Hash Ratings EngineHash Ratings Engine - Technical Consensus Strategy
A systematic trading strategy that harnesses TradingView's Technical Ratings to generate high-conviction entries with institutional-grade risk management.
What It Does
This strategy aggregates the consensus of 26+ technical indicators (RSI, MACD, Stochastics, multiple Moving Averages, etc.) into a single actionable signal. When enough indicators align bullish or bearish, the engine triggers an entry. Built-in trend filtering and ATR-based exits keep you on the right side of the market.
Key Features
Trend Filter - Only takes longs in uptrends, shorts in downtrends. This single filter typically improves results by 20-40% by avoiding counter-trend trades.
ATR-Based Risk Management - Stop loss and trailing stops adapt to current market volatility. Tight stops in calm markets, wider stops in volatile conditions.
Cooldown System - After a losing trade, the strategy waits before re-entering. This prevents the consecutive loss streaks that destroy accounts.
Clean Visuals - Fluorescent entry/exit signals with price level references. See exactly where you got in and out.
Settings Guide
Indicator Timeframe: Leave blank for current chart. Use higher timeframe for fewer, higher-quality signals.
Rating Source: "All" for balanced approach. "MAs" for trend-following. "Oscillators" for mean-reversion.
Entry Thresholds
Strong Signal Threshold: Higher = fewer trades but better conviction. Start at 0.5, test 0.4-0.6.
Risk Management
ATR Period: 12 is responsive, 14 is standard, 20+ is smoother.
Stop Loss: 2-3x ATR for tight stops, 3.5-4x for moderate, 5x+ for wide.
Trail Activation: How far price must move in profit before trailing begins.
Trail Offset: How closely the trail follows price.
Trend Filter
EMA Length: 150 works well on 4H charts. Use 100 for lower timeframes, 200 for daily.
Trade Timing
Cooldown: Keep enabled. 5 bars is a good starting point.
Best Practices
Start with default settings and backtest on your preferred instrument. Adjust the Strong Signal Threshold first - this has the biggest impact on trade frequency. Then tune the EMA length to match your timeframe. Finally, optimize the ATR multipliers for your risk tolerance.
Works on any liquid market - crypto, forex, stocks, futures. Higher timeframes (4H, Daily) tend to produce cleaner signals than lower timeframes.
Disclaimer
Past performance does not guarantee future results. Always backtest thoroughly and use proper position sizing. This strategy is for educational purposes - trade at your own risk.
Trend
US Market Long Horizon Momentum Summary in one paragraph
US Market Long Horizon Momentum is a trend following strategy for US index ETFs and futures built around a single eighteen month time series momentum measure. It helps you stay long during persistent bull regimes and step aside or flip short when long term momentum turns negative.
Scope and intent
• Markets. Large cap US equity indices, liquid US index ETFs, index futures
• Timeframes. 4h/ Daily charts
• Default demo used in the publication. SPY on 4h timeframe chart
• Purpose. Provide a minimal long bias index timing model that can reduce deep drawdowns and capture major cycles without parameter mining
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. One unscaled multiple month log return of an external benchmark symbol drives all entries and exits, with optional volatility targeting as a single risk control switch.
• Failure mode addressed. Fully passive buy and hold ignores the sign of long horizon momentum and can sit through multi year drawdowns. This script offers a way to step down risk in prolonged negative momentum without chasing short term noise.
• Testability. All parameters are visible in Inputs and the momentum series is plotted so users can verify every regime change in the Tester and on price history.
• Portable yardstick. The log return over a fixed window is a unit that can be applied to any liquid symbol with daily data.
Method overview in plain language
The method looks at how far the benchmark symbol has moved in log return terms over an eighteen month window in our example. If that long horizon return is positive the strategy allows a long stance on the traded symbol. If it is negative and shorts are enabled the strategy can flip short, otherwise it goes flat. There is an optional realised volatility estimate on the traded symbol that can scale position size toward a target annual volatility, but in the default configuration the model uses unit leverage and only the sign of momentum matters.
Base measures
Return basis. The core yardstick is the natural log of close divided by the close eighteen months ago on the benchmark symbol. Daily log returns of the traded symbol feed the realised volatility estimate when volatility targeting is enabled.
Components
• Component one Momentum eighteen months. Log of benchmark close divided by its close mom_lookback bars ago. Its sign defines the trend regime. No extra smoothing is applied beyond the long window itself.
• Component two Realised volatility optional. Standard deviation of daily log returns on the traded symbol over sixty three days. Annualised by the square root of 252. Used only when volatility targeting is enabled.
• Optional component Volatility targeting. Converts target annual volatility and realised volatility into a leverage factor clipped by a maximum leverage setting.
Fusion rule
The model uses a simple gate. First compute the sign of eighteen month log momentum on the benchmark symbol. Optionally compute leverage from volatility. The sign decides whether the strategy wants to be long, short, or flat. Leverage only rescales position size when enabled and does not change direction.
Signal rule
• Long suggestion. When eighteen month log momentum on the benchmark symbol is greater than zero, the strategy wants to be long.
• Short suggestion. When that log momentum is less than zero and shorts are allowed, the strategy wants to be short. If shorts are disabled it stays flat instead.
• Wait state. When the log momentum is exactly zero or history is not long enough the strategy stays flat.
• In position. In practice the strategy sits IN LONG while the sign stays positive and flips to IN SHORT or flat only when the sign changes.
Inputs with guidance
Setup
• Momentum Lookback (months). Controls the horizon of the log return on the benchmark symbol. Typical range 6 to 24 months. Raising it makes the model slower and more selective. Lowering it makes it more reactive and sensitive to medium term noise.
• Symbol. External symbol used for the momentum calculation, SPY by default. Changing it lets you time other indices or run signals from a benchmark while trading a correlated instrument.
Logic
• Allow Shorts. When true the strategy will open short positions during negative momentum regimes. When false it will stay flat whenever momentum is negative. Practical setting is tied to whether you use a margin account or an ETF that supports shorting.
Internal risk parameters (not exposed as inputs in this version) are:
• Target Vol (annual). Target annual volatility for volatility targeting, default 0.2.
• Vol Lookback (days). Window for realised volatility, default 63 trading days.
• Max Leverage. Cap on leverage when volatility targeting is enabled, default 2.
Usage recipes
Swing continuation
• Signal timeframe. Use the daily chart.
• Benchmark symbol. Leave at SPY for US equity index exposure.
• Momentum lookback. Eighteen months as a default, with twelve months as an alternative preset for a faster swing bias.
Properties visible in this publication
• Initial capital. 100000
• Base currency. USD
• Default order size method. 5% of the total capital in this example
• Pyramiding. 0
• Commission. 0.03 percent
• Slippage. 3 ticks
• Process orders on close. On
• Bar magnifier. Off
• Recalculate after order is filled. Off
• Calc on every tick. Off
• All request.security calls use lookahead = barmerge.lookahead_off
Realism and responsible publication
The strategy is for education and research only. It does not claim any guaranteed edge or future performance. All results in Strategy Tester are hypothetical and depend on the data vendor, costs, and slippage assumptions. Intrabar motion is not modeled inside daily bars so extreme moves and gaps can lead to fills that differ from live trading. The logic is built for standard candles and should not be used on synthetic chart types for execution decisions.
Performance is sensitive to regime structure in the US equity market, which may change over time. The strategy does not protect against single day crash risk inside bars and does not model gap risk explicitly. Past behavior of SPY and the momentum effect does not guarantee future persistence.
Honest limitations and failure modes
• Long sideways regimes with small net change over eighteen months can lead to whipsaw around the zero line.
• Very sharp V shaped reversals after deep declines will often be missed because the model waits for momentum to turn positive again.
• The sample size in a full SPY history is small because regime changes are infrequent, so any test must be interpreted as indicative rather than statistically precise.
• The model is highly dependent on the chosen lookback. Users should test nearby values and validate that behavior is qualitatively stable.
Legal
Education and research only. Not investment advice. You are responsible for your own decisions. Always test on historical data and in simulation with realistic costs before any live use.
Robrechtian Long-Medium Breakout Trend SystemRobrechtian Long–Medium-Term Breakout Trend System
A professional, rule-based trend-following strategy designed to capture large, sustained price movements using pure price action and breakouts.
This system follows long-established trend-following philosophy: no prediction, no volatility targeting, and no profit targets. Only disciplined entries, position additions, and exits driven entirely by trend structure.
Core Principles
Breakout-driven entries: Initial positions are taken only when price breaks above/below the 80-day Donchian channel, confirming a long–medium-term trend shift.
Short-term confirmation: Breakouts must also exceed the 20-day channel, reducing false positives.
Trend-direction filter: A 50-day moving average slope filter ensures alignment with the broader trend.
Explosive bar filter: Entries avoid excessively large, single-candle expansions (>2.5× ATR(20)) to prevent chasing exhaustion spikes.
Pyramiding into strength: Additional units are added only when price makes fresh 20-day breakouts in the direction of the trend. No scaling out. No adding on dips.
Exit only on trend violation: Positions are closed exclusively when price breaks the opposite 80-day channel. This preserves unlimited upside while enforcing disciplined exits.
Pure trend philosophy: No volatility targeting, no smoothing, no discretionary overrides, no optimization for short-term performance.
Intended Use
This system is designed primarily for diversified futures portfolios, where diversification across dozens of globally liquid markets creates robustness and stability. However, it may also be used on individual assets for educational and analytical purposes.
The system embraces the core trend-following logic:
Small losses, big winners, and unlimited upside when trends persist.
⚠️ WARNINGS / DISCLAIMERS
⚠️ Warning 1 — This strategy is not optimized for single stocks
The Robrechtian Trend System is designed for multi-asset futures portfolios, not single equities.
Performance on individual tickers may vary greatly due to lack of diversification.
⚠️ Warning 2 — Trend following includes substantial drawdowns
Deep drawdowns are a normal and expected feature of all long-term trend-following systems.
The strategy does not attempt to smooth returns or manage volatility.
If you seek steady, low-volatility equity curves, this system is not suitable.
⚠️ Warning 3 — No volatility targeting or risk smoothing
This system intentionally avoids volatility-based position sizing.
Trades may experience larger fluctuations than systems using risk parity or vol targeting.
⚠️ Warning 4 — Not financial advice
This script is for educational and research purposes only.
Past performance does not guarantee future results.
Use at your own risk.
⚠️ Warning 5 — TradingView backtests have known limitations
TradingView does not simulate:
futures contract roll logic
slippage
real bid/ask spreads
liquidity conditions
limit-up/limit-down behavior
Results may vary from live market execution.
Strategy: HMA 50 + Supertrend SniperHMA 50 + Supertrend Confluence Strategy (Trend Following with Noise Filtering)
Description:
Introduction and Concept This strategy is designed to solve a common problem in trend-following trading: Lag vs. False Signals. Standard Moving Averages often lag too much, while price action indicators can generate false signals during choppy markets. This script combines the speed of the Hull Moving Average (HMA) with the volatility-based filtering of the Supertrend indicator to create a robust "Confluence System."
The primary goal of this script is not just to overlay two indicators, but to enforce a strict rule where a trade is only taken when Momentum (HMA) and Volatility Direction (Supertrend) are in perfect agreement.
Why this combination? (The Logic Behind the Mashup)
Hull Moving Average (HMA 50): We use the HMA because it significantly reduces lag compared to SMA or EMA by using weighted calculations. It acts as our primary Trend Direction detector. However, HMA can be too sensitive and "whipsaw" during sideways markets.
Supertrend (ATR-based): We use the Supertrend (Factor 3.0, Period 10) as our Volatility Filter. It uses Average True Range (ATR) to determine the significant trend boundary.
How it Works (Methodology) The strategy uses a boolean logic system to filter out low-quality trades:
Bullish Confluence: The HMA must be rising (Slope > 0) AND the Close Price must be above the Supertrend line (Uptrend).
Bearish Confluence: The HMA must be falling (Slope < 0) AND the Close Price must be below the Supertrend line (Downtrend).
The "Choppy Zone" (Noise Filter): This is a unique feature of this script. If the HMA indicates one direction (e.g., Rising) but the Supertrend indicates the opposite (e.g., Downtrend), the market is considered "Choppy" or indecisive. In this state, the script paints the candles or HMA line Gray and exits all positions (optional setting) to preserve capital.
Visual Guide & Signals To make the script easy to interpret for traders who do not read Pine Script, I have implemented specific visual cues:
Green Cross (+): Indicates a LONG entry signal. Both HMA and Supertrend align bullishly.
Red Cross (X): Indicates a SHORT entry signal. Both HMA and Supertrend align bearishly.
Thick Line (HMA): The main line changes color based on the trend.
Green: Bullish Confluence.
Red: Bearish Confluence.
Gray: Divergence/Choppy (No Trade Zone).
Thin Step Line: This is the Supertrend line, serving as your dynamic Trailing Stop Loss.
Strategy Settings
HMA Length: Default is 50 (Mid-term trend).
ATR Factor/Period: Default is 3.0/10 (Standard for trend catching).
Exit on Choppy: A toggle switch allowing users to decide whether to hold through noise or exit immediately when indicators disagree.
Risk Warning This strategy performs best in trending markets (Forex, Crypto, Indices). Like all trend-following systems, it may experience drawdown during prolonged accumulation/distribution phases. Please backtest with your specific asset before using it with real capital.
XAU BUY/SELL Scalping Strategy M5 PROFX:XAUUSD
This XAU/USD Pro Scalping Strategy is tailored specifically for the M5 timeframe , designed to capture rapid Gold price movements. Instead of relying on lagging indicators, this system utilizes advanced Price Action and Market Structure analysis to identify high-probability entry zones.
The core strength of this strategy lies in its built-in Money Management engine and Multi-threaded Trailing Stop system, ensuring capital preservation and profit maximization.
🚀 Key Features:
1. Smart Price Action Recognition:
The algorithm scans for specific market scenarios to apply dynamic Risk:Reward ratios (ranging from 1:1 to 1:3).
Filters out noise and false breakouts using multi-candle analysis.
Auto Position Sizing:
Calculates trade quantity automatically based on your defined Risk % per Trade .
Ensures consistent risk management regardless of the Stop Loss distance.
Intelligent Trailing Stop:
Uses a dynamic trailing mechanism based on "R" multiples (Risk Units).
Automatically secures profits by moving SL based on the specific setup type ("Case") of each trade.
Safety Filters:
Min SL and Max SL inputs prevent trades during periods of extremely low volatility or excessive risk.
⚙️ Settings:
Risk % per Trade: The percentage of equity to risk per trade (Recommended: 1.0% - 2.0%).
Min/Max SL Points: Dynamic boundaries for Stop Loss to adapt to current market volatility.
💡 Recommendations:
Symbol: XAUUSD / Gold - FXCM.
Timeframe: M5.
Best performance during London and New York sessions.
[iQ]PRO Quant GANN FOURIER VZO RANGE+🔮 PRO Quant GANN FOURIER VZO RANGE+
A Highly Adaptive and Proprietary Quantitative Strategy for Precision Market Analysis
This is the official description for the PRO Quant GANN FOURIER VZO RANGE+ strategy, a sophisticated, closed-source system engineered for high-level market engagement. This tool integrates multiple independent quantitative models into a single, cohesive Ensemble Signal, providing an edge through robust, multi-dimensional analysis.
🔬 Core Quantitative Architecture
The strategy is built on the convergence of several powerful, state-of-the-art analytical components, each designed to capture a distinct facet of market dynamics:
Proprietary Gann Swing Models: We utilize a dual-approach to Gann analysis.
Array–Based Gann Swing: A proprietary implementation leveraging advanced Pine Script array structures for dynamic tracking of significant price pivots and structure shifts. This component continuously monitors market momentum and potential areas of interest, including proprietary "ChoCh" (Change of Character) detection—a highly sensitive mechanism for identifying early trend inflection points. This core mechanism provides a high-frequency structural view of the market.
Composite Multi-Timeframe Gann Swing: This model synthesizes traditional swing analysis across two distinct timeframes to filter noise and confirm structural trends, ensuring the system operates with conviction against the backdrop of a higher-level market perspective.
VZO/VSA (Volume Zone Oscillator/Volume Spread Analysis) Hybrid: This module is engineered to analyze the crucial relationship between price momentum and volume flow, specifically using a Volume Zone Oscillator (VZO) approach integrated with Volume Spread Analysis (VSA) principles. It is designed to identify underlying accumulation and distribution activity with a unique dual-timeframe composite for enhanced signal quality.
Trend and Statistical Component: A dedicated module assesses the statistical bias and slope of the aggregated market movement, providing a crucial check against overextension and ensuring alignment with the underlying price regression trajectory.
⚖️ The Ensemble Signal and Trade Logic
All independent signals—Gann Array, Composite Gann, VZO/VSA, and Trend—are processed through a Weighted Ensemble Logic.
Weighted Voting: Each component's signal is assigned a customizable weight (input parameters wGannComp, wVZO, etc.) to reflect its relative importance in the current market environment.
Threshold-Based Decision: The weighted average of all signals results in an Ensemble Signal. Only when this signal decisively exceeds a customizable Signal Threshold does the system generate a Final Signal for trade execution. This rigor is key to filtering lower-conviction setups.
The strategy's execution logic is designed to open and close positions dynamically based on the Final Signal, maintaining maximum control with a default position size of 15% of equity per trade. A dedicated toggle allows for aggressive position management to "stay in" trades longer under specific conditions identified by the proprietary swing models.
⚙️ Strategic Advantages and Exclusivity
This strategy is marked by its extreme adaptability, incorporating features such as:
Higher Timeframe Synthesis: Crucial components utilize multi-timeframe confirmation to validate signals.
Price Smoothing: An optional, light-touch EMA smoothing is applied to the input price data to enhance signal clarity and reduce spurious whipsaws.
Due to the proprietary nature and complexity of the underlying swing detection algorithms and array management, the source code is kept strictly closed-source. This ensures the continued analytical edge and integrity of the model for our exclusive community.
OG INDICATOR TO MESS AROUND WITH, USE RIGHT, AND ENJOY. PRO STRATS COMING TOO
NFA.
MKNiQ
Titan EMA Liquidity [Stansbooth]
🔥 Precision EMA + FVG Liquidity Sweep System
Advanced Buy/Sell Signal Engine for High-Probability Trade Entries
Unlock a new level of precision with this all-in-one market structure indicator built for traders who demand accuracy, clarity, and confidence.
This tool combines EMA trend filtration , Fair Value Gap (FVG) detection , and liquidity sweep analysis to deliver powerful buy and sell signals that align with institutional price behavior.
✅ Key Features
Dynamic EMA Trend Filter:
Identifies true trend direction and filters out low-quality trades. Signals only trigger when momentum aligns with higher-timeframe directional bias.
Smart FVG Detection:
Automatically highlights bullish and bearish Fair Value Gaps, helping you spot premium/discount zones where institutional traders seek entries.
Liquidity Sweep Identification:
Detects equal highs/lows, stop hunts, and engineered liquidity grabs—then confirms reversals when price sweeps liquidity and returns inside structure.
High-Accuracy Signal Engine:
Buy/Sell alerts trigger only when three layers agree:
1. EMA trend alignment
2. FVG confirmation
3. Liquidity sweep completion
This results in cleaner signals , fewer false entries, and strong trend continuation setups.
Optimized for All Market Conditions:
Works for scalping, day trading, and swing trading across Forex, Crypto, Indices, and Stocks.
What This Indicator Helps You Achieve
Capture smart-money style entries with reduced drawdown
Enter after liquidity grabs instead of before them
Avoid chop with EMA-filtered market direction
Spot precision premium/discount zones using automatic FVG mapping
Obtain high-confidence Buy/Sell signals based on institutional concept
Why Traders Love It
This system isn’t just another signal generator—it’s a market-structure aware model that reads the chart the same way professional traders do.
Every signal is based on probability stacking , giving you the clarity and confidence to take the best setups while ignoring noise.
DEMA ATR Strategy [PrimeAutomation]⯁ OVERVIEW
The DEMA ATR Strategy combines trend-following logic with adaptive volatility filters to identify strong momentum phases and manage trades dynamically.
It uses a Double Exponential Moving Average (DEMA) anchored to ATR volatility bands, creating a self-adjusting trend baseline.
When the adjusted DEMA shifts direction, the strategy enters positions and scales out profit in phases based on ATR-driven targets.
This system adapts to volatility, filters noise, and seeks sustained directional moves.
⯁ KEY FEATURES
DEMA-Volatility Hybrid Filter
Uses Double EMA with ATR expansion/compression logic to form a dynamic trend baseline.
Directional Shift Entries
Entries occur when the adjusted DEMA flips trend (bullish crossover or bearish crossunder vs its past value).
Noise Reduction Mechanism
ATR range caps extreme moves and prevents false flips during choppy volatility spikes.
Multi-Level Take Profits
Targets scale out positions at 1×, 2×, and 3× ATR multiples in the trade direction.
Volatility-Adaptive Targets
ATR multiplier ensures profit targets expand/contract based on market conditions.
Single-Direction Exposure
No pyramiding; the strategy flips position only when trend shifts.
Automated Trade Finalization
When all profit targets trigger, the position is fully closed.
⯁ STRATEGY LOGIC
Trend Direction:
DEMA baseline is modified using ATR upper/lower envelopes.
• If the adjusted DEMA rises above previous value → Bullish
• If it falls below previous value → Bearish
Entry Rules:
• Enter Long when bullish shift occurs and no long position exists
• Enter Short when bearish shift occurs and no short position exists
Take Profit Logic:
3 partial exits for each trade based on ATR:
• TP1 = ±1× ATR
• TP2 = ±2× ATR
• TP3 = ±3× ATR
Profit distribution: 30% / 30% / 40%
Exit Conditions:
• Exit when all TPs hit (full scale-out if sum of all TPs 100%)
• Opposite trend signal closes current trade and opens new one
⯁ WHEN TO USE
Trending environments
Medium–high volatility phases
Swing trading and intraday trend plays
Markets that respect momentum continuation (crypto, indices, FX majors)
⯁ CONCLUSION
This strategy blends DEMA trend recognition with ATR-based volatility adaptation to generate cleaner directional entries and structured take-profit exits. It is designed to capture momentum phases while avoiding noise-driven false signals, delivering a disciplined and scalable trend-following approach.
Anchor SafeSwing Gold StrategyOverview:
The Anchor SafeSwing Gold Strategy is designed for users who prefer structured, rule-based swing trading on XAUUSD. It focuses on identifying high-quality trade setups rather than frequent entries.
This strategy analyzes the market using multiple technical indicators and methods—including trend analysis, multi-chart confirmation, and support/resistance evaluation—to identify potential swing points. It also incorporates a dynamic approach to risk management through adaptive stop-loss and take-profit logic.
How the Strategy Works
1. Multi-Chart & Trend Analysis:
The strategy evaluates trend direction using several indicators and multiple charts. This helps determine whether the trend favors long or short setups.
2. Buy/Sell Conditions:
a. Buy Conditions: When the broader trend is identified as bullish, the strategy waits for the formation of a strong support zone before considering a long position.
b. Sell Conditions: When the trend is bearish, it waits for a confirmed resistance zone before initiating short positions.
3. Dynamic Take-Profit Logic
The strategy uses adaptive take-profit behavior based on evolving market conditions. It monitors new support/resistance structures and various overbought/oversold signals to dynamically exit trades.
4. Dynamic and Configurable Stop-Loss:
A flexible stop-loss system adjusts according to volatility and market structure.
Users can modify the stop-loss threshold in the settings based on their own risk tolerance and account size.
Trading Frequency :
This strategy focuses on select, high-quality setups. As a result, trade frequency is relatively low and may vary depending on market conditions. Backtesting may show roughly several trades per month, but actual live performance can differ.
Important Notes
All trading involves risk, and users should evaluate the strategy and adjust settings according to their own risk management preferences.
Safe Supertrend Strategy (No Repaint)Overview
The Safe Supertrend is a repaint-free version of the popular Supertrend trend-following indicator.
Most Supertrend indicators appear perfect on historical charts because they flip intrabar and then repaint after the candle closes.
This version fixes that by using close-of-bar confirmation only, making every trend flip 100% stable, safe, and non-repainting.
Why This Supertrend Doesn’t Repaint
Most Supertrend indicators calculate their trend direction using the current bar’s data.
But during a live candle:
ATR expands and contracts
The upper/lower bands move
Price moves above/below the band temporarily
A false flip appears → then disappears when the candle closes
That is classic repainting.
This indicator avoids all of that by using:
close > upper
close < lower
This means:
Trend direction flips only based on the previous candle,
No intrabar calculations,
No flickering signals,
No “perfect but fake” historical performance.
Every signal you see on the chart is exactly what was available in real-time.
How It Works
Calculates ATR (Average True Range) and SMA centerline
Builds upper and lower volatility bands
Confirms trend flips only after the previous bar closes
Plots clear bull and bear reversal signals
Works on all markets (crypto, stocks, forex, indices)
No repainting, no recalc, no misleading flips.
Bullish Signal (Trend Up)
A bullish trend begins only when:
The previous candle closes above the upper ATR band,
And this flip is fully confirmed.
A green triangle marks the start of a new uptrend.
Bearish Signal (Trend Down)
A bearish trend begins only when:
The previous candle closes below the lower ATR band,
And the downtrend is confirmed.
A red triangle signals the start of a new downtrend.
Inputs
ATR Length - default 10
ATR Multiplier - default 3.0
Works on all timeframes and market
Simple, but powerful.
Why Use This Version Instead of a Regular Supertrend?
Most Supertrends:
Look great historically
But repaint continuously on live charts
Give false trend flips intrabar
Cannot be reliably used in strategies
This version:
Uses strict previous-bar logic
Never repaints trend direction
Works perfectly in live trading
Backtests accurately
Is ideal for algorithmic strategies
Ideal For:
Trend-following strategies
Breakout trading
Algo trading systems
Reversal detection
Filtering market noise
Swing trading & scalping
Final Note
This is a safer, more reliable Supertrend designed for real-world use — not perfect-looking repaint illusions.
If you use Supertrend in your trading system, this no-repaint version ensures your signals are trustworthy and consistent.
Safe Supertrend Strategy (No Repaint)Overview
The Safe Supertrend is a repaint-free version of the popular Supertrend trend-following indicator.
Most Supertrend indicators appear perfect on historical charts because they flip intrabar and then repaint after the candle closes.
This version fixes that by using close-of-bar confirmation only, making every trend flip 100% stable, safe, and non-repainting.
Why This Supertrend Doesn’t Repaint
Most Supertrend indicators calculate their trend direction using the current bar’s data.
But during a live candle:
ATR expands and contracts
The upper/lower bands move
Price moves above/below the band temporarily
A false flip appears → then disappears when the candle closes
That is classic repainting.
This indicator avoids all of that by using:
close > upper
close < lower
This means:
Trend direction flips only based on the previous candle,
No intrabar calculations,
No flickering signals,
No “perfect but fake” historical performance.
Every signal you see on the chart is exactly what was available in real-time.
How It Works
Calculates ATR (Average True Range) and SMA centerline
Builds upper and lower volatility bands
Confirms trend flips only after the previous bar closes
Plots clear bull and bear reversal signals
Works on all markets (crypto, stocks, forex, indices)
No repainting, no recalc, no misleading flips.
Bullish Signal (Trend Up)
A bullish trend begins only when:
The previous candle closes above the upper ATR band,
And this flip is fully confirmed.
A green triangle marks the start of a new uptrend.
Bearish Signal (Trend Down)
A bearish trend begins only when:
The previous candle closes below the lower ATR band,
And the downtrend is confirmed.
A red triangle signals the start of a new downtrend.
Inputs
ATR Length - default 10
ATR Multiplier - default 3.0
Works on all timeframes and market
Simple, but powerful.
Why Use This Version Instead of a Regular Supertrend?
Most Supertrends:
Look great historically
But repaint continuously on live charts
Give false trend flips intrabar
Cannot be reliably used in strategies
This version:
Uses strict previous-bar logic
Never repaints trend direction
Works perfectly in live trading
Backtests accurately
Is ideal for algorithmic strategies
Ideal For:
Trend-following strategies
Breakout trading
Algo trading systems
Reversal detection
Filtering market noise
Swing trading & scalping
Final Note
This is a safer, more reliable Supertrend designed for real-world use — not perfect-looking repaint illusions.
If you use Supertrend in your trading system, this no-repaint version ensures your signals are trustworthy and consistent.
PA Builder [PrimeAutomation]1. PA Builder – Overview
PA Builder is not a fixed strategy; it’s a framework for building strategies. Instead of giving traders one rigid system, it provides a toolbox where entries, exits, filters, risk parameters, and automation rules can all be defined and combined. The core philosophy is confluence: the idea that a trade should only be taken when multiple independent signals agree. The Builder is built around this principle. Every module; trend, reactors, bands, reversals, volume, structure, divergences, externals can be treated as one layer of confidence. The stronger the alignment across layers, the higher the quality of the setup in theory.
In practice, this means PA Builder encourages traders to think in terms of “confluence,” not single indicators. Trend and positioning define whether you should even be looking for longs or shorts. Timing tools such as bands, reversals and candlestick structures determine when inside that broader bias you want to engage. Confirmation tools like volume and flow tell you whether capital is actually supporting the move. Filter systems then ensure that even if everything looks good locally, you still respect higher-timeframe or opposing warnings. The Builder’s philosophy is simple: enter less often, but only when conditions are genuinely in your favour.
2. Core Entry Signal Components
The entry logic in PA Builder is built on a set of signal engines that can be combined in many ways. Trend Signals form a natural foundation. They use low-lag low-pass filters, borrowed from audio signal processing, to extract directional bias from price without the classic delay of classical moving averages. The sensitivity parameter controls how reactive this engine is: lower values favour cleaner trends and fewer whipsaws, while higher values are better suited to short-term intraday trading where speed matters more than smoothness. Many traders start by requiring that Trend Signals show “all bullish” or “all bearish” before allowing any entries in that direction.
Trend signals firing short positions
On top of this directional backbone, the Dynamic Reactor behaves as an adaptive baseline. It accelerates in volatile phases and slows down during consolidation, effectively acting as a moving reference point for both trend and price position. A typical use of this module is to insist that, for long trades, the price sits above a bullish reactor; for shorts, below a bearish one. At the higher-timeframe level, the Quantum Reactor provides a VWAP-style reference that can be anchored to larger candles than the chart you are trading. A common configuration is to trade on a 15-minute chart while requiring that price is above the 4-hour Quantum Reactor for longs or below it for shorts. The “fast” and “slow” options determine how quickly this reference adapts to new information.
Timing is then refined with tools like Quantum Bands, reversals and candle structure analysis. Quantum Bands identify extremes within the current environment. In an uptrend, a tag of the lower band can be treated as a pullback rather than a breakdown; in a downtrend, the upper band acts like a shorting zone. Many traders combine “trend up and above higher-timeframe reactor” with “price temporarily below lower band” to construct a mean-reversion entry inside a larger uptrend. Reversal detection modules examine recent bars to find turning points, with shorter lookbacks capturing fast flips and longer lookbacks tracking deeper structural changes. Candle structure logic goes beyond classical candlestick names and instead focuses on whether price action confirms follow-through or reversion behaviour, with options like “2X” modes that wait for two successive confirmations before acting.
Before and after filtering using reactor applied.
Additional confirmation layers come from Volume Matrix, Money Flow, OSC True7 and divergence detection. Volume and flow tools answer whether actual capital is participating in the move or whether price is drifting on thin activity. OSC True7 categorises the state of the trend into intuitive buckets, strong, healthy, neutral, or exhausted, making it easier to avoid chasing extremes. Divergences between price and momentum can be used either as entry triggers in contrarian systems or as hard filters that block trades when warning signs are present. Finally, two external indicator inputs make it possible to integrate RSI, MACD, custom indicators or even other strategies into the Builder, either as simple thresholds or as comparative logic between two external sources (for example, requiring a fast EMA to be above a slow EMA before allowing longs).
3. Exit System & Trade Management
The exit systems in PA Builder are designed to be as vital as the entry logic. It assumes exits are not an afterthought, but half of the edge. Instead of forcing a single take profit point, the system uses a three-tier structure where you can assign different portions of the position to different targets. A common pattern is to scale out a small portion early (for example at one ATR), another portion at an intermediate level, and keep the largest slice for a deeper move. This creates a natural balance: you book something early to reduce emotional stress, while leaving room to participate in the full potential of a trend.
Targets can be defined using ATR multiples or risk-to-reward ratios that are directly tied to the initial stop distance. Using ATR keeps exits proportional to current volatility. A two ATR target in a quiet environment is very different in absolute price distance from the same multiple in a high-volatility environment, yet conceptually it represents the same “size” move. Risk-to-reward exits build on this by ensuring that if you risk one unit (1R), the reward targets are set at predefined multiples of that risk. This enforces positive expectancy at the structural level: the strategy cannot generate entries with inherently negative payoffs.
Once price begins to move in your favour, trailing logic takes over if you choose to enable it. Trailing can begin immediately from entry or only after a target has been hit. Many users prefer to let TP1 and TP2 behave as fixed profit points and then apply a trailing stop or trailing take profit to the final remainder. That way, routine winners are banked mechanically, while occasional explosive moves can be ridden for as long as the market allows. The breakeven module supports this behaviour by automatically moving stops to entry (or slightly through entry into profit) after a specified condition such as TP1 being hit. This transforms the risk profile mid trade: once breakeven has been secured, remaining size can be managed with much less psychological pressure.
The system also recognises the cost of time. Kill Switch functionality exits trades that have been open too long under mediocre conditions, typically when they are in modest profit but not progressing. This protects you from capital being tied up while better opportunities appear elsewhere. Underlying all of this are several trailing stop mechanisms: percentage-based, tick-based for very short-term strategies, TP linked trailing that activates only once a certain profit threshold has been achieved, and ATR based trailing that automatically scales the trail distance with volatility. Each method serves a slightly different profile of strategy, but all share the same aim: preserve gains and limit downside in a structured way rather than rely on discretionary judgement after the fact.
4. Filters and Risk Management
The filter systems in PA Builder formalise the idea that good trading is often about knowing when not to act. “Do Not Trade” conditions can be configured so that even a perfectly aligned bullish entry stack is overridden if certain bearish evidence is present. These can include higher timeframe reversal structures, powerful opposing divergences, or conflicting signals in key modules. By assigning conditions specifically to “Do Not Long” and “Do Not Short” rather than only to entries, you create asymmetry: buying requires bullish evidence and an absence of strong bearish warnings; selling requires the mirror.
Volatility filters extend this logic to the regime level. Some strategies are inherently suited to low volatility, range bound environments where fading extremes is profitable; others require expansion and energy to function properly. By binding trading permission to volatility ranges, you ensure that a mean-reversion system does not blindly attempt to fade a breakout, and that a momentum system does not spin its wheels in a dead, sideways market. You can even reference volatility from a higher timeframe than the one you trade, so that a five-minute strategy is still aware of the broader one-hour volatility regime it sits inside.
Applied DO NOT TRADE - removes poor signal
Risk management and position sizing are configured so each trade is expressed in units of risk rather than arbitrary size. Leverage, in this framework, is simply a scaling factor for capital efficiency; the actual risk per trade is still controlled by the distance between entry and stop and the percentage of equity you choose to expose. Reinvestment options then decide what proportion of accumulated profit is fed back into position sizing. A more aggressive reinvestment setting accelerates compounding but increases the amplitude of drawdowns; a more conservative one smooths the equity curve at the cost of slower growth. The Base Trade Value parameter ties all of this together by deciding how much nominal capital or how many contracts are committed per trade in light of your maximum allowed simultaneous positions and your intended use of leverage.
External exit conditions provide further flexibility. For example, you might design a system whose entries rely purely on PA Builder’s internal modules, but whose exits use RSI readings, moving average crosses, or a proprietary external indicator. The separation of entry and exit logic allows you to bolt on different behaviours at the tail end of trades while keeping your core signal engine intact. In all cases, the objective is the same: express risk in a controlled, repeatable way that can survive long stretches of unfavourable market conditions.
5. PDT, Cooldowns and Visual Modes
For traders subject to Pattern Day Trading rules, PA Builder includes a day-trade tracking system that counts business days correctly and respects the three-trades-in-five-days limit. This goes beyond simple compliance; it forces discipline. When intraday trading is heavily constrained, you are naturally pushed toward swing-oriented strategies with fewer, more selective entries. The tool visually marks your PDT status so you never inadvertently cross the line and trigger a lockout.
Cooldown systems address another reality: psychological vulnerability after streaks. Following several consecutive wins, many traders unconsciously loosen their standards, take marginal signals, oversize positions, or overtrade. A win-streak cooldown deliberately pauses trading after a configured number of wins, giving you time to reset. The same applies to losing streaks. After a run of losses, the strongest temptation is often to “make it back now,” which is exactly when discipline is weakest. A loss-streak cooldown enforces a break in activity during this high-risk emotional state, helping to prevent cascading damage driven by revenge trading.
Visualisation comes in two main modes. Classic mode emphasises precision: it draws explicit entry lines, stop levels, target levels and fill zones, making it easy to audit risk/reward on each trade, verify that the exit logic behaves as intended, and review historical trades in detail. Modern mode emphasises market feel: instead of focusing on exact levels, it colours candles and backgrounds to reflect momentum, profit state and dynamics.
This helps you see at a glance whether a strategy is operating in a smooth trending environment or a choppy, fragmented one, and whether current trades are broadly working or struggling. Many users develop and debug in Classic mode and then monitor live performance in Modern mode, so both representations become part of the workflow.
6. Strategy Design Workflow, Examples and Cautions
Designing with PA Builder is inherently iterative. You begin with a simple theory and a minimal configuration, perhaps just a trend filter and a basic stop/target structure, and run a backtest. You then examine where the system fails. If you see many losses occurring in counter-trend conditions, you add an additional directional filter or restrict entries with a higher-timeframe reactor condition. If you observe many small whipsaw losses, you might require candle structure confirmation or volume confirmation before allowing an entry. Each change is made one at a time and evaluated. This process gradually builds a layered system where every component has a clear purpose: some reduce drawdown, some increase win rate, some cut out only the worst trades, and others help capture more of the best ones.
A conservative swing strategy might need an agreement between short-term trend signals, a higher-timeframe Quantum position, and a bullish Dynamic Reactor state, while checking that volume supports the move and that no significant bearish reversals or divergences are present on higher timeframes. It might accept relatively few trades, but each trade would be tightly controlled, scaled out over several ATR-based targets and protected with breakeven and trailing logic. On the opposite end, an aggressive scalping configuration would relax some filters, favour faster sensitivities, use short lookback reversals, and tighten stops and targets dramatically, relying on high frequency and careful volatility filtering to maintain edge.
Throughout all of this, overfitting remains the main danger. The more parameters you tune and the more coincidental rules you add to make the backtest equity curve smoother, the more likely it is that you are capturing noise rather than a real, repeatable edge. Signs of overfitting include heavily optimised numeric values with no intuitive justification, large differences between in-sample and out-of-sample results, or strategies that work spectacularly in very specific regimes and collapse elsewhere. To mitigate this, keep strategies as simple as possible, test across different market regimes (bull, bear, range), and accept that robust systems usually look less “perfect” on the historical chart.
Bridging the gap from backtest to live trading is another critical step. Before risking capital, it is wise to paper trade the configuration for a number of trades to confirm that signal frequency, behaviour and execution align with expectations. When going live, starting with minimal size and gradually scaling up based on real-world performance helps manage both financial and psychological risk. If live results diverge significantly from backtest expectations due to slippage, fees, or changing market conditions, you can adjust, reduce size, or temporarily pause rather than commit fully to a failing configuration.
Ultimately, PA Builder is designed to be a tool for building structured, rules-driven trading systems. It gives you the tools to express your ideas, test them, refine them, and run them under controlled risk. It does not remove uncertainty or guarantee results, but it does provide a clear, transparent way to translate trading concepts into executable, testable logic, and to evolve those systems as markets change and your understanding deepens.
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model.
Strategy Logic
Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically.
To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions.
Exit logic includes:
A take-profit at 3× the ATR distance
A stop-loss at 1.5× the ATR distance
An optional early exit if RSI crosses above 70, signaling overbought conditions
Technical Details
Trend Filter: 200 EMA – must be rising and price must be above it
Entry Signal: RSI dips below 40 during an uptrend
Volatility Filter: ATR must be above a user-defined minimum threshold
Stop-Loss: 1.5× ATR below entry price
Take-Profit: 3.0× ATR above entry price
Exit on Overbought: RSI > 70 (optional early exit)
Backtest Settings
Initial Capital: $10,000
Position Sizing: 5% of equity per trade
Slippage: 1 tick
Commission: 0.075% per trade
Trade Direction: Long only
Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD
This model is tuned for positive P&L across trending environments and volatile markets.
Educational Use Only
This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
Qullamagi EMA Breakout Autotrade (Crypto Futures L+S)Title: Qullamagi EMA Breakout – Crypto Autotrade
Overview
A crypto-focused, Qullamagi-style EMA breakout strategy built for autotrading on futures and perpetual swaps.
It combines a 5-MA trend stack (EMA 10/20, SMA 50/100/200), volatility contraction boxes, volume spikes and an optional higher-timeframe 200-MA filter. The script supports both long and short trades, partial take profit, trailing MA exits and percent-of-equity position sizing for automated crypto futures trading.
Key Features (Crypto)
Qullamagi MA Breakout Engine – trades only when price is aligned with a strong EMA/SMA trend and breaks out of a tight consolidation range. Longs use: Close > EMA10 > EMA20 > SMA50 > SMA100 > SMA200. Shorts are the mirror condition with all MAs sloping in the trend direction.
Strict vs Loose Modes – Strict (Daily) is designed for cleaner swing trades on 1H–4H (full MA stack, box+ATR and volume filters, optional HTF filter). Loose (Intraday) focuses on 10/20/50 alignment with relaxed filters for more frequent 15m–30m signals.
Volatility & Volume Filters for Crypto – ATR-based box height limit to detect volatility contraction, wide-candle filter to avoid chasing exhausted breakouts, and a volume spike condition requiring current volume to exceed an SMA of volume.
Higher-Timeframe Trend Filter (Optional) – uses a 200-period SMA on a higher timeframe (default: 1D). Longs only when HTF close is above the HTF 200-SMA, shorts only when it is below, helping avoid trading against dominant crypto trends.
Autotrade-Oriented Trade Management – position size as % of equity, initial stop anchored to a chosen MA (EMA10 / EMA20 / SMA50) with optional buffer, partial take profit at a configurable R-multiple, trailing MA exit for the remainder, and an optional cooldown after a full exit.
Markets & Timeframes
Best suited for BTC, ETH and major altcoin futures/perpetuals (Binance, Bybit, OKX, etc.).
Strict preset: 1H–4H charts for classic Qullamagi-style trend structure and fewer fake breakouts.
Loose preset: 15m–30m charts for higher trade frequency and more active intraday trading.
Always retune ATR length, box length, volume multiplier and position size for each symbol and exchange.
Strategy Logic (Quick Summary)
Long (Strict): MA stack in bullish alignment with all MAs sloping up → tight volatility box (ATR-based) → volume spike above SMA(volume) × multiplier → breakout above box high (close or intrabar) → optional HTF close above 200-SMA.
Short: Mirror logic: bearish MA stack, tight box, volume spike and breakdown below box low with optional HTF downtrend.
Best Practices for Crypto
Backtest on each symbol and timeframe you plan to autotrade, including commissions and slippage.
Start on higher timeframes (1H/4H) to learn the behavior, then move to 15m–30m if you want more signals.
Use the higher-timeframe filter when markets are strongly trending to reduce counter-trend trades.
Keep position-size percentage conservative until you fully understand the drawdowns.
Forward-test / paper trade before connecting to live futures accounts.
Webhook / Autotrade Integration
Designed to work with TradingView webhooks and external crypto trading bots.
Alert messages include structured fields such as: EVENT=ENTRY / SCALE_OUT / EXIT, SIDE=LONG / SHORT, STRATEGY=Qullamagi_MA.
Map each EVENT + SIDE combination to your bot logic (open long/short, partial close, full close, etc.) on your preferred exchange.
Important Notes & Disclaimer
Crypto markets are highly volatile and can change regime quickly. Backtest and forward-test thoroughly before using real capital. Higher timeframes generally produce cleaner MA structures and fewer fake breakouts.
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading leveraged crypto products involves substantial risk of loss. Always do your own research, manage risk carefully, and never trade with money you cannot afford to lose.
EMA Cross + RSI + ADX - Autotrade Strategy V2Overview
A versatile trend-following strategy combining EMA 9/21 crossovers with RSI momentum filtering and optional ADX trend strength confirmation. Designed for both cryptocurrency and traditional futures/options markets with built-in stop loss management and automated position reversals.
Key Features
Multi-Market Compatibility: Works on both crypto futures (Bitcoin, Ethereum) and traditional markets (NIFTY, Bank NIFTY, S&P 500 futures, equity options)
Triple Confirmation System: EMA crossover + RSI filter + ADX strength (optional)
Automated Risk Management: 2% stop loss with wick-touch detection
Position Auto-Reversal: Opposite signals automatically close and reverse positions
Webhook Ready: Six distinct alert messages for automation (Entry Buy/Sell, Close Long/Short, SL Hit Long/Short)
Performance Metrics
NIFTY Futures (15min): 50%+ win rate with ADX filter OFF
Crypto Markets: Requires extensive backtesting before live deployment
Optimal Timeframes: 15-minute to 1-hour charts (patience required for higher timeframes)
Strategy Logic
Entry Signals:
LONG: EMA 9 crosses above EMA 21 + RSI > 55 + ADX > 20 (if enabled)
SHORT: EMA 9 crosses below EMA 21 + RSI < 45 + ADX > 20 (if enabled)
Exit Signals:
Opposite EMA crossover (auto-closes current position)
Stop loss hit at 2% from entry price (tracks candle wicks)
Technical Indicators:
Fast EMA: 9-period (short-term trend)
Slow EMA: 21-period (primary trend)
RSI: 14-period with 55/45 thresholds (momentum confirmation)
ADX: 14-period with 20 threshold (trend strength filter - optional)
Market-Specific Settings
Traditional Markets (NIFTY, Bank NIFTY, S&P Futures, Options)
Recommended Settings:
ADX Filter: Turn OFF (less choppy, cleaner trends)
Timeframe: 15-minute chart
Win Rate: 50%+ on NIFTY Futures
Why No ADX: Traditional markets have more institutional participation and smoother price action, making ADX unnecessary
Cryptocurrency Markets (BTC, ETH, Altcoins)
Recommended Settings:
ADX Filter: Turn ON (ADX > 20)
Timeframe: 15-minute to 1-hour
Extensive backtesting required before live trading
Why ADX: Crypto markets are highly volatile and prone to false breakouts; ADX filters low-quality chop
Best Practices
✅ Backtest thoroughly on your specific instrument and timeframe
✅ Use larger timeframes (1H, 4H) for higher quality signals and better risk/reward
✅ Adjust RSI thresholds based on market volatility (try 52/48 for more signals, 60/40 for fewer but stronger)
✅ Monitor ADX effectiveness - disable for traditional markets, enable for crypto
✅ Proper position sizing - adjust default_qty_value based on your capital and instrument price
✅ Paper trade first - test for 2-4 weeks before risking real capital
Risk Management
Fixed 2% stop loss per trade (adjustable)
Stop loss tracks candle wicks for accurate execution
Positions auto-reverse on opposite signals (no manual intervention needed)
0.075% commission built into backtest (adjust for your broker)
Customization Options
All parameters are adjustable via inputs:
EMA periods (default: 9/21)
RSI length and thresholds (default: 14-period, 55/45 levels)
ADX length and threshold (default: 14-period, 20 threshold)
Stop loss percentage (default: 2%)
Webhook Automation
This strategy includes six distinct alert messages for automated trading:
"Entry Buy" - Long position opened
"Entry Sell" - Short position opened
"Close Long" - Long position closed on opposite crossover
"Close Short" - Short position closed on opposite crossover
"SL Hit Long" - Long stop loss triggered
"SL Hit Short" - Short stop loss triggered
Compatible with Delta Exchange, Binance Futures, 3Commas, Alertatron, and other webhook platforms.
Important Notes
⚠️ Crypto markets require extensive backtesting - volatility patterns differ significantly from traditional markets
⚠️ Higher timeframes = better results - 15min works but 1H/4H provide cleaner signals
⚠️ ADX toggle is critical - OFF for traditional markets, ON for crypto
⚠️ Not financial advice - always conduct your own research and use proper risk management
⚠️ Past performance ≠ future results - backtest results may not reflect live trading conditions
Disclaimer
This strategy is for educational and informational purposes only. Trading futures and options involves substantial risk of loss. Always backtest thoroughly, start with paper trading, and never risk more than you can afford to lose. The author assumes no responsibility for any trading losses incurred using this strategy.
Tight Entry Trend Engine Strategy═══════════════════════════════════════
TIGHT ENTRY TREND ENGINE
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A breakout-based trend-following system designed to capture explosive
moves by entering at precise resistance/support breakouts with minimal
entry risk and massive profit potential.
⚠️ LOW WIN RATE, HIGH REWARD SYSTEM ⚠️
This is NOT a high win-rate strategy. Expect 25-35% winners, but
when it hits, winners are typically 10X+ larger than losers.
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🎯 WHAT THIS SYSTEM DOES
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The Tight Entry Trend Engine identifies powerful breakout opportunities
by detecting when price breaks through established trendlines with
confirmation from higher timeframe trends:
1. DYNAMIC TRENDLINE DETECTION (3 BANKS)
• Automatically draws support and resistance trendlines
• 3 separate "banks" capture short-term, medium-term, and long-term levels
• Each bank has configurable parameters (required pivot touch count,
angle limits, lengths)
2. BREAKOUT ENTRY TIMING
• Enters LONG when price breaks ABOVE resistance trendlines
• Enters SHORT when price breaks BELOW support trendlines
• Entry Alert occurs at the exact moment of breakout = "tight entry"
• Stop-loss placed just below/above the broken trendline (configurable)
3. HIGHER TIMEFRAME TREND FILTER
• Uses Hull Moving Average (HMA) on higher timeframe for trend following
• Auto-adjusts HTF based on your chart timeframe
• Optional filters prevent entries against major trend
• Optional "overextension" filter avoids buying parabolic moves
4. VOLATILITY-ADAPTIVE RISK MANAGEMENT
• Stop-loss calculated using Average True Range (ATR)
• Tighter stops = better R:R
• Profit targets adjust dynamically with volatility
• Breakeven stop moves automatically when in profit
• Extended profit targets when far from HTF trend
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📊 HOW IT WORKS (METHODOLOGY)
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STEP 1: TRENDLINE FORMATION
The system continuously scans for pivot highs and pivot lows to
construct trendlines. You control:
BANK 1 (Short-Term):
- Pivot Length: How many bars to look back for swing points
- Min Touches: How many pivots needed to form a line (default: 3)
- Max Length: How far back lines can reach (default: 180 bars)
- Angle Limits: Maximum steepness allowed for valid trendlines
- Tolerance: How close pivots must align to form horizontal lines
BANK 2 (Medium-Term):
- Slightly longer pivot periods for more significant levels
- Captures medium-term trend structure
- Default Max Length: 200 bars
BANK 3 (Long-Term):
- Focuses on major support/resistance zones
- Often uses horizontal levels (angled lines disabled by default)
- Default Max Length: 300 bars
The system draws RESISTANCE lines (red) above price and SUPPORT
lines (green) below price. These adapt in real-time as new pivots form.
STEP 2: BREAKOUT DETECTION
LONG SIGNALS:
- Price closes above a resistance trendline
- Higher timeframe trend is up (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
SHORT SIGNALS:
- Price closes below a support trendline
- Higher timeframe trend is down (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
The "tight" aspect: Because you're entering right at the trendline
break, your stop-loss can be placed very close (just below the
broken resistance for longs), creating exceptional risk/reward ratios.
STEP 3: POSITION SIZING
Choose between:
- Fixed $ Risk Per Trade: Risk same dollar amount every trade
- % Risk Per Trade: Risk percentage of current equity
Position size automatically calculated based on:
- Your risk amount
- Distance to stop-loss (ATR-based)
- Works with stocks, futures, crypto (auto-adjusts for contract multipliers)
STEP 4: EXIT MANAGEMENT
Multiple exit methods working together:
- PROFIT TARGET: Exits when profit reaches 100x your risk
- EXTENDED PROFIT: Earlier exit (80R) when very far from HTF trend
- STOP LOSS: Fixed ATR-based stop below entry
- HTF TREND EXIT: Exits when price crosses below HTF trend with profit
- BREAKEVEN PULLBACK: Exits if profit drops below 0.6R after reaching breakeven
- PARTIAL PROFITS: Optional - take partial profits at specified R-multiple
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🔧 KEY COMPONENTS EXPLAINED
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HULL MOVING AVERAGE (HMA)
A smoothed moving average that reduces lag compared to traditional
MAs. The system uses HMA on a higher timeframe to determine the
dominant trend direction. You can choose:
- Auto HTF: System picks appropriate HTF based on your chart timeframe
- Manual HTF: You specify the higher timeframe
AVERAGE TRUE RANGE (ATR)
Measures current market volatility. Used for:
- Stop-loss distance (tighter when volatility low)
- Profit targets (larger when volatility high)
- Position sizing (smaller positions in volatile conditions)
- Breakeven trigger distance
TRENDLINE ANGLE FILTERING
Each trendline bank has angle limits to ensure quality:
- Resistance lines: Max downward/upward slope allowed
- Support lines: Max downward/upward slope allowed
- Angles automatically adjust based on current volatility
- Prevents overly steep/unreliable trendlines
SENSITIVITY CONTROL
One master slider adjusts multiple parameters:
- Trendline detection sensitivity
- HTF MA length
- Exit timing
- Auto-adjusts for daily+ timeframes (60% increase)
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⚙️ WHAT YOU SEE ON YOUR CHART
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TRENDLINES:
✓ Red resistance lines above price
✓ Green support lines below price
✓ Orange broken lines (past breakouts)
✓ Lines extend to show current levels
HTF TREND:
✓ Thick colored line showing higher timeframe trend
✓ Color gradient: Red (bearish) → Orange → Yellow → Green (bullish)
✓ 250-bar smoothed curve for visual clarity
ENTRY/EXIT SIGNALS:
✓ Small green dot below bar = Long entry
✓ Small red dot above bar = Short entry
✓ Small red dot above = Long exit
✓ Small black dot below = Short exit
OPTIONAL DETAILED LABELS:
✓ Bank number that triggered entry (Bank 1, 2, or 3)
✓ Exit reason (Profit Target, Stop Loss, HTF Exit, etc.)
✓ Partial profit notifications
POSITION TRACKING:
✓ Yellow dashed line at entry price (extends right)
✓ Green/red fill showing current profit/loss zone
✓ Lime arrows at top = Currently in long position
✓ Red arrows at bottom = Currently in short position
✓ Gray background = No position (flat)
STATS TABLE (Top Right):
✓ Current position (LONG/SHORT/FLAT)
✓ Risk per trade ($ or %)
✓ Entry price
✓ Unrealized P/L in dollars
✓ P/L in R-multiples (how many R's profit/loss)
✓ Average winner/loser R ($ mode) OR CAGR (% mode)
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📈 OPTIMAL USAGE
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BEST ASSETS:
- NASDAQ:QQQ on 1-hour (reg) chart ⭐ (PRIMARY OPTIMIZATION)
- Strong trending stocks: NVDA, AAPL, TSLA, MSFT, GOOGL, AMZN
- High volatility tech stocks
- Crypto: BTC, ETH
- Any liquid asset with clear trends and momentum (GOLD)
AVOID:
- Low volatility stocks
- Ranging/choppy markets
- Penny stocks or illiquid assets
- Assets without clear directional movement
BEST TIMEFRAMES:
- PRIMARY: 1-hour charts (optimal for QQQ)
- ALSO EXCELLENT: 2H, 4H, 8H
- WORKS: 15min, 30min (only momentum leaders, more noise)
- WORKS WITH ADJUSTMENTS: 1D, 2D (decrease trendline pivot lengths)
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📊 BACKTEST RESULTS (QQQ 1H (Reg hours), 1999-2024)
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The system showed on NASDAQ:QQQ 1-hour timeframe (regular hours):
- Total Return: 1,100,000%+ over 24 years
- Total Trades: 500+
- Win Rate: ~20-24% (LOW - this is by design!)
- Average Winner: 8-15% gain
- Average Loser: 2-4% loss
- Win/Loss Ratio: 10:1 (winners much bigger than losers)
- Profit Factor: 3+
- Max Drawdown: 45-50%
- Risk per trade: 3% of capital
KEY INSIGHT: This is a LOW WIN RATE, HIGH REWARD system. You will
lose more trades than you win, but the few winners are so large
they more than compensate for many small losses.
IMPORTANT: These are backtested results using optimal parameters
on historical data. Real trading results will vary based on:
- Your execution and timing
- Slippage and commissions
- Your emotional discipline
- Market conditions during your trading period
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🎓 WHO IS THIS FOR?
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IDEAL FOR:
✓ Swing traders comfortable holding winners for longer period
✓ Part-time traders (1H = check 2-3x per day)
✓ Traders seeking exceptional risk/reward ratios
✓ Those comfortable with low win rates if winners are huge
✓ Technical analysis enthusiasts
✓ Breakout traders
✓ Trend followers
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🚀 GETTING STARTED - STEP BY STEP
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STEP 1: APPLY TO YOUR CHART
- Search "Tight Entry Trend Engine" in indicators
- Click to apply to your chart
- Trendlines and HTF line will appear immediately
STEP 2: CHOOSE YOUR SETTINGS
For BEGINNERS - Use These Settings First:
1. Trade Direction & Filters:
• ENABLE LONGS: ✓ ON
• ENABLE SHORTS: ✗ OFF (start with longs only)
• Sensitivity: 1.0 (default)
• HTF Trend Entry Filter: ✓ ON (safer entries)
• Block Entries When Overextended: ✓ ON (avoid parabolic tops)
2. Position Sizing & Risk:
• Position Sizing: "Per Risk"
• RISK Type: "$ Per Trade"
• Risk Amount: $200 (or 1-3% of your account)
3. Visual Settings:
• Show Support Lines: ✗ OFF (unless trading shorts)
• Show Detailed Entry/Exit Labels: ✓ ON
• Show Stats Table: ✓ ON
• Show Entry Line & P/L Fill: ✓ ON
4. Leave everything else at DEFAULT for now
STEP 3: UNDERSTAND WHAT YOU SEE
When trendlines appear:
- RED lines above = Resistance (watch for price breaking UP through these)
- GREEN lines below = Support (watch for price breaking DOWN)
- When price breaks a red line = Potential LONG entry
- When price breaks a green line = Potential SHORT entry
The HTF trend line (thick colored):
- Green/lime = Strong uptrend (favorable for longs)
- Red = Strong downtrend (favorable for shorts if enabled)
- Orange/yellow = Transitioning
STEP 4: OBSERVE SIGNALS
- Small GREEN dot below bar = System entered LONG
- Small RED dot above bar = System exited LONG
- Check the label to see which "Bank" triggered (Bank 1, 2, or 3)
- Watch the yellow entry line and colored fill show your P/L
STEP 5: PAPER TRADE FIRST
- Use TradingView's paper trading feature
- Watch how signals perform on YOUR chosen asset
- Understand the win rate will be LOW (20-35%)
- Verify that winners are indeed much larger than losers
- Test for at least 20-30 signals before going live
STEP 6: OPTIMIZE FOR YOUR ASSET (OPTIONAL)
If default settings aren't working well:
For FASTER signals (more trades):
- Reduce Pivot Length 1 to 3-4
- Reduce Max Length 1 to 120-150
- Increase Sensitivity to 1.2-1.5
For SLOWER signals (higher quality):
- Increase Pivot Length 1 to 7-10
- Increase Max Length 1 to 250+
- Decrease Sensitivity to 0.7-0.9
For DAILY timeframes:
- Increase all Pivot Lengths by 30-50%
- Increase all Max Lengths significantly
- Sensitivity: 0.6-0.8
═══════════════════════════════════════
⚙️ ADVANCED SETTINGS EXPLAINED
═══════════════════════════════════════
TRENDLINE BANK SETTINGS:
Each bank (1, 2, 3) has these parameters:
- Min Touches: Minimum pivots to form a line
- Lower (2) = More lines, earlier detection
- Higher (4+) = Fewer lines, higher quality
- Pivot Length: Lookback for swing points
- Lower (3-5) = Reacts to recent price action
- Higher (10+) = Only major swing points
- Max Length: How old a trendline can be
- Shorter (100-150) = Only recent lines
- Longer (300+) = Include historical levels
- Tolerance: Alignment strictness for horizontal lines
- Lower (3.0-3.5) = Very strict horizontal
- Higher (4.5+) = More forgiving alignment
- Allow Angled Lines: Enable diagonal trendlines
- ON = Catches sloped support/resistance
- OFF = Only horizontal levels
- Angle Limits: Maximum steepness allowed
- Lower (1-2) = Only gentle slopes
- Higher (4-6) = Accept steeper angles
- Automatically adjusts for volatility
ATR MULTIPLIERS:
- STOP LOSS ATR (0.6): Distance to stop-loss
- Lower (0.4-0.5) = Tighter stops, stopped out more
- Higher (0.8-1.0) = Wider stops, more room
- PROFIT TARGET ATR (100): Main profit target
- This is 100x your risk = 10,000% R:R
- Lower (50-80) = Take profits sooner
- Higher (120+) = Let winners run longer
- BREAKEVEN ATR (40): When to move stop to breakeven
- Lower (20-30) = Protect profits earlier
- Higher (60+) = Give more room before protecting
HIGHER TIMEFRAME:
- Auto HTF: Automatically selects appropriate HTF
- 5min chart → uses 2H
- 15-30min → uses 6H
- 1-4H → uses 2D
- Daily → uses 4D
- HTF MA Length (300): HMA period for trend
- Lower (150-250) = More responsive
- Higher (400-500) = Smoother, less whipsaw
- HTF Trend Following Exit: Exits when crossing HTF
- ON = Additional exit method
- OFF = Rely only on profit targets/stops
- HTF Trend Entry Filter: Only trade with HTF trend
- ON = Safer, fewer signals
- OFF = More aggressive, more signals
- Block Entries When Overextended: Prevents chasing
- ON = Avoids parabolic tops/bottoms
- OFF = Enter all breakouts regardless
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💡 TRADING PHILOSOPHY & EXPECTATIONS
═══════════════════════════════════════
This system is built on one core principle:
"ACCEPT SMALL, FREQUENT LOSSES TO CAPTURE RARE, MASSIVE WINS"
What this means:
- You WILL lose 65%-75% of your trades
- Most losses will be small (1-2R)
- Some winners hit 80R+
- Over time, math works in your favour
Trend Catcher and Mean ReversionPlease DM if you want to use this strategy.
it took long time to make this code profitable using 3 parameters only!
it allow you to:
1- Pyramid as you see fit.
2- allow option to use trend catching strategy ( while keeping mean reversion strategy)
3- Time filter to limit trading and exit at your preferred time.
4- it works for long, short or both positions.
5- has trailing tp as an option as well while keeping initial sl as hard stop
6- tp multiple (of stop loss) is optional
ongoing working for alerts and automation. More on that for subscribers only.
i will charge the minimum fee to utilize this code as we don't need your money but we need people to support our vision.
SwingTrade ADX Strategy v6This is a swing trading strategy that combines VWAP (Volume Weighted Average Price), ADX (Average Directional Index) for trend strength, and volume ratios to generate long/short entry and exit signals. It's designed for daily charts but can be adapted.
#### Key Features:
- **Entries**: Based on VWAP crossovers, rising/falling delta (price deviation from VWAP), ADX trend confirmation, and volume ratios.
- **Exits**: Dynamic exits when VWAP delta reverses after a peak.
- **Filters**: Optional toggles for VWAP signals, ADX, and volume. Backtest date range for custom periods.
- **Visuals**: VWAP line, signal shapes/labels, and an info panel showing key metrics (VWAP Delta %, ADX, Volume Ratio).
- **Alerts**: Built-in alerts for buy/sell entries and exits.
#### How to Use:
1. Apply to your chart (e.g., stocks, forex, crypto).
2. Adjust parameters in the settings (e.g., ADX threshold, volume period).
3. Enable/disable indicators as needed.
4. Backtest using the date filters and review equity curve.
**Disclaimer**: This is for educational purposes only. Past performance is not indicative of future results. Not financial advice—trade at your own risk. Backtest thoroughly and use with proper risk management.
Feedback welcome! If you find it useful, give it a like.
Strategy Builder Pro [ChartPrime]ChartPrime Strategy Creator Overview
The ChartPrime Strategy Builder offers traders an innovative, structured approach to building and testing strategies. The Strategy Creator allows users to combine, test, and automate complex strategies with many parameters.
Key Features of the ChartPrime Strategy Builder
1. Customizable Buy and Sell Conditions
The Strategy Creator provides flexibility in establishing entry and exit rules, with separate sections for long and short strategies. Traders can combine multiple conditions in each section to fine-tune when positions are opened or closed. For instance, they might choose to only buy when the indicator signals a buy and the Dynamic Reactor (a low lag filter) indicator shows a bullish trend. Users are able to pick, mix and match the following list of features:
Signal Mode: Select the type of assistive signals you are requiring. Provided are both trend following signals with self optimization using backtest results as well as reversal signals, aiming to provide real time tops and bottoms in markets. Both these signal modes can be fine tuned using the tuning input to refine signals to a trader's liking. ChartPrime Trend Signals leverage audio engineering inspired techniques and low-pass filters in order to achieve and attempt to produce lower lag response times and therefore are designed to have a uniqueness when compared to more classical trend following approaches.
The Dynamic Reactor: provides a simple band passing through the chart. This can provide assistance in support and resistance locations as well as identifying the trend direction expressed via green and red colors. Taking a moving average and applying unique adaptivity calculations gives this plot a unique and fast behavior.
Candlestick structures: analyze candlestick formation putting a spin on classical candlestick patterns and provide the most relevant formations on the chart. These are not classical and are filtered by further analyzing market activity. A trader's classic with a spin.
The Prime Trend Assistant: provides a trend following dynamic support and resistance level. This makes it perfect to use in confluence or as a filter for other supporting indicators. This is an adaptive trend following system designed to handle volatility leveraging filter kernels as opposed to low pass filters.
Money Flow: with further filters applied for early response to money flow changes in the market. This can be a great filter in trends.
Oscillator reversals: are built in leveraging an oscillator focusing on market momentum allowing users to enter based on market shifts and trends along with reversals.
Volume-Inspired Signals: determine overbought and oversold conditions, adding another layer of analysis to the oscillator. These appear as orange labels, providing a simple reading into a possible reversal.
The Volume Matrix: is a volume oscillator that shows whether money is flowing into or out of the market. Green suggests an uptrend with buyers in control, while red indicates a majority of sellers. By incorporating smoothed volume analysis, it distinguishes between bullish and bearish volumes, offering an early indication of potential trend reversals.
The True 7: is a middle-ranking system that evaluates the strength of a move and the overall trend, offering a numeric or visual representation of trend strength. It can also indicate when a trend is starting to reverse, providing leading signals for potential market shifts. Rather than using an oscillator, this offers the unique edge of falling into set categories, making understanding it simple. This can be a great confluence point when designing a strategy.
Take profits: These offer real-time suggestions from our algorithm on when it might be a good time to take profit. Using these as part of a strategy allows for great entries at bottoms and tops of trends.
Using features such as the Dynamic reactor have dual purposes. Traders can use this as both a filter and an entry condition. This allows for true interoperability when using the Strategy Builder. The above conditions are duplicated for short entries too allowing for symmetrical trading systems. By disabling all of the entry conditions on either long or short areas of the settings will create a strategy that only takes a single type of position. For example; a trader that just wants to take longs can disable all short options.
2. Layered Entries
Layered entries, a feature to enhance the uniqueness in the tool. It allows traders to average into positions as the market moves, rather than committing all capital at once. This feature is particularly useful for volatile markets where prices may fluctuate substantially. The Strategy Builder lets users adjust the number of layered entries, which can help in managing risk and optimizing entry points as well as the aggressiveness of the safety orders. With each safety order placed the system will automatically and dynamically scale into positions reducing the average entry price and hence dynamically adjust the potential take profits. Due to the potential complexities of exiting during multiple orders, a smart system is employed to automatically take profits on the layered system aiming to take profits at peaks of trends.
Users are able to override this smart TP system at the bottom of the settings instead targeting percentage profits for both short and long positions.
Entries lowering average buy price
The ability to adjust how quickly the system layers into positions can also be adjusted via the layered entries drop down between fast and slow mode where the slow mode will be more cautious when producing new orders.
3. Flexible Take Profit (TP) and Stop Loss (SL) Options
Traders can set their TP and SL levels according to various parameters, including ATR (Average True Range), risk-reward ratio, trailing stops, or specific price changes. If layered entries are active, an automatic TP method is applied by default, though traders can manually specify TP values if they prefer. This setup allows for precise control over trade exits, tailored to the strategy’s risk profile.
Provided options
The ability to use external take profits and stop losses is also provided. By loading an indicator of your choice the plots will be added to the chart. By navigating to the external sources area of the settings, users can select this plot and use it as part of a wider trading system.
Example: Let’s say a user has entries based on the inbuilt trend signals and wishes to exit whenever the RSI crosses above 70, they can add RSI to the chart, select crossing up and enter the value of 70.
4. Integrated Reinvestment for Compounding Gains
The reinvestment option allows traders to reinvest a portion of their gains into future trades, increasing trade size over time and benefiting from compounding. For example, a user might set 30% of each trade's profit to reinvest, with the remaining 70% allocated for risk management or additional safety orders. This approach can enhance long-term growth while balancing risk.
Generally in trading it can be a good approach to take profits so we suggest a healthy balance. This setting is generally best used for slow steady strategies with the long term aim of accumulating as much of the asset as possible.
5. Leverage and Position Sizing
Users can configure leverage and position sizing to simulate varying risk levels and capital allocations. A dashboard on the interface displays margin requirements based on the selected leverage, allowing traders to estimate trade sizes relative to their available capital. Whenever using leverage especially with layered entries it’s important to keep a close eye on the position sizes to avoid potential liquidations.
6. Pre-Configured Strategies for Immediate Testing
For users seeking a starting point, ChartPrime includes a range of preset strategies. These were developed and backtested by ChartPrime’s team. This allows traders to start with a stable base and adapt it to their own preferences. It is vital to understand that historical performance doesn't guarantee future success, and traders should be mindful of overfitting. These pre-built configurations offer a structured way and base to design strategies off of. These are also subject to changing results as new price action arrives and they become outdated. They serve the purpose of simply being example use cases.
7. In-Depth Specific Backtesting Ranges
The Strategy Builder includes backtesting capabilities, providing a clear view of how different setups would have performed over specified time periods. Traders can select date ranges to target specific market conditions, then review results on TradingView to see how their strategies perform across different market trends.
Example Use Case: Developing a Strategy
Consider a trader who is focused on long positions only and prefers a lower-risk strategy (note these tools can be used for all assets; we are using an undisclosed asset as an example). Using the Strategy Builder, they could:
- Disable short conditions.
- Set long entry rules to trigger when both the ChartPrime oscillator and Quantum Reactor indicators show bullish signals.
- Enable layered entries to improve average entry prices by adding to positions during market dips.
- Run a backtest over a two-year period to see historical performance trends, making adjustments as needed.
The backtest will show where entries and exits would have occurred and how layered entries may have impacted profitability.
8. Iterative design
Strategy builders and creating a strategy is often an iterative process. By experimenting and using logic; a trader can arrive at a more sustainable system. Analyzing the shortcomings of your strategy and iteratively designing and filtering them out is the goal. For example; let’s say a strategy has high drawdown, a user would want to tighten stop losses for example to reduce this and find a balance point between optimizing winning trades and reducing the drawdown. When designing a strategy there are generally tradeoffs and optimizing taking into consideration a wide range of factors is key. This also applies to filtering techniques, entries and exits and every variable in the strategy.
Let’s say a strategy was taking too many long positions in a downtrend and after you’ve analyzed the data, you come to the conclusion this needs to be solved. Filtering these using built in trend following tools can be a great approach and refining with logic is a great approach.
The Strategy Builder also takes into consideration those who seek to automate especially via reinvesting and leverage features.
Considerations
The ChartPrime Strategy Builder aims to help traders build clear, rule-based strategies without excessive complexity. As with all backtesting tools, it's crucial to understand that historical performance doesn't guarantee future success, and traders should be mindful of overfitting. This tool offers a structured way to test strategies against various market conditions, helping traders refine their approaches with data-driven insights. Traders should also ensure they enter the correct fees when designing strategies and ensure usage on standard candle types.
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
TrendSync Pro (SMC)📊 TrendSync Pro (SMC) – Advanced Trend-Following Strategy with HTF Alignment
Created by Shubham Singh
🔍 Strategy Overview
TrendSync Pro (SMC) is a precision-based smart trend-following strategy inspired by Smart Money Concepts (SMC). It combines: Real-time pivot-based trendline detection
Higher Time Frame (HTF) filtering to align trades with dominant trend
Risk management via adjustable Stop Loss (SL) and Take Profit (TP)
Directional control — trade only bullish, bearish, or both setups
Realistic backtesting using commissions and slippage
Pre-optimized profiles for scalpers, intraday, swing, and long-term traders
🧠 How It Works:
🔧 Strategy Settings Image:
beeimg.com
The strategy dynamically identifies trend direction by using swing high/low pivots. When a new pivot forms: It draws a trendline from the last significant pivot
Detects whether the trend is up (based on pivot lows) or down (based on pivot highs)
Waits for price to break above/below the trendline
Confirms with HTF price direction (HTF close > previous HTF close = bullish)
Only then it triggers a long or short trade
It exits either at TP, SL, or a manual trendline break
🛠️ Adjustable Parameters:
Trend Period: Length for pivot detection (affects sensitivity of trendlines)
HTF Timeframe: Aligns lower timeframe entries with higher timeframe direction
SL% and TP%: Customize your risk-reward profile
Commission & Slippage: Make backtests more realistic
Trade Direction: Choose to trade: Long only, Short only, or Both
🎛️ Trade Direction Control:
In settings, you can choose: Bullish Only: Executes only long entries
Bearish Only: Executes only short entries
Both: Executes both long and short entries when conditions are met
This allows you to align trades with your own market bias or external analysis.
📈 Entry Logic: Long Entry:
• Price crosses above trendline
• HTF is bullish (HTF close > previous close)
• Latest pivot is a low (trend is considered up)
Short Entry:
• Price crosses below trendline
• HTF is bearish (HTF close < previous close)
• Latest pivot is a high (trend is considered down)
📉 Exit Logic: Hit Take Profit or Stop Loss
Manual trendline invalidation: If price crosses opposite of the trend direction
⏰ Best Timeframes & Recommended Settings:
Scalping (1m to 5m):
HTF = 15m | Trend Period = 7
SL = 0.5% | TP = 1% to 2%
Intraday (15m to 30m):
HTF = 1H | Trend Period = 10–14
SL = 0.75% | TP = 2% to 3%
6 Hour Trading (30m to 1H):
HTF = 4H | Trend Period = 20
SL = 1% | TP = 4% to 6%
Swing Trading (4H to 1D):
HTF = 1D | Trend Period = 35
SL = 2% | TP = 8% to 12%
Long-Term Investing (1D+):
HTF = 1W | Trend Period = 50
SL = 3% | TP = 15%+
Note: These are recommended base settings. Adjust based on volatility, asset class, or personal trading style.
📸 Testing Note:
beeimg.com
TradingView limits test length to 20k bars (~40 trades on smaller timeframes). To show long-term results: Test on higher timeframes (e.g., 1H, 4H, 1D)
Share images of backtest result in description
Host longer test result screenshots on Imgur or any public drive
📍 Asset Behavior Insight:
This strategy works on multiple assets, including BTC, ETH, etc.
Performance varies by trend strength:
Sometimes BTC performs better than ETH
Other times ETH gives better results
That’s normal as both assets follow different volatility and trend behavior
It’s a trend-following setup. Longer and clearer the trend → better the results.
✅ Best Practices: Avoid ranging markets
Use proper SL/TP for each timeframe
Use directional filter if you already have a directional bias
Always forward test before going live
⚠️ Trading Disclaimer:
This script is for educational and backtesting purposes only. Trading involves risk. Always use risk management and never invest more than you can afford to lose.
