades won only 35%, the adaptive algorithm increases the momentum weight and decreases the reversal weight proportionally. The adjustment formula is:
New_Weight = Current_Weight + (Component_Win_Rate - Average_Win_Rate) × Adaptation_Speed
This creates a self-correcting mechanism where successful signal generators receive more influence in future composite scores, while underperforming components are de-emphasized. The system separately tracks long versus short win rates and applies directional bias corrections—if shorts consistently outperform longs, the strategy applies a 10% reduction to bullish signals to prevent fighting the prevailing market character.
Dynamic Parameter Adjustment
Beyond component weightings, three critical strategy parameters self-adjust based on performance:
Minimum Signal Score: The threshold required to trigger a trade. If overall win rate falls below 45%, the system increments this threshold by 0.10 per adjustment cycle, making the strategy more selective. If win rate exceeds 60%, the threshold decreases to allow more opportunities. This prevents the strategy from overtrading during unfavorable conditions and capitalizes on high-probability environments.
Risk Multiplier: Controls position sizing aggression. When drawdown exceeds 5%, risk per trade reduces by 10% per cycle. When drawdown falls below 2%, risk increases by 5% per cycle. This implements the professional risk management principle of "bet small when losing, bet bigger when winning" algorithmically.
Bars Between Trades: Spacing filter to prevent overtrading. Base value (default 9 bars) multiplies by drawdown factor and losing streak factor. During drawdown or consecutive losses, spacing expands up to 2x to allow market conditions to change before re-entering.
All adaptation operates during live forward-testing or real trading—there is no in-sample optimization applied to historical data. The system learns solely from its own realized trades.
Universal Futures Compatibility
The strategy implements universal futures instrument detection that automatically adapts to any futures contract without requiring manual configuration. Instead of hardcoding specific contract specifications, the system reads three critical values directly from TradingView's symbol information:
Tick Size Detection: Uses `syminfo.mintick` to obtain the minimum price increment for the current instrument. This value varies widely across markets—ES trades in 0.25 ticks, crude oil (CL) in 0.01 ticks, gold (GC) in 0.10 ticks, and treasury futures (ZB) in increments of 1/32nds. The strategy adapts all entry buffer calculations and stop placement logic to the detected tick size.
Point Value Detection: Uses `syminfo.pointvalue` to determine the dollar value per full point of price movement. For ES, one point equals $50; for crude oil, one point equals $1,000; for gold, one point equals $100. This automatic detection ensures accurate P&L calculations and risk-per-contract measurements across all instruments.
Tick Value Calculation: Combines tick size and point value to compute dollar value per tick: Tick_Value = Tick_Size × Point_Value. This derived value drives all position sizing calculations, ensuring the risk management system correctly accounts for each instrument's economic characteristics.
This universal approach means the strategy functions identically on emini indices (ES, MES, NQ, MNQ), micro indices, energy contracts (CL, NG, RB), metals (GC, SI, HG), agricultural futures (ZC, ZS, ZW), treasury futures (ZB, ZN, ZF), currency futures (6E, 6J, 6B), and any other futures contract available on TradingView. No parameter adjustments or instrument-specific branches exist in the code—the adaptation happens automatically through symbol information queries.
Stop-Out Rate Monitoring System
The strategy includes an intelligent stop-out rate tracking system that monitors the percentage of your last 20 trades (or available trades if fewer than 20) that were stopped out. This metric appears in the dashboard's Performance section with color-coded guidance:
Green (<30% stop-out rate): Very few trades are being stopped out. This suggests either your stops are too loose (giving back profits on reversals) or you're in an exceptional trending market. Consider tightening your Stop Loss ATR multiplier to lock in profits more efficiently.
Orange (30-65% stop-out rate): Healthy range. Your stop placement is appropriately sized for current market conditions and the strategy's risk-reward profile. No adjustment needed.
Red (>65% stop-out rate): Too many trades are being stopped out prematurely. Your stops are likely too tight for the current volatility regime. Consider widening your Stop Loss ATR multiplier to give trades more room to develop.
Critical Design Philosophy: Unlike some systems that automatically adjust stops based on performance statistics, this strategy intentionally keeps stop-loss control in the user's hands. Automatic stop adjustment creates dangerous feedback loops—widening stops increases risk per contract, which forces position size reduction, which distorts performance metrics, leading to incorrect adaptations. Instead, the dashboard provides visibility into stop performance, empowering you to make informed manual adjustments when warranted. This preserves the integrity of the adaptive system while giving you the critical data needed for stop optimization.
Execution Kernel Architecture
The entry system offers three distinct execution modes to match trader preference and market character:
StopBreakout Mode: Places buy-stop orders above the prior bar's high (for longs) or sell-stop orders below the prior bar's low (for shorts), plus a 2-tick buffer. This ensures entries only occur when price confirms directional momentum by breaking recent structure. Ideal for trending and momentum-driven markets.
LimitPullback Mode: Places limit orders at a pullback price calculated as: Entry_Price = Close - (ATR × Pullback_Multiplier) for longs, or Close + (ATR × Pullback_Multiplier) for shorts. Default multiplier is 0.5 ATR. This waits for mean-reversion before entering in the signal direction, capturing better prices in volatile or oscillating markets.
MarketNextOpen Mode: Executes at market on the bar immediately following signal generation. This provides fastest execution but sacrifices the filtering effect of requiring price confirmation.
All pending entry orders include a configurable Time-To-Live (TTL, default 6 bars). If an order is not filled within the TTL period, it cancels automatically to prevent stale signals from executing in changed market conditions.
Professional Exit Management
The exit system implements a three-stage progression: initial stop loss, breakeven adjustment, and dynamic trailing stop.
Initial Stop Loss: Calculated as entry price ± (ATR × User_Stop_Multiplier × Volatility_Adjustment). Users have direct control via the Stop Loss ATR multiplier (default 1.25). The system then applies volatility regime adjustments: ×1.2 in high-volatility environments (stops automatically widen), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. This ensures stops adapt to market character while maintaining user control over baseline risk tolerance.
Breakeven Trigger: When profit reaches a configurable multiple of initial risk (default 1.0R), the stop loss automatically moves to breakeven (entry price). This locks in zero-loss status once the trade demonstrates favorable movement.
Trailing Stop Activation: When profit reaches the Trail_Trigger_R multiple (default 1.2R), the system cancels the fixed stop and activates a dynamic trailing stop. The trail uses Step and Offset parameters defined in R-multiples. For example, with Trail_Offset_R = 1.0 and Trail_Step_R = 1.5, the stop trails 1.0R behind price and moves in 1.5R increments. This captures extended moves while protecting accumulated profit.
Additional failsafes include maximum time-in-trade (exits after N bars if specified) and end-of-session flatten (automatically closes all positions X minutes before session end to avoid overnight exposure).
Core Calculation Methodology
Signal Component Scoring
Momentum Component:
- Calculates 14-period DMI (Directional Movement Index) with ADX strength filter (trending when ADX > 25)
- Computes three RSI timeframes: fast (7-period), medium (14-period), slow (21-period)
- Analyzes MACD (12/26/9) histogram for directional acceleration
- Bullish momentum: uptrend (DI+ > DI- with ADX > 25) + MACD histogram rising above zero + RSI fast between 50-80 = +1.6 score
- Bearish momentum: downtrend (DI- > DI+ with ADX > 25) + MACD histogram falling below zero + RSI fast between 20-50 = -1.6 score
- Score multiplies by volatility adjustment factor: ×0.8 in high volatility (momentum less reliable), ×1.2 in low volatility (momentum more persistent)
Structure Component:
- Identifies swing highs and lows using 10-bar pivot lookback on both sides
- Maintains most recent swing high as dynamic resistance, most recent swing low as dynamic support
- Detects breakouts: bullish when close crosses above resistance with prior bar below; bearish when close crosses below support with prior bar above
- Breakout score: ±1.0 for confirmed break
- Moving average alignment: +0.5 when price > SMA20 > SMA50 (bullish structure); -0.5 when price < SMA20 < SMA50 (bearish structure)
- Total structure range: -1.5 to +1.5
Volume Component:
- Calculates Volume Price Trend: VPT = Σ [(Close - Close ) / Close × Volume]
- Compares VPT to its 10-period EMA as signal line (similar to MACD logic)
- Computes 20-period volume moving average and standard deviation
- High volume event: current volume > (volume_average + 1× std_dev)
- Bullish volume: VPT > VPT_signal AND high_volume = +1.0
- Bearish volume: VPT < VPT_signal AND high_volume = -1.0
- No score if volume is not elevated (filters out low-conviction moves)
Reversal Component:
- Identifies extreme RSI conditions: RSI slow < 30 (oversold) or > 70 (overbought)
- Requires structural confluence: price at or below support level for bullish reversal; at or above resistance for bearish reversal
- Requires momentum shift: RSI fast must be rising (for bull) or falling (for bear) to confirm reversal in progress
- Bullish reversal: RSI < 30 AND price ≤ support AND RSI rising = +1.0
- Bearish reversal: RSI > 70 AND price ≥ resistance AND RSI falling = -1.0
Composite Score Calculation
Final_Score = (Momentum × Weight_M) + (Structure × Weight_S) + (Volume × Weight_V) + (Reversal × Weight_R)
Initial weights: Momentum = 1.0, Structure = 1.2, Volume = 0.8, Reversal = 0.6
These weights adapt after each trade based on component-specific performance as described above.
The system also applies directional bias adjustment: if recent long trades have significantly lower win rate than shorts, bullish scores multiply by 0.9 to reduce aggressive long entries. Vice versa for underperforming shorts.
Position Sizing Algorithm
The position sizing calculation incorporates multiple confidence factors and automatically scales to any futures contract:
1. Base risk amount = Account_Size × Base_Risk_Percent × Adaptive_Risk_Multiplier
2. Stop distance in price units = ATR × User_Stop_Multiplier × Volatility_Regime_Multiplier × Entry_Buffer
3. Risk per contract = Stop_Distance × Dollar_Per_Point (automatically detected from instrument)
4. Raw position size = Risk_Amount / Risk_Per_Contract
Then applies confidence scaling:
- Signal confidence = min(|Weighted_Score| / Min_Score_Threshold, 2.0) — higher scores receive larger size, capped at 2×
- Direction confidence = Long_Win_Rate (for bulls) or Short_Win_Rate (for bears)
- Type confidence = Win_Rate of dominant signal type (momentum/structure/volume/reversal)
- Total confidence = (Signal_Confidence + Direction_Confidence + Type_Confidence) / 3
Adjusted size = Raw_Size × Total_Confidence × Losing_Streak_Reduction
Losing streak reduction = 0.5 if losing_streak ≥ 5, otherwise 1.0
Universal Maximum Position Calculation: Instead of hardcoded limits per instrument, the system calculates maximum position size as: Max_Contracts = Account_Size / 25000, clamped between 1 and 10 contracts. This means a $50,000 account allows up to 2 contracts, a $100,000 account allows up to 4 contracts, regardless of which futures contract is being traded. This universal approach maintains consistent risk exposure across different instruments while preventing overleveraging.
Final size is rounded to integer and bounded by the calculated maximum.
Session and Risk Management System
Timezone-Aware Session Control
The strategy implements timezone-correct session filtering. Users specify session start hour, end hour, and timezone from 12 supported zones (New York, Chicago, Los Angeles, London, Frankfurt, Moscow, Tokyo, Hong Kong, Shanghai, Singapore, Sydney, UTC). The system converts bar timestamps to the selected timezone before applying session logic.
For split sessions (e.g., Asian session 18:00-02:00), the logic correctly handles time wraparound. Weekend trading can be optionally disabled (default: disabled) to avoid low-liquidity weekend price action.
Multi-Layer Risk Controls
Daily Loss Limit: Strategy ceases all new entries when daily P&L reaches negative threshold (default $2,000). This prevents catastrophic drawdown days. Resets at timezone-corrected day boundary.
Weekly Profit Target: Strategy ceases trading when weekly profit reaches target (default $10,000). This implements the professional principle of "take the win and stop pushing luck." Resets on timezone-corrected Monday.
Maximum Daily Trades: Hard cap on entries per day (default 20) to prevent overtrading during volatile conditions when many signals may generate.
Trailing Drawdown Guard: Optional prop-firm-style trailing stop on account equity. When enabled, if equity drops below (Peak_Equity - Trailing_DD_Amount), all trading halts. This simulates the common prop firm rule where exceeding trailing drawdown results in account termination.
All limits display status in the real-time dashboard, showing "MAX LOSS HIT", "WEEKLY TARGET MET", or "ACTIVE" depending on current state.
How To Use This Strategy
Initial Setup
1. Apply the strategy to your desired futures chart (tested on 5-minute through daily timeframes)
2. The strategy will automatically detect your instrument's specifications—no manual configuration needed for different contracts
3. Configure your account size and risk parameters in the Core Settings section
4. Set your trading session hours and timezone to match your availability
5. Adjust the Stop Loss ATR multiplier based on your risk tolerance (0.8-1.2 for tighter stops, 1.5-2.5 for wider stops)
6. Select your preferred entry execution mode (recommend StopBreakout for beginners)
7. Enable adaptation (recommended) or disable for fixed-parameter operation
8. Review the strategy's Properties in the Strategy Tester settings and verify commission/slippage match your broker's actual costs
The universal futures detection means you can switch between ES, NQ, CL, GC, ZB, or any other futures contract without changing any strategy parameters—the system will automatically adapt its calculations to each instrument's unique specifications.
Dashboard Interpretation
The strategy displays a comprehensive real-time dashboard in the top-right corner showing:
Market State Section:
- Trend: Shows UPTREND/DOWNTREND/CONSOLIDATING/NEUTRAL based on ADX and DMI analysis
- ADX Value: Current trend strength (>25 = strong trend, <20 = consolidating)
- Momentum: BULL/BEAR/NEUTRAL classification with current momentum score
- Volatility: HIGH/LOW/NORMAL regime with ATR percentage of price
Volume Profile Section (Large dashboard only):
- VPT Flow: Directional bias from volume analysis
- Volume Status: HIGH/LOW/NORMAL with relative volume multiplier
Performance Section:
- Daily P&L: Current day's profit/loss with color coding
- Daily Trades: Number of completed trades today
- Weekly P&L: Current week's profit/loss
- Target %: Progress toward weekly profit target
- Stop-Out Rate: Percentage of last 20 trades (or available trades if <20) that were stopped out. Includes all stop types: initial stops, breakeven stops, trailing stops, timeout exits, and EOD flattens. Color coded with actionable guidance:
- Green (<30%): Shows "TIGHTEN" guidance. Very few stop-outs suggests stops may be too loose or exceptional market conditions. Consider reducing Stop Loss ATR multiplier.
- Orange (30-65%): Shows "OK" guidance. Healthy stop-out rate indicating appropriate stop placement for current conditions.
- Red (>65%): Shows "WIDEN" guidance. Too many premature stop-outs. Consider increasing Stop Loss ATR multiplier to give trades more room.
- Status: Overall trading status (ACTIVE/MAX LOSS HIT/WEEKLY TARGET MET/FILTERS ACTIVE)
Adaptive Engine Section:
- Min Score: Current minimum threshold for trade entry (higher = more selective)
- Risk Mult: Current position sizing multiplier (adjusts with performance)
- Bars BTW: Current minimum bars required between trades
- Drawdown: Current drawdown percentage from equity peak
- Weights: M/S/V/R showing current component weightings
Win Rates Section:
- Type: Win rates for Momentum, Structure, Volume, Reversal signal types
- Direction: Win rates for Long vs Short trades
Color coding shows green for >50% win rate, red for <50%
Session Info Section:
- Session Hours: Active trading window with timezone
- Weekend Trading: ENABLED/DISABLED status
- Session Status: ACTIVE/INACTIVE based on current time
Signal Generation and Entry
The strategy generates entries when the weighted composite score exceeds the adaptive minimum threshold (initial value configurable, typically 1.5 to 2.5). Entries display as layered triangle markers on the chart:
- Long Signal: Three green upward triangles below the entry bar
- Short Signal: Three red downward triangles above the entry bar
Triangle tooltip shows the signal score and dominant signal type (MOMENTUM/STRUCTURE/VOLUME/REVERSAL).
Position Management and Stop Optimization
Once entered, the strategy automatically manages the position through its three-stage exit system. Monitor the Stop-Out Rate metric in the dashboard to optimize your stop placement:
If Stop-Out Rate is Green (<30%): You're rarely being stopped out. This could mean:
- Your stops are too loose, allowing trades to give back too much profit on reversals
- You're in an exceptional trending market where tight stops would work better
- Action: Consider reducing your Stop Loss ATR multiplier by 0.1-0.2 to tighten stops and lock in profits more efficiently
If Stop-Out Rate is Orange (30-65%): Optimal range. Your stops are appropriately sized for the strategy's risk-reward profile and current market volatility. No adjustment needed.
If Stop-Out Rate is Red (>65%): You're being stopped out too frequently. This means:
- Your stops are too tight for current market volatility
- Trades need more room to develop before reaching profit targets
- Action: Increase your Stop Loss ATR multiplier by 0.1-0.3 to give trades more breathing room
Remember: The stop-out rate calculation includes all exit types (initial stops, breakeven stops, trailing stops, timeouts, EOD flattens). A trade that reaches breakeven and gets stopped out at entry price counts as a stop-out, even though it didn't lose money. This is intentional—it indicates the stop placement didn't allow the trade to develop into profit.
Optimization Workflow
For traders wanting to customize the strategy for their specific instrument and timeframe:
Week 1-2: Run with defaults, adaptation enabled
Allow the system to execute at least 30-50 trades (the Learning Period plus additional buffer). Monitor which session periods, signal types, and market conditions produce the best results. Observe your stop-out rate—if it's consistently red or green, plan to adjust Stop Loss ATR multiplier after the learning period. Do not adjust parameters yet—let the adaptive system establish baseline performance data.
Week 3-4: Analyze adaptation behavior and optimize stops
Review the dashboard's adaptive weights and win rates. If certain signal types consistently show <40% win rate, consider slightly reducing their base weight. If a particular entry mode produces better fill quality and win rate, switch to that mode. If you notice the minimum score threshold has climbed very high (>3.0), market conditions may not suit the strategy's logic—consider switching instruments or timeframes.
Based on your Stop-Out Rate observations:
- Consistently <30%: Reduce Stop Loss ATR multiplier by 0.2-0.3
- Consistently >65%: Increase Stop Loss ATR multiplier by 0.2-0.4
- Oscillating between zones: Leave stops at default and let volatility regime adjustments handle it
Ongoing: Fine-tune risk and execution
Adjust the following based on your risk tolerance and account type:
- Base Risk Per Trade: 0.5% for conservative, 0.75% for moderate, 1.0% for aggressive
- Stop Loss ATR Multiplier: 0.8-1.2 for tight stops (scalping), 1.5-2.5 for wide stops (swing trading)
- Bars Between Trades: Lower (5-7) for more opportunities, higher (12-20) for more selective
- Entry Mode: Experiment between modes to find best fit for current market character
- Session Hours: Narrow to specific high-performance session windows if certain hours consistently underperform
Never adjust: Do not manually modify the adaptive weights, minimum score, or risk multiplier after the system has begun learning. These parameters are self-optimizing and manual interference defeats the adaptive mechanism.
Parameter Descriptions and Optimization Guidelines
Adaptive Intelligence Group
Enable Self-Optimization (default: true): Master switch for the adaptive learning system. When enabled, component weights, minimum score, risk multiplier, and trade spacing adjust based on realized performance. Disable to run the strategy with fixed parameters (useful for comparing adaptive vs non-adaptive performance).
Learning Period (default: 15 trades): Number of most recent trades to analyze for performance calculations. Shorter values (10-12) adapt more quickly to recent conditions but may overreact to variance. Longer values (20-30) produce more stable adaptations but respond slower to regime changes. For volatile markets, use shorter periods. For stable trends, use longer periods.
Adaptation Speed (default: 0.25): Controls the magnitude of parameter adjustments per learning cycle. Lower values (0.05-0.15) make gradual, conservative changes. Higher values (0.35-0.50) make aggressive adjustments. Faster adaptation helps in rapidly changing markets but increases parameter instability. Start with default and increase only if you observe the system failing to adapt quickly enough to obvious performance patterns.
Performance Memory (default: 100 trades): Maximum number of historical trades stored for analysis. This array size does not affect learning (which uses only Learning Period trades) but provides data for future analytics features including stop-out rate tracking. Higher values consume more memory but provide richer historical dataset. Typical users should not need to modify this.
Core Settings Group
Account Size (default: $50,000): Starting capital for position sizing calculations. This should match your actual account size for accurate risk per trade. The strategy uses this value to calculate dollar risk amounts and determine maximum position size (1 contract per $25,000).
Weekly Profit Target (default: $10,000): When weekly P&L reaches this value, the strategy stops taking new trades for the remainder of the week. This implements a "quit while ahead" rule common in professional trading. Set to a realistic weekly goal—20% of account size per week ($10K on $50K) is very aggressive; 5-10% is more sustainable.
Max Daily Loss (default: $2,000): When daily P&L reaches this negative threshold, strategy stops all new entries for the day. This is your maximum acceptable daily loss. Professional traders typically set this at 2-4% of account size. A $2,000 loss on a $50,000 account = 4%.
Base Risk Per Trade % (default: 0.5%): Initial percentage of account to risk on each trade before adaptive multiplier and confidence scaling. 0.5% is conservative, 0.75% is moderate, 1.0-1.5% is aggressive. Remember that actual risk per trade = Base Risk × Adaptive Risk Multiplier × Confidence Factors, so the realized risk will vary.
Trade Filters Group
Base Minimum Signal Score (default: 1.5): Initial threshold that composite weighted score must exceed to generate a signal. Lower values (1.0-1.5) produce more trades with lower average quality. Higher values (2.0-3.0) produce fewer, higher-quality setups. This value adapts automatically when adaptive mode is enabled, but the base sets the starting point. For trending markets, lower values work well. For choppy markets, use higher values.
Base Bars Between Trades (default: 9): Minimum bars that must elapse after an entry before another signal can trigger. This prevents overtrading and allows previous trades time to develop. Lower values (3-6) suit scalping on lower timeframes. Higher values (15-30) suit swing trading on higher timeframes. This value also adapts based on drawdown and losing streaks.
Max Daily Trades (default: 20): Hard limit on total trades per day regardless of signal quality. This prevents runaway trading during extremely volatile days when many signals may generate. For 5-minute charts, 20 trades/day is reasonable. For 1-hour charts, 5-10 trades/day is more typical.
Session Group
Session Start Hour (default: 5): Hour (0-23 format) when trading is allowed to begin, in the timezone specified. For US futures trading in Chicago time, session typically starts at 5:00 or 6:00 PM (17:00 or 18:00) Sunday evening.
Session End Hour (default: 17): Hour when trading stops and no new entries are allowed. For US equity index futures, regular session ends at 4:00 PM (16:00) Central Time.
Allow Weekend Trading (default: false): Whether strategy can trade on Saturday/Sunday. Most futures have low volume on weekends; keeping this disabled is recommended unless you specifically trade Sunday evening open.
Session Timezone (default: America/Chicago): Timezone for session hour interpretation. Select your local timezone or the timezone of your instrument's primary exchange. This ensures session logic aligns with your intended trading hours.
Prop Guards Group
Trailing Drawdown Guard (default: false): Enables prop-firm-style trailing maximum drawdown. When enabled, if equity drops below (Peak Equity - Trailing DD Amount), all trading halts for the remainder of the backtest/live session. This simulates rules used by funded trader programs where exceeding trailing drawdown terminates the account.
Trailing DD Amount (default: $2,500): Dollar amount of drawdown allowed from equity peak. If your equity reaches $55,000, the trailing stop sets at $52,500. If equity then drops to $52,499, the guard triggers and trading ceases.
Execution Kernel Group
Entry Mode (default: StopBreakout):
- StopBreakout: Places stop orders above/below signal bar requiring price confirmation
- LimitPullback: Places limit orders at pullback prices seeking better fills
- MarketNextOpen: Executes immediately at market on next bar
Limit Offset (default: 0.5x ATR): For LimitPullback mode, how far below/above current price to place the limit order. Smaller values (0.3-0.5) seek minor pullbacks. Larger values (0.8-1.2) wait for deeper retracements but may miss trades.
Entry TTL (default: 6 bars, 0=off): Bars an entry order remains pending before cancelling. Shorter values (3-4) keep signals fresh. Longer values (8-12) allow more time for fills but risk executing stale signals. Set to 0 to disable TTL (orders remain active indefinitely until filled or opposite signal).
Exits Group
Stop Loss (default: 1.25x ATR): Base stop distance as a multiple of the 14-period ATR. This is your primary risk control parameter and directly impacts your stop-out rate. Lower values (0.8-1.0) create tighter stops that reduce risk per trade but may get stopped out prematurely in volatile conditions—expect stop-out rates above 65% (red zone). Higher values (1.5-2.5) give trades more room to breathe but increase risk per contract—expect stop-out rates below 30% (green zone). The system applies additional volatility regime adjustments on top of this base: ×1.2 in high volatility environments (stops widen automatically), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. For scalping on lower timeframes, use 0.8-1.2. For swing trading on higher timeframes, use 1.5-2.5. Monitor the Stop-Out Rate metric in the dashboard and adjust this parameter to keep it in the healthy 30-65% orange zone.
Move to Breakeven at (default: 1.0R): When profit reaches this multiple of initial risk, stop moves to breakeven. 1.0R means after price moves in your favor by the distance you risked, you're protected at entry price. Lower values (0.5-0.8R) lock in breakeven faster. Higher values (1.5-2.0R) allow more room before protection.
Start Trailing at (default: 1.2R): When profit reaches this multiple, the fixed stop transitions to a dynamic trailing stop. This should be greater than the BE trigger. Values typically range 1.0-2.0R depending on how much profit you want secured before trailing activates.
Trail Offset (default: 1.0R): How far behind price the trailing stop follows. Tighter offsets (0.5-0.8R) protect profit more aggressively but may exit prematurely. Wider offsets (1.5-2.5R) allow more room for profit to run but risk giving back more on reversals.
Trail Step (default: 1.5R): How far price must move in profitable direction before the stop advances. Smaller steps (0.5-1.0R) move the stop more frequently, tightening protection continuously. Larger steps (2.0-3.0R) move the stop less often, giving trades more breathing room.
Max Bars In Trade (default: 0=off): Maximum bars allowed in a position before forced exit. This prevents trades from "going stale" during periods of no meaningful price action. For 5-minute charts, 50-100 bars (4-8 hours) is reasonable. For daily charts, 5-10 bars (1-2 weeks) is typical. Set to 0 to disable.
Flatten near Session End (default: true): Whether to automatically close all positions as session end approaches. Recommended to avoid carrying positions into off-hours with low liquidity.
Minutes before end (default: 5): How many minutes before session end to flatten. 5-15 minutes provides buffer for order execution before the session boundary.
Visual Effects Configuration Group
Dashboard Size (default: Normal): Controls information density in the dashboard. Small shows only critical metrics (excludes stop-out rate). Normal shows comprehensive data including stop-out rate. Large shows all available metrics including weights, session info, and volume analysis. Larger sizes consume more screen space but provide complete visibility.
Show Quantum Field (default: true): Displays animated grid pattern on the chart indicating market state. Disable if you prefer cleaner charts or experience performance issues on lower-end hardware.
Show Wick Pressure Lines (default: true): Draws dynamic lines from bars with extreme wicks, indicating potential support/resistance or liquidity absorption zones. Disable for simpler visualization.
Show Morphism Energy Beams (default: true): Displays directional beams showing momentum energy flow. Beams intensify during strong trends. Disable if you find this visually distracting.
Show Order Flow Clouds (default: true): Draws translucent boxes representing volume flow bullish/bearish bias. Disable for cleaner price action visibility.
Show Fractal Grid (default: true): Displays multi-timeframe support/resistance levels based on fractal price structure at 10/20/30/40/50 bar periods. Disable if you only want to see primary pivot levels.
Glow Intensity (default: 4): Controls the brightness and thickness of visual effects. Lower values (1-2) for subtle visualization. Higher values (7-10) for maximum visibility but potentially cluttered charts.
Color Theme (default: Cyber): Visual color scheme. Cyber uses cyan/magenta futuristic colors. Quantum uses aqua/purple. Matrix uses green/red terminal style. Aurora uses pastel pink/purple gradient. Choose based on personal preference and monitor calibration.
Show Watermark (default: true): Displays animated watermark at bottom of chart with creator credit and current P&L. Disable if you want completely clean charts or need screen space.
Performance Characteristics and Best Use Cases
Optimal Conditions
This strategy performs best in markets exhibiting:
Trending phases with periodic pullbacks: The combination of momentum and structure components excels when price establishes directional bias but provides retracement opportunities for entries. Markets with 60-70% trending bars and 30-40% consolidation produce the highest win rates.
Medium to high volatility: The ATR-based stop sizing and dynamic risk adjustment require sufficient price movement to generate meaningful profit relative to risk. Instruments with 2-4% daily ATR relative to price work well. Extremely low volatility (<1% daily ATR) generates too many scratch trades.
Clear volume patterns: The VPT volume component adds significant edge when volume expansions align with directional moves. Instruments and timeframes where volume data reflects actual transaction flow (versus tick volume proxies) perform better.
Regular session structure: Futures markets with defined opening and closing hours, consistent liquidity throughout the session, and clear overnight/day session separation allow the session controls and time-based failsafes to function optimally.
Sufficient liquidity for stop execution: The stop breakout entry mode requires that stop orders can fill without significant slippage. Highly liquid contracts work better than illiquid instruments where stop orders may face adverse fills.
Suboptimal Conditions
The strategy may struggle with:
Extreme chop with no directional persistence: When ADX remains below 15 for extended periods and price oscillates rapidly without establishing trends, the momentum component generates conflicting signals. Win rate typically drops below 40% in these conditions, triggering the adaptive system to increase minimum score thresholds until conditions improve. Stop-out rates may also spike into the red zone.
Gap-heavy instruments: Markets with frequent overnight gaps disrupt the continuous price assumptions underlying ATR stops and EMA-based structure analysis. Gaps can also cause stop orders to fill at prices far from intended levels, distorting stop-out rate metrics.
Very low timeframes with excessive noise: On 1-minute or tick charts, the signal components react to micro-structure noise rather than meaningful price swings. The strategy works best on 5-minute through daily timeframes where price movements reflect actual order flow shifts.
Extended low-volatility compression: During historically low volatility periods, profit targets become difficult to reach before mean-reversion occurs. The trail offset, even when set to minimum, may be too wide for the compressed price environment. Stop-out rates may drop to green zone indicating stops should be tightened.
Parabolic moves or climactic exhaustion: Vertical price advances or selloffs where price moves multiple ATRs in single bars can trigger momentum signals at exhaustion points. The structure and reversal components attempt to filter these, but extreme moves may override normal logic.
The adaptive learning system naturally reduces signal frequency and position sizing during unfavorable conditions. If you observe multiple consecutive days with zero trades and "FILTERS ACTIVE" status, this indicates the strategy has self-adjusted to avoid poor conditions rather than forcing trades.
Instrument Recommendations
Emini Index Futures (ES, MES, NQ, MNQ, YM, RTY): Excellent fit. High liquidity, clear volatility patterns, strong volume signals, defined session structure. These instruments have been extensively tested and the universal detection handles all contract specifications automatically.
Micro Index Futures (MES, MNQ, M2K, MYM): Excellent fit for smaller accounts. Same market characteristics as the standard eminis but with reduced contract sizes allowing proper risk management on accounts below $50,000.
Energy Futures (CL, NG, RB, HO): Good to mixed fit. Crude oil (CL) works well due to strong trends and reasonable volatility. Natural gas (NG) can be extremely volatile—consider reducing Base Risk to 0.3-0.4% and increasing Stop Loss ATR multiplier to 1.8-2.2 for NG. The strategy automatically detects the $10/tick value for CL and adjusts position sizing accordingly.
Metal Futures (GC, SI, HG, PL): Good fit. Gold (GC) and silver (SI) exhibit clear trending behavior and work well with the momentum/structure components. The strategy automatically handles the different point values ($100/point for gold, $5,000/point for silver).
Agricultural Futures (ZC, ZS, ZW, ZL): Good fit. Grain futures often trend strongly during seasonal periods. The strategy handles the unique tick sizes (1/4 cent increments) and point values ($50/point for corn/wheat, $60/point for soybeans) automatically.
Treasury Futures (ZB, ZN, ZF, ZT): Good fit for trending rates environments. The strategy automatically handles the fractional tick sizing (32nds for ZB/ZN, halves of 32nds for ZF/ZT) through the universal detection system.
Currency Futures (6E, 6J, 6B, 6A, 6C): Good fit. Major currency pairs exhibit smooth trending behavior. The strategy automatically detects point values which vary significantly ($12.50/tick for 6E, $12.50/tick for 6J, $6.25/tick for 6B).
Cryptocurrency Futures (BTC, ETH, MBT, MET): Mixed fit. These markets have extreme volatility requiring parameter adjustment. Increase Base Risk to 0.8-1.2% and Stop Loss ATR multiplier to 2.0-3.0 to account for wider stop distances. Enable 24-hour trading and weekend trading as these markets have no traditional sessions.
The universal futures compatibility means you can apply this strategy to any of these markets without code modification—simply open the chart of your desired contract and the strategy will automatically configure itself to that instrument's specifications.
Important Disclaimers and Realistic Expectations
This is a sophisticated trading strategy that combines multiple analytical methods within an adaptive framework designed for active traders who will monitor performance and market conditions. It is not a "set and forget" fully automated system, nor should it be treated as a guaranteed profit generator.
Backtesting Realism and Limitations
The strategy includes realistic trading costs and execution assumptions:
- Commission: $0.62 per contract per side (accurate for many retail futures brokers)
- Slippage: 1 tick per entry and exit (conservative estimate for liquid futures)
- Position sizing: Realistic risk percentages and maximum contract limits based on account size
- No repainting: All calculations use confirmed bar data only—signals do not change retroactively
However, backtesting cannot fully capture live trading reality:
- Order fill delays: In live trading, stop and limit orders may not fill instantly at the exact tick shown in backtest
- Volatile periods: During high volatility or low liquidity (news events, rollover days, pre-holidays), slippage may exceed the 1-tick assumption significantly
- Gap risk: The backtest assumes stops fill at stop price, but gaps can cause fills far beyond intended exit levels
- Psychological factors: Seeing actual capital at risk creates emotional pressures not present in backtesting, potentially leading to premature manual intervention
The strategy's backtest results should be viewed as best-case scenarios. Real trading will typically produce 10-30% lower returns than backtest due to the above factors.
Risk Warnings
All trading involves substantial risk of loss. The adaptive learning system can improve parameter selection over time, but it cannot predict future price movements or guarantee profitable performance. Past wins do not ensure future wins.
Losing streaks are inevitable. Even with a 60% win rate, you will encounter sequences of 5, 6, or more consecutive losses due to normal probability distributions. The strategy includes losing streak detection and automatic risk reduction, but you must have sufficient capital to survive these drawdowns.
Market regime changes can invalidate learned patterns. If the strategy learns from 50 trades during a trending regime, then the market shifts to a ranging regime, the adapted parameters may initially be misaligned with the new environment. The system will re-adapt, but this transition period may produce suboptimal results.
Prop firm traders: understand your specific rules. Every prop firm has different rules regarding maximum drawdown, daily loss limits, consistency requirements, and prohibited trading behaviors. While this strategy includes common prop guardrails, you must verify it complies with your specific firm's rules and adjust parameters accordingly.
Never risk capital you cannot afford to lose. This strategy can produce substantial drawdowns, especially during learning periods or market regime shifts. Only trade with speculative capital that, if lost, would not impact your financial stability.
Recommended Usage
Paper trade first: Run the strategy on a simulated account for at least 50 trades or 1 month before committing real capital. Observe how the adaptive system behaves, identify any patterns in losing trades, monitor your stop-out rate trends, and verify your understanding of the entry/exit mechanics.
Start with minimum position sizing: When transitioning to live trading, reduce the Base Risk parameter to 0.3-0.4% initially (vs 0.5-1.0% in testing) to reduce early impact while the system learns your live broker's execution characteristics.
Monitor daily, but do not micromanage: Check the dashboard daily to ensure the strategy is operating normally and risk controls have not triggered unexpectedly. Pay special attention to the Stop-Out Rate metric—if it remains in the red or green zones for multiple days, adjust your Stop Loss ATR multiplier accordingly. However, resist the urge to manually adjust adaptive weights or disable trades based on short-term performance. Allow the adaptive system at least 30 trades to establish patterns before making manual changes.
Combine with other analysis: While this strategy can operate standalone, professional traders typically use systematic strategies as one component of a broader approach. Consider using the strategy for trade execution while applying your own higher-timeframe analysis or fundamental view for trade filtering or sizing adjustments.
Keep a trading journal: Document each week's results, note market conditions (trending vs ranging, high vs low volatility), record stop-out rates and any Stop Loss ATR adjustments you made, and document any manual interventions. Over time, this journal will help you identify conditions where the strategy excels versus struggles, allowing you to selectively enable or disable trading during certain environments.
Technical Implementation Notes
All calculations execute on closed bars only (`calc_on_every_tick=false`) ensuring that signals and values do not repaint. Once a bar closes and a signal generates, that signal is permanent in the history.
The strategy uses fixed-quantity position sizing (`default_qty_type=strategy.fixed, default_qty_value=1`) with the actual contract quantity determined by the position sizing function and passed to the entry commands. This approach provides maximum control over risk allocation.
Order management uses Pine Script's native `strategy.entry()` and `strategy.exit()` functions with appropriate parameters for stops, limits, and trailing stops. All orders include explicit from_entry references to ensure they apply to the correct position.
The adaptive learning arrays (trade_returns, trade_directions, trade_types, trade_hours, trade_was_stopped) are maintained as circular buffers capped at PERFORMANCE_MEMORY size (default 100 trades). When a new trade closes, its data is added to the beginning of the array using `array.unshift()`, and the oldest trade is removed using `array.pop()` if capacity is exceeded. The stop-out tracking system analyzes the trade_was_stopped array to calculate the rolling percentage displayed in the dashboard.
Dashboard rendering occurs only on the confirmed bar (`barstate.isconfirmed`) to minimize computational overhead. The table is pre-created with sufficient rows for the selected dashboard size and cells are populated with current values each update.
Visual effects (fractal grid, wick pressure, morphism beams, order flow clouds, quantum field) recalculate on each bar for real-time chart updates. These are computationally intensive—if you experience chart lag, disable these visual components. The core strategy logic continues to function identically regardless of visual settings.
Timezone conversions use Pine Script's built-in timezone parameter on the `hour()`, `minute()`, and `dayofweek()` functions. This ensures session logic and daily/weekly resets occur at correct boundaries regardless of the chart's default timezone or the server's timezone.
The universal futures detection queries `syminfo.mintick` and `syminfo.pointvalue` on each strategy initialization to obtain the current instrument's specifications. These values remain constant throughout the strategy's execution on a given chart but automatically update when the strategy is applied to a different instrument.
The strategy has been tested on TradingView across timeframes from 5-minute through daily and across multiple futures instrument types including equity indices, energy, metals, agriculture, treasuries, and currencies. It functions identically on all instruments due to the percentage-based risk model and ATR-relative calculations which adapt automatically to price scale and volatility, combined with the universal futures detection system that handles contract-specific specifications.
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic
This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail.
1. General Description
Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions.
Key Features:
Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes.
Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses.
Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes.
Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold).
Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle).
Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results).
Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio.
Strategy Settings:
Initial capital: $10,000.
Pyramiding: Up to 3 positions.
Position size: 10% of equity (default_qty_value=10).
Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management.
Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading.
2. Working Logic (Step by Step)
The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works:
a. Input Parameters
The inputs are grouped for clarity:
Herd Behavior (🐑):
RSI Period (14): For overbought/oversold detection.
Volume MA Period (20): To calculate average volume for spike detection.
Herd Threshold (2.0): Volume multiplier for detecting herd activity.
Liquidity Analysis (💧):
Liquidity Lookback (50): Bars to check for recent highs/lows.
Liquidity Sensitivity (1.5): Volume multiplier for trap detection.
Institutional Flow (🏦):
Institutional Volume Multiplier (2.5): For detecting large volume spikes.
Institutional MA Period (21): For Accumulation/Distribution smoothing.
Nash Equilibrium (⚖️):
Nash Period (100): For calculating price mean and standard deviation.
Nash Deviation (0.02): Multiplier for equilibrium bands.
Risk Management (🛡️):
Use Stop-Loss (true): Enables SL at 2% below/above entry price.
Use Take-Profit (true): Enables TP at 5% above/below entry price.
b. Herd Behavior Detection
RSI (14): Checks for extreme conditions:
Overbought: RSI > 70 (potential herd buying).
Oversold: RSI < 30 (potential herd selling).
Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold).
Momentum: Price change over 10 bars (close - close ) compared to its SMA(20).
Herd Signals:
Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background).
Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background).
c. Liquidity Trap Detection
Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback).
Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones.
Trap Conditions:
Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5).
Down Trap: Price breaks recent low, closes above it, with a volume spike.
Visualization: Traps are marked with small red/green crosses above/below bars.
d. Institutional Flow Analysis
Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity.
Accumulation/Distribution (AD):
Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time.
Smoothed with SMA(21) (inst_ma_length).
Accumulation: AD > MA + high volume = Institutions buying.
Distribution: AD < MA + high volume = Institutions selling.
Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying.
e. Nash Equilibrium
Calculation:
Price mean: SMA(100) (nash_period).
Standard deviation: stdev(100).
Upper Nash: Mean + StdDev x 0.02 (nash_deviation).
Lower Nash: Mean - StdDev x 0.02.
Conditions:
Near Equilibrium: Price between upper and lower Nash bands (stable market).
Above Nash: Price > upper band (overbought, sell potential).
Below Nash: Price < lower band (oversold, buy potential).
Visualization: Orange line (mean), red/green lines (upper/lower bands).
f. Game Theory Signals
The strategy generates three types of signals, combined into long/short triggers:
Contrarian Signals:
Buy: Herd selling + (accumulation or down trap) = Go against retail panic.
Sell: Herd buying + (distribution or up trap).
Momentum Signals:
Buy: Below Nash + positive smart money + no herd buying.
Sell: Above Nash + negative smart money + no herd selling.
Nash Reversion Signals:
Buy: Below Nash + rising close (close > close ) + volume > MA.
Sell: Above Nash + falling close + volume > MA.
Final Signals:
Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy.
Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell.
g. Position Management
Position Sizing (Minimax Principle):
Default: 1.0 (10% of equity).
In Nash equilibrium: Reduced to 0.5 (conservative).
During institutional volume: Increased to 1.5 (aggressive).
Entries:
Long: If long_signal is true and no existing long position (strategy.position_size <= 0).
Short: If short_signal is true and no existing short position (strategy.position_size >= 0).
Exits:
Stop-Loss: If use_sl=true, set at 2% below/above entry price.
Take-Profit: If use_tp=true, set at 5% above/below entry price.
Pyramiding: Up to 3 concurrent positions allowed.
h. Visualization
Nash Bands: Orange (mean), red (upper), green (lower).
Background Colors:
Herd buying: Red (90% transparency).
Herd selling: Green.
Institutional volume: Blue.
Signals:
Contrarian buy/sell: Green/red triangles below/above bars.
Liquidity traps: Red/green crosses above/below bars.
Tables:
Game Theory Table (Top-Right):
Herd Behavior: Buying frenzy, selling panic, or normal.
Institutional Flow: Accumulation, distribution, or neutral.
Nash Equilibrium: In equilibrium, above, or below.
Liquidity Status: Trap detected or safe.
Position Suggestion: Long (green), Short (red), or Wait (gray).
Backtest Table (Bottom-Right):
Total Trades: Number of closed trades.
Win Rate: Percentage of winning trades.
Net Profit/Loss: In USD, colored green/red.
Profit Factor: Gross profit / gross loss.
Max Drawdown: Peak-to-trough equity drop (%).
Win/Loss Trades: Number of winning/losing trades.
Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown).
Avg Win/Loss Ratio: Average win per trade / average loss per trade.
Last Update: Current time.
i. Backtesting Metrics
Tracks:
Total trades, winning/losing trades.
Win rate (%).
Net profit ($).
Profit factor (gross profit / gross loss).
Max drawdown (%).
Simplified Sharpe ratio (returns / drawdown).
Average win/loss ratio.
Updates metrics on each closed trade.
Displays a label on the last bar with backtest period, total trades, win rate, and net profit.
j. Alerts
No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")).
Use TradingView's alert system with Strategy Tester outputs.
3. Usage Tips
Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals.
Settings:
Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping).
Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets.
Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto).
Nash Period: Increase to 200 for longer-term analysis.
Backtesting:
Use TradingView's Strategy Tester to evaluate performance.
Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability.
Test on different assets/timeframes to ensure robustness.
Live Trading:
Start with a demo account.
Combine with other indicators (e.g., EMAs, support/resistance) for confirmation.
Monitor liquidity traps and institutional flow for context.
Risk Management:
Always use SL/TP to limit losses.
Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading).
Avoid over-leveraging (pyramiding=3 can amplify risk).
Troubleshooting:
If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity).
Ensure sufficient historical data for Nash and liquidity calculations.
If tables overlap, adjust position.top_right/bottom_right coordinates.
4. Key Differences from the Previous Indicator
Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting.
Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones.
Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns.
Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator.
Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy.
Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator.
5. Conclusion
The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management.
If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
Hanzo Strategy - Volume & Smart Money📊 HANZO STRATEGY - Complete Description
## 🎯 Strategy Overview
The **Hanzo Strategy** is an advanced institutional trading system that combines Volume Profile analysis, Smart Money Concepts, and Price Action patterns to identify high-probability trade setups. This strategy is specifically designed for trading Gold (XAUUSD), NAS100, and US30 on the 15-minute timeframe.
---
## 🧠 Core Trading Philosophy
The Hanzo Strategy operates on the principle that **institutional money leaves footprints** in the market through:
- Volume accumulation at key price levels
- Liquidity sweeps and stop hunts
- Order block formations
- Strategic wick rejections at support/resistance
By identifying these institutional behaviors and combining them with precise volume analysis, the strategy aims to trade **with** the smart money, not against it.
---
## 🔑 Key Components
### 1️⃣ **Fixed Range Volume Profile (FRVP)**
- **What it does:** Analyzes the last 2 days of price action and calculates where the most volume traded
- **Point of Control (POC):** The price level with the highest trading volume - acts as a magnet for price
- **How we use it:** Price tends to revert to POC. When price is far from POC and starts moving toward it, we prepare for entries
- **Visual:** Yellow cross line on the chart marking the POC
### 2️⃣ **Wick Cluster Detection**
- **What it does:** Automatically identifies price levels where multiple candle wicks have rejected (2-6+ wicks)
- **Why it matters:** Multiple rejections at the same level indicate strong institutional support/resistance
- **Upper wick clusters:** Resistance zones where price was rejected downward
- **Lower wick clusters:** Support zones where price was rejected upward
- **Visual:** Dashed lines (red for resistance, green for support)
### 3️⃣ **Session Volatility Boxes**
- **London Session (8:00-16:00 UTC+3):** Captures European market volatility range
- **New York Session (13:30-20:00 UTC+3):** Captures US market volatility range
- **How we use it:** These ranges often act as support/resistance for the rest of the day
- **Visual:** Blue box for London, Orange box for New York
### 4️⃣ **Smart Money Zones**
**Order Blocks:**
- Strong institutional areas where banks and hedge funds placed large orders
- **Bullish Order Block:** Area where smart money bought heavily before a strong upward move
- **Bearish Order Block:** Area where smart money sold heavily before a strong downward move
- **Visual:** Green/Red filled boxes with "Bull OB" or "Bear OB" labels
**Liquidity Sweeps:**
- Price breaks above recent high or below recent low, then quickly reverses
- This is a "stop hunt" - institutions triggering retail stops before moving in the real direction
- **Bullish Sweep:** Price dips below support, grabs stops, then reverses up
- **Bearish Sweep:** Price pops above resistance, grabs stops, then reverses down
- **Visual:** Triangle markers (green up = bullish, red down = bearish)
### 5️⃣ **Engulfing Pattern Recognition**
- **Bullish Engulfing:** Large green candle fully engulfs the previous red candle - shows strong buying pressure
- **Bearish Engulfing:** Large red candle fully engulfs the previous green candle - shows strong selling pressure
- **How we use it:** Confirmation signal when combined with other factors
- **Visual:** Small circles below/above candles
### 6️⃣ **Trend Bias Indicator**
- Dynamically calculates market bias based on price position relative to POC
- **Bullish:** Price > 0.2% above POC
- **Neutral:** Price within 0.2% of POC
- **Bearish:** Price > 0.2% below POC
- **Visual:** Label at top of chart showing current bias
---
## 📈 Entry Signal Logic
The strategy generates **LONG** and **SHORT** signals based on confluence of multiple factors:
### 🟢 LONG ENTRY CONDITIONS:
1. **POC Break:** Price crosses above POC from below + Trend Bias is Bullish
**OR**
2. **Support Bounce:** Price touches a lower wick cluster + Bullish Engulfing pattern forms
3. **Additional Filter:** Trend Bias must NOT be Bearish
### 🔴 SHORT ENTRY CONDITIONS:
1. **POC Break:** Price crosses below POC from above + Trend Bias is Bearish
**OR**
2. **Resistance Rejection:** Price touches an upper wick cluster + Bearish Engulfing pattern forms
3. **Additional Filter:** Trend Bias must NOT be Bullish
---
## 🎯 Risk Management
### Stop Loss:
- **Calculation:** 2 × ATR(14) from entry price
- **Logic:** Uses Average True Range to adapt to current market volatility
- **Example:** If ATR = 10 points, stop loss is 20 points away
### Take Profit:
- **Calculation:** 3 × ATR(14) from entry price
- **Risk:Reward Ratio:** 1:1.5 (risking 2 ATR to make 3 ATR)
- **Example:** If ATR = 10 points, take profit is 30 points away
### Position Sizing:
- **Default:** 2% of account equity per trade
- **Adjustable:** Can be modified in strategy settings
---
## ⚙️ Strategy Settings & Customization
### Volume Profile Settings:
- **Lookback Days:** How many days to analyze (default: 2)
- **Profile Rows:** Resolution of volume calculation (default: 24)
- **POC Distance Threshold:** Minimum distance from POC for "far from POC" status (default: 0.3%)
### Wick Cluster Settings:
- **Min Wicks for Cluster:** How many wicks needed to form a cluster (default: 3)
- **Lookback Bars:** How far back to search for wicks (default: 50)
- **Tolerance %:** How close wicks must be to cluster together (default: 0.15%)
### Session Settings:
- **London Session:** 08:00-16:00 (adjustable)
- **New York Session:** 13:30-20:00 (adjustable)
- **UTC Offset:** Timezone adjustment (default: +3)
### Smart Money Settings:
- **Order Block Lookback:** How far back to search for order blocks (default: 20)
- **Toggle On/Off:** Can enable/disable order blocks and liquidity sweeps independently
---
## 📊 Performance Metrics Display
The strategy includes a real-time **Information Table** (top-right corner) showing:
| Metric | Description |
|--------|-------------|
| **Trend Bias** | Current market direction (Bullish/Neutral/Bearish) |
| **POC Price** | Current Point of Control price level |
| **Distance from POC** | How far current price is from POC (%) |
| **ATR (14)** | Current volatility measurement |
| **High Wick Clusters** | Number of resistance clusters detected |
| **Low Wick Clusters** | Number of support clusters detected |
| **Current Signal** | Active signal (LONG/SHORT/None) |
---
## 🚨 Alert System
The strategy can send alerts for:
1. **LONG Signal Triggered** - When all conditions met for long entry
2. **SHORT Signal Triggered** - When all conditions met for short entry
3. **Price Touching Support Cluster** - Warning that price at key support
4. **Price Touching Resistance Cluster** - Warning that price at key resistance
**Alert Frequency:** Once per bar (prevents spam)
---
## 📅 Best Trading Timeframes & Instruments
### ✅ Recommended Timeframes:
- **Primary Entry:** 15-minute chart
- **Trend Confirmation:** 30-minute or 1-hour chart
- **Higher Timeframe Filter:** 4-hour for major trend direction
### ✅ Recommended Instruments:
1. **Gold (XAUUSD)** - High volatility, respects key levels well
2. **NAS100 (US Tech 100)** - Strong trends, good liquidity
3. **US30 (Dow Jones)** - Reliable institutional participation
4. **EUR/USD, GBP/USD** - Can work on major forex pairs with adjustments
### ⏰ Best Trading Sessions:
- **London Open (08:00-12:00 UTC+3)** - High volatility, clear directional moves
- **New York Open (13:30-17:00 UTC+3)** - Strongest moves, highest volume
- **Overlap (13:30-16:00 UTC+3)** - Best liquidity and movement
### ⚠️ Avoid Trading:
- Asian session (low volatility)
- Major news events (first 15 minutes after high-impact news)
- Sundays and holidays (low liquidity)
---
## 💡 Pro Trading Tips
### 1. **Multiple Timeframe Confirmation**
- Check 1-hour chart for overall trend before taking 15-minute signals
- Only take LONG signals if 1-hour is bullish
- Only take SHORT signals if 1-hour is bearish
### 2. **POC Strategy**
- Best entries occur when price returns to POC after being far away
- Wait for POC touch + confirmation pattern (engulfing, order block)
- POC acts as support in uptrends, resistance in downtrends
### 3. **Wick Cluster Strategy**
- Strongest signals occur when wick clusters align with POC
- Look for 4+ wicks at the same level for highest probability
- Recent clusters (formed in last 2 days) are stronger than old ones
### 4. **Order Block Strategy**
- Fresh order blocks (just formed) are more powerful
- Wait for price to return to order block zone before entering
- Best when order block + wick cluster occur at same level
### 5. **London/NY Box Strategy**
- If price breaks above session high → look for LONG pullback entries
- If price breaks below session low → look for SHORT pullback entries
- Price often returns to session mid-point before continuing
### 6. **Risk Management Rules**
- **Never risk more than 2% per trade**
- **Don't trade more than 3 positions simultaneously**
- **If 2 losses in a row, reduce size to 1% or stop for the day**
- **Move stop to breakeven after 1:1 profit reached**
### 7. **High-Probability Setups**
Look for **CONFLUENCE** - the more factors aligned, the better:
✅ **BEST LONG SETUP:**
- Price at lower wick cluster (support)
- Price at/near POC
- Bullish order block present
- Bullish engulfing pattern forms
- Trend Bias = Bullish
- 1-hour chart = uptrend
✅ **BEST SHORT SETUP:**
- Price at upper wick cluster (resistance)
- Price at/near POC
- Bearish order block present
- Bearish engulfing pattern forms
- Trend Bias = Bearish
- 1-hour chart = downtrend
---
## 📈 Performance Expectations
### Typical Win Rate:
- **Conservative Trading (high confluence only):** 55-65% win rate
- **Moderate Trading (good setups):** 45-55% win rate
- **Aggressive Trading (all signals):** 35-45% win rate
### Typical Risk:Reward:
- **Average R:R:** 1:1.5 (with 2 ATR stop and 3 ATR target)
- **Breakeven adjusted:** Often improves to 1:2+ when stop moved to BE
### Monthly Trade Frequency (15M chart):
- **Gold:** 60-100 signals per month
- **NAS100:** 50-80 signals per month
- **US30:** 40-70 signals per month
---
## 🎓 Strategy Philosophy Summary
The Hanzo Strategy is built on three core principles:
1. **Follow the Volume** - Trade where institutions are active
2. **Respect the Levels** - Key support/resistance zones matter
3. **Confirm with Price Action** - Wait for confirmation before entering
This is NOT a holy grail - it requires:
- ✅ Discipline to wait for proper setups
- ✅ Patience to let trades play out
- ✅ Risk management to protect capital
- ✅ Emotional control to handle losses
---
## 🛠️ How to Use This Strategy
### Step 1: Initial Setup
1. Add strategy to 15-minute chart
2. Check that all components are visible (POC, clusters, boxes, etc.)
3. Adjust colors if needed for your chart theme
### Step 2: Daily Routine
1. **Pre-Market (before 8:00 AM):**
- Check POC location
- Note wick clusters from previous days
- Mark London/NY session boxes from yesterday
2. **London Session (8:00-16:00):**
- Watch for POC interactions
- Monitor for order blocks forming
- Wait for confluence setups
3. **NY Session (13:30-20:00):**
- Highest activity period
- Best signal quality
- More aggressive entries allowed
### Step 3: Trade Execution
1. Wait for signal label (LONG or SHORT) to appear
2. Check confluence factors (minimum 3)
3. Enter immediately or on next candle
4. Set stop loss at 2 × ATR from entry
5. Set take profit at 3 × ATR from entry
6. Move stop to breakeven at +1.5 ATR profit
### Step 4: Trade Management
- **Don't move stop closer** (let trade breathe)
- **Can trail stop** after 2:1 profit reached
- **Can take partial profits** at 1.5:1 and let rest run
- **Journal every trade** for future improvement
---
## ⚠️ Important Disclaimers
1. **Past performance does not guarantee future results**
2. **This strategy involves risk** - only trade with money you can afford to lose
3. **Backtest thoroughly** on your specific instruments before live trading
4. **Start small** - test with minimum position sizes first
5. **Market conditions change** - what works today may not work tomorrow
6. **Use proper risk management** - this is the #1 key to long-term success
---
## 🎯 Quick Reference Checklist
Before taking any trade, ask yourself:
- ✅ Is there a clear LONG or SHORT signal?
- ✅ Are we in London or NY session?
- ✅ Is price at/near POC or wick cluster?
- ✅ Is trend bias aligned with my direction?
- ✅ Is there an order block or engulfing pattern?
- ✅ Is my risk:reward at least 1:1.5?
- ✅ Am I risking no more than 2% of my account?
**If 5+ are YES → Take the trade!**
**If 3 or fewer YES → Skip and wait for better setup!**
---
## 🚀 Final Words
The Hanzo Strategy is a professional-grade trading system that combines institutional analysis with precise technical execution. Success comes not from taking every signal, but from taking only the **highest probability setups** with proper risk management.
**Trade smart. Trade safe. Trade like an institution.**
📊 **Good luck and profitable trading!** 📊
KDH v2.0 (English) Trading Strategy Indicator# KDH Diamond Strategy v3.3 - TradingView Description
---
## 🇬🇧 ENGLISH VERSION
### 📊 KDH Diamond Strategy v3.3
**Professional High-Leverage Futures Trading System**
---
#### 🎯 Overview
KDH Diamond is an advanced algorithmic trading strategy specifically optimized for **1-hour timeframe futures trading** with high-leverage environments. Built on proven institutional concepts including Fair Value Gaps (FVG), Volume Profile analysis, and multi-layered confirmation filters, this strategy delivers consistent results without repainting.
---
#### ✨ Key Features
**🔥 Optimized for 1H Timeframe**
- Extensively backtested across multiple markets
- Highest profit rate achieved on 1-hour charts
- Perfect for swing traders and active position management
**🎨 No Repainting - 100% Reliable Signals**
- All signals are confirmed and locked on bar close
- What you see in backtest is what you get in real-time
- Complete transparency with `calc_on_order_fills=true`
**💎 Automated Risk Management**
- Automatic Stop Loss and Take Profit calculation
- Intelligent SL/TP placement based on market structure
- Built-in position sizing controls (adjustable % per trade)
**🚀 High-Leverage Futures Optimized**
- Designed specifically for leveraged futures trading
- Risk-reward ratios calibrated for 10-20x leverage environments
- Precision entry timing to maximize profit potential
**🔄 Advanced Position Management**
- Automatic reversal entries at TP levels
- Multiple re-entry opportunities per signal
- Dynamic trade management based on market conditions
**🎛️ Multi-Layer Confirmation System**
- **SMA50 Filter (1H)**: Trend alignment confirmation
- **Momentum Filter**: KAMA-based directional strength
- **RSI Divergence Filter**: Reversal detection at extremes
- **Volume Profile Filter**: Order flow and liquidity analysis
---
#### 📈 How It Works
**Signal Generation**
The strategy identifies **Inverted Fair Value Gaps (IFVG)** - institutional order blocks that signal high-probability reversal or continuation zones. Each signal is validated through multiple confirmation filters before execution.
**Entry Logic**
- Limit orders placed at optimal price levels within FVG zones
- Price must touch the midline and close in favorable direction
- All filters must align for signal activation
**Exit Strategy**
- Stop Loss: Placed at the next opposing FVG level
- Take Profit: Calculated using nearest FVG in profit direction
- Automatic reversal entry option at TP levels
**Visual System**
- Color-coded boxes show FVG zones (green/red)
- Real-time position tracking with entry, SL, and TP lines
- Comprehensive dashboard displaying filter status and P&L
---
#### 🎯 Who Is This For?
✅ **Perfect For:**
- Futures traders using 10-20x leverage
- Traders seeking systematic, rule-based strategies
- Those who want automated SL/TP management
- 1-hour chart swing traders
- Traders familiar with institutional concepts (FVG, order flow)
❌ **Not Ideal For:**
- Scalpers (designed for 1H timeframe)
- Spot-only traders (optimized for leveraged futures)
- Beginners unfamiliar with leverage risks
- Set-and-forget automated trading (requires monitoring)
---
#### 📊 What You Get
**Strategy Features:**
- Complete FVG detection and inversion system
- 4 professional-grade confirmation filters
- Automated SL/TP calculation and placement
- TP reversal entry system
- Volume Profile sentiment analysis
- Real-time position tracking dashboard
- Webhook alert support for automation
- Clean, organized code with detailed comments
**Visual Components:**
- FVG boxes with inversion coloring
- Volume Profile sentiment boxes (optional)
- Entry, SL, and TP lines for each position
- Position status table with live P&L
- Filter status dashboard
---
#### ⚙️ Customization Options
**Adjustable Filters (User Control):**
- SMA50 Filter (1H) - Trend alignment ON/OFF
- Momentum Filter - Directional strength ON/OFF
- RSI Divergence Filter - Reversal detection ON/OFF
- Volume Profile Filter - Order flow analysis ON/OFF
**Fixed Parameters (Optimized):**
- All core parameters are pre-optimized for 1H timeframe
- Ensures consistent performance without overwhelming options
- Prevents parameter over-fitting by users
---
#### ⚠️ Important Disclaimers
**Risk Warning:**
This strategy is designed for leveraged futures trading, which carries substantial risk. High leverage (10-20x) can result in rapid losses. Only trade with capital you can afford to lose.
**Performance:**
Past performance does not guarantee future results. Always backtest on your specific market and timeframe before live trading.
**Usage:**
This is a trading tool, not financial advice. Users are responsible for their own trading decisions and risk management.
**Requirements:**
- Understanding of futures trading and leverage
- Familiarity with Fair Value Gaps and institutional concepts
- Ability to monitor positions (not fully automated)
- Proper risk management discipline
---
#### 🔧 Technical Specifications
- **Platform:** TradingView Pine Script v5
- **Type:** Strategy (with backtesting capabilities)
- **Timeframe:** Optimized for 1H (works on other timeframes)
- **Markets:** Any futures market (crypto, stocks, indices, forex)
- **Repainting:** NO - All signals are final on bar close
- **Alerts:** Full webhook support for automation
- **Default Settings:** 10% position size, pyramiding enabled (max 10 positions)
---
#### 📞 Support
Questions about setup or usage? Contact the author through TradingView messages.
**Note:** This indicator is for educational and trading tool purposes only. The author is not responsible for trading losses. Trade responsibly and within your risk tolerance.
Price-Volume w Trendline - Strategy [presentTrading]█ Introduction and How it is Different
The Price-Volume with Trendline Strategy is an innovative strategy that combines volume profile analysis, price-based Z-scores, and dynamic trendline filtering to identify optimal entry and exit points in the market. What sets this strategy apart is the integration of volume concentration (Point of Control or PoC) with dynamic volatility thresholds. Additionally, this strategy introduces a multi-step take profit (TP) mechanism that adjusts based on predefined levels, allowing traders to exit trades progressively while capitalizing on market momentum.
BTCUSD 6hr LS Performance
█ Strategy, How it Works: Detailed Explanation
The combination of multiple indicators and methodologies serves to create a more robust and reliable trading system. Each element is carefully chosen for its complementary role in providing accurate signals while minimizing false entries and exits. Here’s why the different components were chosen and how they work together:
- PoC and Z-Scores: The volume profile identifies key price areas, while the Z-score measures deviations from the mean. Together, they highlight points where the market is likely to react. For example, when the Z-score indicates an oversold condition near a PoC support level, it increases the probability of a reversal, providing a clear entry signal.
- Trendlines and Z-Scores: Trendlines serve as a secondary filter to ensure that price deviations identified by Z-scores align with broader market trends. This ensures that trades are only entered when the price has both deviated from its average and broken through a significant trendline level, reducing the likelihood of false signals.
- Multi-Step TP and Risk Management: Finally, the multi-step take profit logic works in tandem with the entry signals generated by the PoC, Z-scores, and trendlines. As the price moves in favor of the trade, profits are gradually locked in, ensuring the trader captures gains while still leaving room for further upside.
🔶 Point of Control (PoC) and Volume Profile Analysis
The PoC identifies the price level with the highest volume concentration within a specified lookback period. This price level represents where the most trading activity has occurred, often acting as a strong support or resistance. By breaking down the range into several rows (bins), the strategy identifies how much volume was traded at each price level.
🔶 Z-Score Calculation
The Z-score is a statistical metric that measures how far the current price is from its mean, expressed in terms of standard deviations. This is calculated both for price deviation and PoC-based deviation.
🔶 Trendline Breakout Filtering
The trendline filtering is a crucial aspect that refines entry signals by confirming trend continuation or reversals. It calculates trendlines based on pivot highs and lows using the selected method (e.g., ATR or standard deviation).
🔶 Multi-Step Take Profit
The multi-step take profit mechanism allows the strategy to take partial profits at several predefined levels. For example, when the price reaches 3%, 8%, 14%, or 21% above (or below) the entry price, it exits portions of the position. This is a useful technique for locking in profits as the market moves favorably.
Local
█ Usage
The Price-Volume with Trendline Strategy can be applied to various asset classes, including stocks, cryptocurrencies, and commodities. It is particularly effective in volatile markets where price deviations and volume concentrations signal potential reversals or trend continuations. By adjusting the settings for volatility and the lookback period, this strategy can be tailored to both short-term intraday trades and longer-term swing trades.
█ Default Settings
The default settings in the strategy play a vital role in shaping its performance.
- POC_lookbackLength (144): This defines the number of bars used to calculate the PoC. A longer lookback captures more data, leading to a more stable PoC, but may result in delayed signals. A shorter lookback increases responsiveness but may introduce noise.
- priceDeviationLength (200): This determines the period for calculating the standard deviation of price. A higher length smooths out the volatility, reducing the likelihood of false signals. Shorter lengths make the strategy more sensitive to sudden price movements.
- TL_length (14): Controls the swing detection period for trendline calculation. A shorter length will generate more frequent trendline breakouts, while a longer length captures only significant moves.
- Stop Loss and Take Profit: The strategy offers both fixed and SuperTrend-based stop losses. SuperTrend is adaptive to volatility, while fixed stop losses provide simpler risk control. The multi-step take profit ensures that profits are secured progressively, which can improve performance in trending markets by reducing the risk of full reversals.
Each of these settings can significantly affect the strategy’s risk-reward balance. For instance, increasing the stop loss level or the take profit percentages allows the strategy to stay in trades longer, potentially increasing profit per trade but at the cost of larger drawdowns. Conversely, tighter stops and smaller profit targets result in more frequent trades with lower average profit per trade.
Price-Volume Dynamic - Strategy [presentTrading]█ Introduction and How it is Different
The "Price-Volume Dynamic - Strategy" leverages a unique blend of price action, volume analysis, and statistical z-scores to establish trading positions. This approach differentiates itself by integrating the concept of the Point of Control (POC) from volume profile analysis with price-based z-score indicators to create a dynamic trading strategy. It tailors entry and exit thresholds based on current market volatility, providing a responsive and adaptive trading method. This strategy stands out by considering both historical volatility and price trends to adjust trading decisions in real-time, enhancing its effectiveness in various market conditions.
BTCUSD 4h LS Performance
█ Strategy: How It Works – Detailed Explanation
🔶 Calculating Point of Control (POC)
The Point of Control (POC) represents the price level with the highest traded volume over a specified lookback period. It's calculated by dividing the price range into a number of rows, each representing a price level. The volume at each price level is tallied and the level with the maximum volume is designated as the POC.
🔶 Dynamic Thresholds Adjustments
The entry and exit thresholds are dynamically adjusted based on normalized volatility, which is derived from the current, minimum, and maximum ATR over a specified period. This normalization ensures that the thresholds adapt to changes in market conditions, making the strategy sensitive to shifts in market volatility.
BTCUSD local performance
█ Trade Direction
The strategy can be configured to trade in three different directions: Long, Short, or Both. This flexibility allows traders to align their trading strategy with their market outlook or risk preferences. By adjusting the `POC_tradeDirection` input, traders can selectively participate in market movements that match their trading style and objectives.
█ Usage
To deploy this strategy, traders should apply it within a trading software that supports scripting and backtesting, such as TradingView's Pine Script environment. Users can input their parameters based on their analysis of the market conditions and their risk tolerance. It is essential for traders to backtest the strategy using historical data to evaluate its performance and make necessary adjustments before applying it in live trading scenarios.
█ Default Settings
- Lookback Length: Sets the period over which the highest and lowest prices, and the volume per price level, are calculated. A higher lookback length smoothens the volatility but may delay response to recent market movements.
- Number of Rows: Determines the granularity of price levels within the price range. More rows provide a more detailed volume profile but require more computational resources.
- Entry Z-Score Threshold Base: Influences the sensitivity of the strategy to enter trades. Higher values make the strategy more conservative, requiring stronger deviation from the mean to trigger a trade.
- Exit Z-Score Threshold Base: Sets the threshold for exiting trades, with lower values allowing trades to close on smaller price retractions, thereby potentially preserving profits or reducing losses.
- Trading Direction: Allows selection between Long, Short, or Both, enabling traders to tailor the strategy to their market view or risk preferences.
Volumemetrix Variance StrategyThe “Volumemetrix Variance Strategy” is an advanced Pine Script strategy designed to identify trade entries and exits using a combination of volume profile analysis, candle structure, and volatility filters. It constructs a dynamic volume profile over a specified lookback period to identify critical price levels such as the Point of Control (PoC), Value Area High (VAH), and Value Area Low (VAL). These levels represent zones of high trading activity that often act as support and resistance. The script smooths and adjusts these levels across different timeframes to align short-term market structure with higher-timeframe trends. It incorporates a variety of filters to exclude doji candles, detect continuation or rejection patterns, and confirm alignment with higher timeframe candle direction (e.g., 4-hour bullish or bearish bias).
Trade logic is built around detecting crossovers and breakouts relative to the PoC and value areas. The system can trigger entries based on several configurable behaviors: breakout, retake, bounce, reversal, or rejection near key volume zones. It supports flexible entry conditions for long, short, or both sides of the market, as well as a range of customizable settings for time-based trading restrictions, end-of-day position closures, and alert-based data capture. For execution, the script includes integrated risk management—users can specify take-profit and stop-loss levels, enable moving (trailing) stops, and even apply a “power curve” model to dynamically adjust trailing stops using exponential decay logic that adapts to price progress.
Overall, the Volumemetrix Variance Strategy is a hybrid between a quantitative volume-based strategy and a volatility-adaptive trade manager. It combines fixed range volume profiling with multi-timeframe confirmation, candle pattern validation, and adaptive exit logic. Its architecture allows for detailed trade automation, alert generation for external systems, and real-time control over parameters such as ATR scaling, entry delay, or bar confirmation. The result is a high-granularity framework for both backtesting and live execution that seeks to capture statistically favorable setups around liquidity concentration zones.
Pro Reversal Strategie - FinalCore Functionality Description
The "Pro Reversal Strategy" script is a comprehensive and highly customizable trading system for TradingView. Its core idea is based on a mean-reversion strategy, which aims to capitalize on price extremes where the price is likely to revert to its statistical mean. This script ist full AI generated. There ist no support and no financial advice.
To identify entry points, the script combines classic indicators like the RSI (to detect overbought and oversold conditions) and Bollinger Bands (to measure volatility extremes).
However, the script's strength lies in its confluence logic: a simple RSI or Bollinger Band signal is not enough to trigger a trade. Instead, a series of filters are applied to enhance the quality of the trade signals. These include:
Trend Filter: Trades are only taken in the direction of the higher-level trend (defined by a 200-period Moving Average).
Volatility and Volume Filter: ADX and volume analysis ensure that the market has sufficient momentum for a move.
Market Structure Analysis: Concepts like Fair Value Gaps (FVG), liquidity zones, and the Volume Profile (VRVP/POC) are used to place trades in high-probability zones.
Momentum Filter: Special "Vector Candles" confirm the strength of buyers or sellers at the moment of the signal.
Furthermore, the script offers advanced features for risk and trade management, including automatic position sizing based on a percentage risk and dynamic exit strategies like a breakeven stop and a trailing stop-loss (Chandelier ATR).
A detailed info panel visualizes all key metrics in real-time directly on the chart. Thanks to its versatile configuration options, the script can be adapted for various trading styles, including swing trading, day trading, and scalping.
Core Strategies & Filters (English)
Here is a breakdown of the specific strategies and confirmation filters used within the script:
RSI Mean Reversion: Uses the Relative Strength Index (RSI) to identify overbought (> rsiSellShort) and oversold (< rsiBuyLong) conditions, which serve as the primary trigger for a potential price reversal.
Bollinger Bands (BB) Volatility Filter: Trades are confirmed when the price touches or exceeds the outer Bollinger Bands. This indicates a move to a statistical extreme in terms of volatility, reinforcing the reversal thesis.
Trend Filter (200 SMA): Ensures that long trades are only considered in a general uptrend (price > SMA 200) and short trades in a downtrend (price < SMA 200), preventing trades against the dominant market direction.
ADX Trend Strength Filter: Utilizes the Average Directional Index (ADX) to confirm that a market is trending with sufficient strength. Trades are filtered out during weak or non-trending phases (adx < adxThreshold).
Volume Profile (VRVP / POC): Analyzes volume at specific price levels to identify high-volume nodes (Point of Control - POC). This acts as a filter to avoid entering trades directly into a zone of strong support or resistance.
Vector Candle Filter: Identifies "Vector Candles" – large, high-volume candles that close strongly near their high (bullish) or low (bearish). This custom filter confirms strong conviction behind the initial reversal signal.
Market Structure (FVG & Liquidity): Incorporates advanced price action concepts. It looks for entries after a liquidity zone above a previous high/low has been tapped (Liquidity Grab) or when price enters a Fair Value Gap (FVG), adding a layer of institutional trading logic.
Chart Pattern Recognition: Optionally identifies classic chart patterns like "W-Patterns" (Double Bottom), "M-Patterns" (Double Top), and Ascending Triangles to provide additional visual confirmation for traders.
Position Sizing (Risk %): Automatically calculates the trade size based on a user-defined percentage of the total equity (riskPct) and the distance to the stop-loss, ensuring consistent risk management for every trade.
Dynamic Exit Management: Implements advanced exit strategies beyond a fixed take-profit. This includes moving the stop-loss to Breakeven after a certain risk-to-reward ratio is met and using a Trailing Stop-Loss (e.g., Chandelier ATR) to lock in profits as a trade develops.
TTE Elite Market SignalsWelcome to TTE Elite Market Signals Your very own personal trading assistant
Trading today demands more than intuition—it requires exclusive access to elite-level market intelligence and the discipline to act on high-probability signals. Every professional trader seeks that decisive advantage: the clarity and confidence that separates consistent profitability from market uncertainty. The financial markets show no mercy, demanding precision, logic, and strategy grounded in institutional-grade analysis.
Human judgment, while powerful, can be compromised by fatigue and emotion, leading to costly trading errors. This is precisely where TTE Elite Market Signals excels. Our sophisticated platform combines proven trading methodologies with advanced signal generation technology, delivering market intelligence that empowers you to identify optimal entry and exit opportunities while maintaining complete control over your trading decisions.
Revolutionary Signal Intelligence
TTE Elite Market Signals features adaptive learning technology that evolves with market conditions. It continuously refines its analysis, helping you identify higher-probability setups while providing the market intelligence needed for superior risk management.
Elite Analysis Modes
Our platform adapts its signal generation to match market personalities:
- Institutional Flow Mode (MM-hybrid): Identifies manipulation patterns and tracks smart money movement with exclusive institutional-grade precision
- Momentum Adaptive Mode: Rapidly adjusts analysis when volatility and momentum shift
- Conservative Precision Mode: Steady, risk-conscious signals for consistent performance
- Adaptive Intelligence Mode: Self-refining system that enhances signal quality over time from past trades (long term of use)
Comprehensive Signal Intelligence
TTE Elite Market Signals integrates multiple sophisticated analytical systems:
- Volume Profile analysis for exclusive institutional-level market insights
- Pattern recognition enhanced by machine learning algorithms
- Intelligent exit timing that identifies optimal profit-taking opportunities
- Protection against market manipulation tactics
- Position sizing guidance that scales with trading success
- Fibonacci based reversal logic
Perfect for Your Trading Evolution
Experienced traders appreciate our sophisticated market intelligence and institutional-grade analytics that provide genuine competitive advantages.
Developing traders benefit from intelligent signal analysis that handles complex market calculations while teaching professional-level market interpretation and risk management principles via visuals on chart and descriptive panel.
All timeframes supported—from scalping to swing trading, TTE Elite Market Signals adapts to your preferred trading style via several user input selections.
Two Elite Service Modes
1. Signal Intelligence Mode: Real-time market signals with AI-driven analysis and detailed trade rationale
2. Alert Precision Mode: High-probability setup notifications with comprehensive market context and risk parameters
The Exclusive Learning Advantage
What makes TTE Elite Market Signals exceptional: it maintains a comprehensive trade memory and identifies the highest-probability signals, adapts to changing volatility patterns, and continuously refines(does not repaint) its analysis to enhance your profit potential and trading accuracy.
Built-in Professional Protection
- Advanced manipulation detection safeguards against institutional market maker(MM) tactics
- Intelligent risk assessment adjusts signal confidence based on market conditions
- Progressive scaling guidance maximizes winners while minimizing losses(educational)
- Comprehensive oversight with customizable risk parameters
Experience the Elite Difference
TTE gives you visuals on the chart of past trades and live metrics results to see what actually work and what fails, to minimize unrealistic expectations. Just sit back and watch sophisticated algorithms work tirelessly on your behalf, identifying opportunities that others miss and alerting you as signals are generated. Transforming the stressful, emotional battlefield of trading into a systematic analytical approach.
Let the System Do the Heavy Lifting
While others struggle with analysis paralysis and emotional decision-making, you'll have access to signals that have already processed hundreds of data points, identified institutional patterns, and calculated optimal risk-reward scenarios for a far less stressful trading experience.
What Elite Traders Should Know
TTE Elite Market Signals represents cutting-edge signal generation technology designed for serious market education and skill development, but it is not a black box, nor perfect for all markets. It must be adjusted to yield optimal results. While our advanced capabilities and institutional-grade features provide significant analytical advantages, trading success requires discipline and proper execution. Markets evolve, and optimal results demand understanding of signal context.
Success with TTE Elite Market Signals comes from mastering our analytical modes and using the proper entry types such as breakout entry, machine learning(ML) entry etc, utilizing and selecting the most effective risk control to optimize it, and maintaining disciplined risk management.
Join the Elite Trading Revolution
This isn't just another signal service—it equips you with the tools to do proper market analysis displaying price movement and volume profile designed for serious traders who understand that consistent profitability comes from discipline, superior market intelligence and proper interpretation, not luck.
Trade smart, stay profitable, and achieve trading excellence.
Best TTE Settings
Trade Entry Types:
1st Best Breakout Entry(out perform all others when used alone)
2nd Best ML Entry by itself or + Pattern Entry Combined
Risk Management:
ATR Multiplier 2
Enable Master Size Control
Master Size Mode
Max Risk Per Trade % 2.5
Max Multiplier Cap 1.5
Enable Growth Scaling
Growth Scaling Mode-set to Time Based or Performance
Risk Management System- set to Hybrid
Enable ML System
ML Mode-set to Auto or Quantum Learning
ML Application Strategy-set to Universal All Entries
Enable Trend Continuation
Mode- Set to Standard
Independent Entry-stays unchecked(off)
Best Performing Instruments on TTE (will update list as more are adjusted and tested)
NVDA
AMD
AMZN
TSLA
SPY
QQQ
PLTR
Momentum Pull Back Stratergy"Master Pull Back Strategy" is a highly detailed momentum and volume-based trading system designed for Trading View. It visually annotates the chart, detects buy/sell signals, tracks market phases, and evaluates retracements and confirmations. Below is a full breakdown of its logic and components:
🔷 1. Volume Profile Highlights (Arrow Emojis)
Purpose: Show volume strength vs. average using color-coded arrows.
Calculates average volume over a user-defined period (length = 10).
Divides current volume by average volume to get volRatio.
Based on volRatio, plots small arrows (acting like diamonds) in various colors:
Low volume (black, navy, blue...) to high volume (yellow, red, purple).
Visual Purpose: Give a quick sense of how "loud" or "quiet" a candle's volume is.
📈 2. Highs of Day Tracking
Purpose: Track the high price reached during different trading sessions.
Defines pre-market, regular, and post-market sessions.
Tracks the highest price (high) in each session.
Plots colored lines:
Orange: Pre-market high
Red: Regular market high
Blue: Post-market high
🟩 3. Green Candle Pattern Detection
Purpose: Detect bullish patterns formed by consecutive green candles.
Key Conditions:
Count green candles (greenCount) until a red candle appears or 10 candles max.
Require at least 1 silver-or-above volume candle (volRatio >= 1.0).
Must have ≥3% price gain during the green sequence.
Must accumulate >20,000 volume during the green run.
If Valid:
Locks the pattern.
Records important values:
patternStartPrice, patternEndPrice, totalPatternVolume, patternHigh, patternBars
Marks the bar after which red starts (redStartBar)
⬇️ 4. Retracement Monitoring
Purpose: Track retracement from the pattern high after it locks.
Defines retracement percentage:
(greenPatternHigh - low) / (greenPatternHigh - greenPatternLow)
If retracement exceeds 80%, it invalidates the pattern.
Buy signal is disabled if pattern retraces too far.
✅ 5. Buy Signal Logic
Purpose: Fire a buy signal after pattern lock if price breaks above local high.
Conditions:
Pattern is locked (patternLocked).
Price breaks above a short-term high (triggerBreak).
It's not the first red candle.
Price is within 8.5% above EMA9.
Buy signal fires and:
Sets buyActive = true
Tracks highest price after buy
Stores buyPrice = close
❌ 6. Sell Signal Logic
Purpose: Exit signal after retracement from post-buy high.
While buy is active:
If price retraces ≥3% from the post-buy high → sellSignal = true
Resets buyActive, trackedHigh, and buyPrice
Plots a red "SELL" label above the bar.
🎨 7. Buy Signal Visual Color Coding
Purpose: Color buy signal based on how deep the retracement is.
Uses retracement percentage:
≥65% → Red (high risk)
45–65% + MACD bullish → Yellow (moderate)
<45% + MACD bullish → Green (ideal)
Plots BUY label below bar in the respective color.
🔻 8. Retracement Triangle Visuals
Purpose: Shows retracement progression while pattern is locked.
If pattern is locked and not ready for buy:
Plots triangle below bar in the buyColor for visual tracking.
⭐ 9. Star Markers Above Lock Candle
Purpose: Confirmations when pattern locks.
First Star:
Plotted above the first red candle after green pattern lock.
Second Star (⭐⭐):
Additional confirmations:
Volume OK (less than previous)
MACD bullish
Price > VWAP
VolAtLock > 100K
Price up >6% from first green candle
Price below 75% of daily EMA200 or above EMA200
Third Star (⭐⭐⭐):
Even stricter confirmations:
Volume < 60% of previous
High <= previous high
VolAtLock > 500K
Price > $3
Gain >9% from first green
Price < 50% of daily EMA200 or above EMA200
📊 10. Bar Coloring
Purpose: Visually highlight bars based on pattern phase and MACD.
Gray: MACD Bearish
Light Green: Part of active green pattern
Blue: In locked phase but no buy triggered
🔄 11. Reset Logic
Purpose: Clears all tracking variables once a buy signal fires or pattern is invalidated.
Also resets if:
Retracement is too deep
10 candles pass post-lock without a trigger
⛰️ 12. Double Top Detection
Purpose: Basic visual marker when current high == previous high.
Plots a gray triangle if current and previous bar highs match.
📌 Summary: What This Strategy Shows
Buy Opportunities: Based on high-volume green runs and confirmed breakouts.
Sell Triggers: Once a retracement from peak exceeds 3%.
Visuals for Confirmation:
Diamonds for volume
Stars for lock confidence
Colors for retracement strength
Risk Management:
Retracement filtering
Time limits on locked phases
Volume filters
Market Context: Tracks pre/regular/post market highs and daily EMA 200.
Patient Trendfollower (7)(alpha) Backtesting AlgorithmThis is an alpha version of backtesting algorithm for my Patient Trendfollower (7) strategy. It can help you adapt the indicator to other charts than EURUSD. Please bear in mind that price action, volume profiles and supzistences are a catalyst for successful trading, not an indicator. You can get significantly better results if you use these things in your trading and use Trendfollower only as a secondary tool.
Patient Trendfollower Indicator
Thanks belongs to @everget and Satik FX, their contributions are highlighted on an indicator page.
Auction Market Theory: Value Area & VWAP Fade - DashboardAn "Auction Market Theory" dashboard is a visual summary of the market's state according to the principles of Auction Market Theory. It consolidates key metrics like the Value Area (VA), Point of Control (POC), and Volume-Weighted Average Price (VWAP) into a single, easy-to-read panel on your chart.
What a Dashboard Shows
The purpose of the dashboard is to give traders a quick, real-time snapshot of the market's auction process. It helps you answer critical questions like:
Where is the market's "fair value"? This is shown by the Value Area (VA) range.
Where is the most volume concentrated? This is the Point of Control (POC), the price that acts as a gravitational center.
How are market participants currently positioned? The VWAP provides a measure of the average price paid, weighted by volume. Price trading above VWAP suggests a bullish volume bias, while price below suggests a bearish bias.
Is the market in a state of balance or imbalance? The relationship between the current price and these key levels helps to quickly determine if the market is accepting a price range (balance) or rejecting it (imbalance/trend).
How to Interpret the Dashboard
Value Area (VA) & Point of Control (POC)
These metrics are derived from a volume profile and are the foundation of the auction theory dashboard. The dashboard displays the VA's low and high, as well as the POC. These levels define the market's "accepted" price range for a given period.
VWAP
VWAP acts as a real-time moving average that is more responsive to volume than a standard moving average. It's often used as an intraday anchor. When price is significantly stretched from the VWAP (and its standard deviation bands), it's a signal of a potential over-extension and a target for a mean-reversion trade.
Dashboard's Role in Trading
The dashboard is not an entry signal itself, but a contextual tool. It provides the framework for your trading decisions. For a "fade the edge" strategy, you would use the dashboard to:
Identify the edges: See the exact price levels of the VA and VWAP bands.
Wait for the stretch: Look for price to move beyond those edges.
Confirm the reversal: Only then would you look at other indicators (like RSI or volume spikes) for an entry signal.
Manage the trade: Use the POC as a potential take-profit target, as price has a high probability of returning to this point of volume consensus.
CVD Divergence Strategy.1.mmThis is the matching Strategy version of Indicator of the same name.
As a member of the K1m6a Lions discussion community we often use versions of the Cumulative Volume Delta indicator
as one of our primary tools along with RSI, RSI Divergences, Open interest, Volume Profile, TPO and Fibonacci levels.
We also discuss visual interpretations of CVD Divergences across multiple time frames much like RSI divergences.
RSI Divergences can be identified as possible Bullish reversal areas when the RSI is making higher low points while
the price is making lower low points.
RSI Divergences can be identified as possible Bearish reversal areas when the RSI is making lower high points while
the price is making higher high points.
CVD Divergences can also be identified the same way on any timeframe as possible reversal signals. As with RSI, these Divergences
often occur as a trend's momentum is giving way to lower volume and areas when profits are being taken signaling a possible reversal
of the current trending price movement.
Hidden Divergences are identified as calculations that may be signaling a continuation of the current trend.
Having not found any public domain versions of a CVD Divergence indicator I have combined some public code to create this
indicator and matching strategy. The calculations for the Cumulative Volume Delta keep a running total for the differences between
the positive changes in volume in relation to the negative changes in volume. A relative upward spike in CVD is created when
there is a large increase in buying vs a low amount of selling. A relative downward spike in CVD is created when
there is a large increase in selling vs a low amount of buying.
In the settings menu, the is a drop down to be used to view the results in alternate timeframes while the chart remains on current timeframe. The Lookback settings can be adjusted so that the divs show on a more local, spontaneous level if set at 1,1,60,1. For a deeper, wider view of the divs, they can be set higher like 7,7,60,7. Adjust them all to suit your view of the divs.
To create this indicator/strategy I used a portion of the code from "Cumulative Volume Delta" by @ contrerae which calculates
the CVD from aggregate volume of many top exchanges and plots the continuous changes on a non-overlay indicator.
For the identification and plotting of the Divergences, I used similar code from the Tradingview Technical "RSI Divergence Indicator"
This indicator should not be used as a stand-alone but as an additional tool to help identify Bullish and Bearish Divergences and
also Bullish and Bearish Hidden Divergences which, as opposed to regular divergences, may indicate a continuation.
Nifty Volume profile + VWAP + EMA The script picks up nifty stocks with their current respective weights and plots a Volume Weighted Average Price line along with 2 EMAs and an alert when the EMAs cross over.
You can customize the script for EMA lengths and to remove alert. Basic utility of the script is to analyse volumes driving the Nifty 50 index.
Credits to @daytraderph and his script (Custom Volume) who's code I used to build this script. Also thanks to my friend @Varun who helped me code it.
Underworld Hunter Backtesting AlgorhitmThis strategy is built to prove the profitability of my Underworld Hunter indicator . It tests two different strategies. I won't be going into the calculation again since it is part of the original script. I just made a few adjustments.
First one is clearly visual. It plots slimmer twin-coloured lines now and has a different colour for every extreme level. Second is less obvious - I switched Relative Strength Index for Commodity Channel Index.
Extreme levels are as follows: green 100 -► 120, yellow 120 -► 140, orange 140 -► 160, red 160 -► 180 and purple above 180, I will have a special separate algorithm for testing optimal CCI levels someday, in this script, these values are only meant to help you with manual operations and do not influence results of the strategy in any way.
#Trending strategy
The trending strategy opens a position whenever the price leaves the bands and holds it until two consecutive bars are closed within the bands. The picture shows one winning position that hasn't yet been resulted. It also shows a few fakeouts. For this strategy, you want to keep the length below 110, the deviation should be below 2 and you probably want to play lower timeframes.
#Within the bands
The second strategy is pretty much the opposite. It opens a position when the price reaches outer bands and holds it until two consecutive bars are closed within the bands and current bar closes below previous bars low in case of long. It is working on hourly timeframes and you need higher length and deviation to succeed. The picture shows a few positions on EURUSD. Each of them is profitable but would be much higher if you closed it manually when it was time. You need to enable this strategy, which automatically disables the other one.
When using my script, you need to bear in mind that the first strategy doesn't detect optimal levels to close the price. A trend is often followed by a less volatile and boring correction which causes bands to shrink and lower your profits if you don't close manually as it will take longer till bands are reached.
On the other hand, second script literally has no stop-loss. As long as the price is outside the range, it will never close which will cause major drawdowns, unless you control the trade manually. CCI is here to help you with both.
I also recommend combining this with Market Profile (on TW, there is only Volume Profile, which can be used in a similar way) and trading day theory (trending with multiple distributions, trending day, normal day, a variation on a normal day, non-trending day or neutral day). Always keep in mind that it is up to traders to be profitable, indicators can support a good trader, but they will not fix a bad one.
LiquiBreak — Semi-Automatic Breakout, Gap & Trend-Filter StrategLiquiBreak is a semi-automatic breakout + gap detection strategy that combines pivots, a volatility filter and an optional Supertrend direction check to generate entry signals. It can optionally place take-profit and stop-loss orders in points. Use it to highlight high-probability breakout/gap setups and to automate exits when you want — otherwise treat its signals as trade alerts that require your confirmation.
📌 LiquiBreak — Semi-Automatic Breakout, Gap & Trend Strategy
1. Overview
1. LiquiBreak is a semi-automatic breakout + gap strategy designed to catch high-quality moves with volatility confirmation.
2. Uses pivot-based support/resistance , gap detection , Supertrend filtering , and optional automatic TP/SL in points .
3. Works on all assets and timeframes, especially effective on XAUUSD, Indices, Crypto and FX pairs .
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2. What This Script Detects
1. Breakouts above resistance and below support during strong volatility.
2. Bullish & bearish gap patterns confirmed with momentum sequences.
3. Dynamic volatility zones based on normalized ATR ranges.
4. Optional Supertrend trend direction for filtering bad signals.
5. Automatic TP/SL orders when enabled.
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3. Recommended Indicators to Combine With
To increase accuracy and reduce false breakouts:
1. Supertrend (included) – best for trend direction.
2. EMA 9/21 or EMA 20/50 – confirms trend strength & pullbacks.
3. RSI or Stoch RSI – avoid overbought/oversold breakouts.
4. VWAP – institutional bias & fair value zones.
5. CPR / Pivot Points – confluence with breakout levels.
6. MACD – trend confirmation on higher timeframe.
7. Volume Profile (optional) – find breakout liquidity zones.
These indicators help filter low-quality signals without affecting the script’s core logic.
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4. Key Features
1. Volatility-based pivot support & resistance .
2. Reliable breakout confirmation using real-time volatility strength.
3. Strong gap pattern detection with ATR threshold.
4. Optional Supertrend confirmation for safer entries.
5. Point-based Take Profit / Stop Loss .
6. Toggle on/off: Longs, Shorts, TP, SL .
7. Semi-automatic execution — not fully automated.
8. Clean, optimized structure for stability and speed.
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5. Inputs / Settings
1. Pivot / Levels Period – defines structural S/R levels.
2. Volatility Filter (%) – prevents low-quality signals.
3. TP Points – automatic take-profit target.
4. SL Points – automatic stop-loss.
5. Enable TP / Enable SL – full exit control.
6. Allow Long / Allow Short – direction control.
7. Supertrend Filter – filter weak counter-trend trades.
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6. How to Use the Strategy
1. Select timeframe & tune pivot/volatility settings.
2. Enable/disable automatic TP/SL based on your style.
3. Turn ON Supertrend for safer trend-based trades.
4. Confirm signals using EMA, RSI, VWAP, Volume or CPR.
5. Watch for high-volatility breakouts near key levels.
6. Use multiple timeframe analysis for stronger confirmation.
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7. Important Warning (User Must Monitor Trades)
⚠ This script is NOT a fully automatic bot.
1. You MUST monitor the chart while using this strategy.
2. You MUST manually close trades if market conditions change.
3. Auto TP/SL helps, but during news events or fast markets, slippage may occur.
4. Treat this script as a signal + entry assistant , not a fire-and-forget system.
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8. Best Practices
1. Works best on XAUUSD, NAS100, BTC, ETH, EURUSD .
2. Avoid major news unless experienced.
3. Increase volatility filter during choppy markets.
4. Use M15–H1 for clean breakouts; M5 for scalping.
5. For beginners: keep TP/SL enabled for safety.
6. Backtest first → then paper trade → then live trade.
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9. Disclaimer
1. For educational and research purposes only .
2. Not financial advice.
3. User is fully responsible for their trades and risk.
4. Past performance does not guarantee future results.
Nasdaq 1 min Nasdaq 1 minute
XAGUSD 5 MIN
The volume profile is built by distributing the tick volume equally across the discrete price levels of each bar. This is an approximation.
