3-Minute RSI and EMA Crossover Strategy 3-Minute RSI and EMA Crossover Sell Strategy with Exit Conditions and Re-entry
Media Móvil Exponencial (EMA)
Real-Time EMA Cross Strategy For Fast Scalping📊 Overview
A professional-grade EMA crossover strategy with real-time execution capabilities. Designed for traders who need instant signal execution and seamless position management, this strategy adapts to any trading style with fully customizable EMA periods.
⚡ Core Features
Instant Execution Technology: Enter/exit positions immediately when signals occur
Seamless Position Switching: Automatically reverses positions without gaps or delays
Customizable EMA Periods: Adapt to any market or timeframe with adjustable settings
Real-Time & Bar-Close Modes: Choose your execution preference
Smart Position Management: No overlapping positions, clean entries and exits
Professional Dashboard: Live monitoring of indicators and position status
🎯 Ideal For
Scalpers requiring instant execution
Day traders seeking responsive strategies
Swing traders who need reliable crossover signals
Anyone looking for a clean, professional trading system
💎 What Makes This Special
No Lag: Real-time mode executes trades the moment crossover occurs
Clean Code: Optimized Pine Script v5 with best practices
Visual Clarity: Color-coded zones, clear signal markers, and info panel
Flexibility: Works across all timeframes and markets
Professional Grade: Includes proper position sizing and risk management
📈 How It Works
Long Signal: Fast EMA crosses above Slow EMA
Short Signal: Fast EMA crosses below Slow EMA
Position Management: Automatic reversal on opposite signals
Execution Options: Choose between instant or bar-close execution
⚙️ Customization
Adjust both EMA periods to match your strategy (2/5, 4/9, 9/21, 12/26, etc.)
Toggle real-time execution on/off
Full control over position sizing
Customizable visual elements
🔔 Built-in Alerts
Long entry signals
Short entry signals
Position reversal notifications
📝 Tips for Best Results
Lower timeframes (1-15min) for scalping with fast EMAs
Higher timeframes (1H-4H) for swing trading with slower EMAs
Test different EMA combinations to find your edge
Always use proper risk management
🚀 Version 3 Improvements
Enhanced crossover detection algorithm
Improved real-time execution logic
Better position management
Cleaner visual interface
More reliable signal generation
5-min Strat Strategy V2 (With Stop Loss)README: 5-min Strat Strategy V2 – $7,500 Stop Loss Version
✅ Description
This is a rules-based intraday trading strategy developed for use on futures contracts like MNQ (Micro Nasdaq) or MES (Micro S&P). It focuses on momentum-based breakout entries above pre-market highs, during regular trading hours, and uses EMAs to define trend alignment.
⚙️ Strategy Components
✅ Trade Type
Long-Only strategy
Entry and exit based on EMAs, price position, and time windows
✅ Time Frame
Built for 5-minute charts
✅ Symbols
Optimized for MNQ (Micro Nasdaq Futures)
Works on MES or other U.S. index futures with similar structure
📅 Time Windows
Pre-Market Hours (PMH/PML): 04:00 – 09:30 AM EST
Regular Trading Hours (RTH): 09:30 AM – 4:00 PM EST
Auto Exit Time: 4:59 PM EST (to comply with prop firm rules)
📌 Entry Conditions (Long)
48 EMA > 200 EMA (Bullish alignment)
Price > Locked Pre-Market High
Green Candle (close > open)
During RTH (9:30–16:00 EST)
Cooldown: Must wait 4 candles after last entry
Max Trades per Day: 3
💥 Exit Conditions
Primary Exit: Close below the 48 EMA
Max Loss Exit: Stop loss set to $7,500 per trade
EOD Exit: All positions are closed at 4:59 PM EST
💰 Risk Management
Contracts: 6 Micro contracts per trade
Stop Loss: Dynamic point-based SL calculated based on:
MNQ point value = $20/point per contract
30 contracts = $120/point
Max SL points = $7,500 / $120 = 62.5 points
📊 Key Variables for Logging
Parameter Value
Max Stop Loss $7,500
Position Size 30 Micro Contracts - ***Varies depending on account size***
Cooldown Bars 4 (20 min)
Max Daily Trades 3
Strategy Version V2 – $7.5K SL
Quantura - Quantified Price Action StrategyIntroduction
“Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices.
Originality & Value
The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of:
Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity.
Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs.
RSI filter: Can be set to normal or aggressive, confirming momentum before trades.
Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies.
EMA filter: Aligns trades with the broader market trend.
Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions.
This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow.
Functionality & Indicators
Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap.
Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection.
RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness.
FVG filter: Adds validation by requiring price interaction with inefficiency zones.
EMA filter: Ensures longs are above EMA and shorts below EMA.
Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status.
Parameters & Customization
Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options.
Liquidity filter: Mode (Run or Sweep), display, and swing length.
RSI: Enable/disable, length, and style (normal or aggressive).
Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles.
EMA: Length, enable/disable, and visualization.
Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing.
Visualization: Custom candle coloring and optional overlay for better clarity.
Default Properties (Strategy Settings)
Initial Capital: 10,000 USD
Position Size: 100% of equity per trade (backtest default)
Commission: 0.1%
Slippage: 1
Pyramiding: 0 (only one position at a time)
Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%.
Backtesting & Performance
Backtests on XPTUSD over 2.5 years with the default settings produced:
164 trades
67.68% win rate
Profit factor: 1.7
Maximum drawdown: 27.81%
These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (164) is sufficient for statistical analysis, results may vary across markets and timeframes.
Risk Management
Three configurable take-profit levels with percentage allocation.
Initial stop-loss based on user-defined percentage.
Dynamic stop-loss that adjusts with market movement.
Break-even logic that shifts stops to entry after predefined gains.
Position sizing based on risk percentage of equity.
This framework allows both conservative and aggressive configurations, depending on user preference.
Limitations & Market Conditions
Works best in volatile and liquid markets such as crypto, metals, indices, and FX.
May produce false signals in low-volume or sideways environments.
Unexpected news or macro events can override technical conditions.
Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use.
Usage Guide
Add “Quantura – Quantified Price Action Strategy” to your chart.
Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe.
Configure risk management: take-profits, stop-loss, and risk-per-trade percentage.
Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions.
Optimize parameters before applying the strategy to different markets.
Author & Access
Developed 100% by Quantura. Published as an Invite-Only script.
Important
This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Quantura - Quantitative AlgorythmIntroduction
“Quantura – Quantitative Algorithm” is an invite-only Pine Script strategy designed for multi-timeframe analysis, combining technical filters with user-adjustable fundamental sentiment. It was primarily developed for cryptocurrency markets but can also be applied across other assets such as Forex, stocks, and indices. The goal is to generate structured trade signals through a confluence of techniques rather than relying on a single indicator.
Originality & Value
Quantura is not a simple mashup of indicators. Its originality comes from how multiple layers of analysis are integrated into a single decision framework . Instead of showing indicators separately, the strategy only issues trades when several conditions align simultaneously:
RSI entry triggers confirm overbought/oversold reversals.
Market structure on a higher timeframe confirms trend direction.
Order block detection highlights zones of concentrated supply and demand.
Premium/Discount zones identify potential over- and undervaluation.
HTF EMA provides trend confirmation.
Optional candlestick patterns strengthen reversal or continuation signals.
An optional correlation filter compares the main asset to a reference instrument.
This design forces agreement between different methodologies (momentum, structure, value, volume, sentiment), which reduces noise compared to using them in isolation.
Functionality & Indicators
Entry trigger: RSI exits from extreme zones.
Filters: Only valid when all selected filters (HTF structure, EMA, order blocks, premium/discount, candlesticks, correlation, volume) confirm the direction.
Fundamental bias: User-defined sentiment and analysis settings (bullish, bearish, neutral) influence whether long or short trades are permitted.
Exits: ATR-based take profit and stop loss, with optional breakeven, opposite-signal exit, and session-end exit.
Visualization: Buy/Sell markers, trend-colored candles, and an optional dashboard summarizing indicator status.
Parameters & Customization
Timeframes: Independent HTF and LTF selection.
Trading direction: Long / Short / Both.
Session and weekday filters.
RSI length and thresholds.
Filters: HTF structure, order blocks, premium/discount, EMA, candlestick, ATR volatility, volume zones, correlation.
Exit rules: ATR multipliers for TP/SL, breakeven logic, session-end exit, opposite-signal exit.
Visuals: Toggle signals, candles, dashboard, custom colors.
Default Properties (Strategy Settings)
Initial Capital: 100,000 USD
Position Size: 15% of equity per trade
Commission: 0.25%
Slippage: enabled
Pyramiding: 0 (one position at a time)
Note: The position sizing of 15% equity per trade is intentionally set for backtesting demonstration. In real trading, risking this much is considered aggressive. Most traders prefer to risk 1-5% of equity, and rarely above 10%.
Backtesting & Performance
Backtests on BTCUSD (2 years) with the above defaults showed:
112 trades
Win rate: 40%
Profit factor: 1.4
Maximum drawdown: 34%
These results illustrate how the confluence model behaves, but they are not predictive of future performance . The trade sample size (72 trades) is below the 100+ usually recommended for statistical robustness. Users should re-test with their own preferred symbols, settings, and timeframes.
Risk Management
ATR-based stops and targets scale with volatility.
Commission and slippage are included by default for realistic modeling.
Opposite-signal exit helps capture trend reversals.
Session-end exit can close intraday positions before illiquid hours.
Breakeven option protects profits when available.
Although the default allocation uses 15% per trade for demonstration, this is not a recommendation. Users are encouraged to adjust risk sizing downwards to sustainable levels (commonly 1-5%).
Limitations & Market Conditions
Performs best in volatile, liquid markets (e.g., crypto).
May struggle in prolonged sideways markets with low volatility.
News events and fundamentals outside user inputs can override signals.
Backtests below 100 trades should be considered exploratory, not statistically conclusive.
Usage Guide
Add “Quantura – Quantitative Algorithm” to your chart in strategy mode.
Select HTF and LTF timeframes, trading direction, and session filters.
Configure confluence filters (structure, EMA, order blocks, premium/discount, candlestick, correlation, volume).
Set sentiment and analysis bias in fundamental settings.
Adjust ATR multipliers and exits.
Review buy/sell signals and analyze performance in the Strategy Tester.
Author & Access
Developed 100% by Quantura . Distributed as an Invite-Only script . Details are provided in the Author’s Instructions field.
Important: This description complies with TradingView’s Script Publishing Rules and House Rules. It does not guarantee profitability, avoids unrealistic claims, and explains how the strategy integrates multiple methods into a coherent decision framework.
CDC BACKTEST (MACD) FIX AMOUNT $200k per trade This strategy implements an Exponential Moving Average (EMA) Crossover System designed for backtesting and performance evaluation. EMA 12,26 (MACD)
The trading logic is based on the crossover between two EMAs — a short-term EMA (12) and a long-term EMA (26) — which serves as a momentum-based signal for trend identification.
Buy Condition:
A long (buy) position is entered when the 12-period EMA crosses above the 26-period EMA, indicating a potential upward trend or bullish momentum.
Sell Condition:
A position is closed, or a short (sell) position is opened, when the 12-period EMA crosses below the 26-period EMA, signaling a potential downward trend or bearish momentum.
Position Sizing:
Each trade with a fixed position size of 200,000 USD (default), while the starting account balance is set at 400,000 (USD).
Both the fixed trade amount and the initial balance are user-adjustable parameters, allowing flexibility for different risk preferences and portfolio sizes.
WIN1! • Crossing EMAs• (By Mesquita, v7)Moving average crossover strategy for intraday movements, especially in the continuous index (WIN1!) on the Brazilian stock exchange B³. The strategy is customizable for time windows, has a filter for trades only above the long-term average, whether only long, only short, or both, with or without stop loss.
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
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TAGS:
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trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
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CATEGORY:
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Strategies
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CHART SETUP RECOMMENDATIONS:
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For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
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COMPLIANCE NOTES:
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✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
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Turtle Strategy - Triple EMA Trend with ADX and ATRDescription
The Triple EMA Trend strategy is a directional momentum system built on the alignment of three exponential moving averages and a strong ADX confirmation filter. It is designed to capture established trends while maintaining disciplined risk management through ATR-based stops and targets.
Core Logic
The system activates only under high-trend conditions, defined by the Average Directional Index (ADX) exceeding a configurable threshold (default: 43).
A bullish setup occurs when the short-term EMA is above the mid-term EMA, which in turn is above the long-term EMA, and price trades above the fastest EMA.
A bearish setup is the mirror condition.
Execution Rules
Entry:
• Long when ADX confirms trend strength and EMA alignment is bullish.
• Short when ADX confirms trend strength and EMA alignment is bearish.
Exit:
• Stop Loss: 1.8 × ATR below (for longs) or above (for shorts) the entry price.
• Take Profit: 3.3 × ATR in the direction of the trade.
Both parameters are configurable.
Additional Features
• Start/end date inputs for controlled backtesting.
• Selective activation of long or short trades.
• Built-in commission and position sizing (percent of equity).
• Full visual representation of EMAs, ADX, stop-loss, and target levels.
This strategy emphasizes clean trend participation, strict entry qualification, and consistent reward-to-risk structure. Ideal for swing or medium-term testing across trending assets.
(5m) EMA Cross + RSI + Stoch + ATR Strategy Psammodromus1979Indicators
EMA4
EMA9
EMA20
EMA50
RSI
STOCHASTIC
ATR
With buy/sell indicators directly on main chart
It worked for me when waited for retracement on EMA50
Didn't work when on accumulation.
EMA Trend Buy sell strategyThis strategy is built to help investors get into a trend safely and smartly — without rushing and without getting in and out too often.
When to Buy:
First Signal – Small Step In (50% Buy)
When the short-term trend (EMA 18) turns positive and goes above the medium trend (EMA 33),
👉 we buy half of our planned position.
This is an early warning that a new upward trend might be starting.
Second Signal – Full Confidence (Buy other 50%)
If the medium-term trend (EMA 33) also crosses above the long-term (EMA 50),
👉 we buy the other half of the position.
Now we’re more confident that the trend is real.
When to Sell:
First Warning – Reduce Position (Sell 50%)
If EMA 33 falls below EMA 50,
👉 we sell half of the position to reduce risk.
Trend Reversal – Exit Completely (Sell the rest)
If EMA 18 also falls below EMA 33,
👉 we sell the remaining half and leave the trade fully.
Why This Strategy?
📉 We don’t jump in all at once.
→ We wait for confirmation before going full in.
⏳ We stay in the trade as long as the trend is healthy.
→ No overtrading or reacting to small moves.
📊 We get out slowly, not suddenly.
→ This helps protect profits and avoid emotional decisions.
BTC 5-MA Multi Cross Strategy By Hardik Prajapati Ai TradelabThis strategy is built around the five most powerful and commonly used moving averages in crypto trading — 5, 20, 50, 100, and 200-period SMAs (Simple Moving Averages) — applied on a 1-hour Bitcoin chart.
Core Idea:
The strategy aims to identify strong bullish trends by confirming when the price action crosses above all key moving averages. This alignment of multiple MAs indicates momentum shift and helps filter out false breakouts.
⸻
⚙️ How It Works:
1. Calculates 5 Moving Averages:
• 5 MA → Short-term momentum (fastest signal)
• 20 MA → Near-term trend confirmation
• 50 MA → Mid-term trend filter
• 100 MA → Long-term trend foundation
• 200 MA → Macro-trend direction (strongest support/resistance)
2. Buy Condition (Entry):
• A Buy is triggered when:
• The price crosses above the 5 MA, and
• The closing price remains above all other MAs (20, 50, 100, 200)
This signals that momentum is aligned across all time horizons — a strong uptrend confirmation.
3. Sell Condition (Exit):
• The position is closed when price crosses below the 20 MA, showing weakness in short-term momentum.
4. Visual Signals:
• 🟢 BUY triangle below candles → Entry signal
• 🔴 SELL triangle above candles → Exit signal
• Colored MAs plotted for trend clarity.
⸻
📈 Recommended Usage:
• Chart: BTC/USDT
• Timeframe: 1 Hour
• Type: Trend-following crossover strategy
• Ideal for: Identifying major breakout moves and confirming trend reversals.
⸻
⚠️ Notes:
• This script is meant for educational and backtesting purposes only.
• Always apply additional confirmation tools (like RSI, Volume, or VIX-style filters) before live trading.
• Works best during trending markets; may produce whipsaws in sideways zones.
Universal Breakout Strategy [KedArc Quant]Description:
A flexible breakout framework where you can test different logics (Prev Day, Bollinger, Volume, ATR, EMA Trend, RSI Confirm, Candle Confirm, Time Filter) under one system.
Choose your breakout mode, and the strategy will handle entries, exits, and optional risk management (ATR stops, take-profits, daily loss guard, cooldowns).
An on-chart info table shows live mode values (like Prev High/Low, Bollinger levels, RSI, etc.) plus P&L stats for quick analysis.
Use it to compare which breakout style works best on your instrument and timeframe, whether intraday, swing, or positional trading
🔑 Why it’s useful
* Flexibility: Switch between breakout strategies without loading different indicators.
* Clarity: On-chart info table displays current mode, relevant indicator levels, and live strategy P&L stats.
* Testing efficiency: Quickly A/B test different breakout styles under the same backtest environment.
* Transparency: Every trade is rule-based and displayed with entry/exit markers.
🚀 How it helps traders
* Lets you experiment with breakout strategies quickly without loading multiple scripts.
* Helps identify which breakout method fits your instrument & timeframe.
* Gives clear on-chart visual + statistical feedback for confident decision-making.
⚙️ Input Configuration
* Breakout Mode → choose which strategy to test:
* *Prev Day* → breakouts of yesterday’s High/Low.
* *Bollinger* → Upper/Lower BB pierce.
* *Volume* → Breakout confirmed with volume above average.
* *ATR Stop* → Wide range breakout using ATR filter.
* *Time Filter* → Breakouts inside defined session hours.
* *EMA Trend* → Breakouts only in EMA fast > slow alignment.
* *RSI Confirm* → Breakouts with RSI confirmation (e.g. >55 for longs).
* *Candle Confirm* → Breakouts validated by bullish/bearish candle.
* Lookback / ATR / Bollinger inputs → adjust sensitivity.
* Intrabar mode → option to evaluate breakouts using bar highs/lows instead of closes.
* Table options → show/hide info table, show/hide P&L stats, choose corner placement.
📈 Entry & Exit Logic
* Entry → occurs when breakout condition of chosen mode is met.
* Exit → default exits via opposite signals or optional stop/target if enabled.
* Session filter → optional auto-flat at session end.
* P&L management → optional daily loss guard, cooldown between trades, and ATR-based stop/take profit.
❓ FAQ — Choosing the best setup
Q: Which strategy should I use for which chart?
* *Prev Day Breakouts*: Best on indices, FX, and liquid futures with strong daily levels.
* *Bollinger*: Works well in range-bound environments, or crypto pairs with volatility compression.
* *Volume*: Good on equities where breakout strength is tied to volume spikes.
* *ATR Stop*: Suits volatile instruments (commodities, crypto).
* *EMA Trend*: Useful in trending markets (stocks, indices).
* *RSI Confirm*: Adds momentum filter, better for swing trades.
* *Candle Confirm*: Ideal for scalpers needing visual confirmation.
* *Time Filter*: For intraday traders who want signals only in high-liquidity sessions.
Q: What timeframe should I use?
* Intraday traders → 5m to 15m (Time Filter, Candle Confirm).
* Swing traders → 1H to 4H (EMA Trend, RSI Confirm, ATR Stop).
* Position traders → Daily (Prev Day, Bollinger).
* Breakout
A trade entry condition triggered when price crosses above a resistance level (for longs) or below a support level (for shorts).
* Prev Day High/Low
Formula:
Prev High = High of (Day )
Prev Low = Low of (Day )
* Bollinger Bands
Formula:
Basis = SMA(Close, Length)
Upper Band = Basis + (Multiplier × StdDev(Close, Length))
Lower Band = Basis – (Multiplier × StdDev(Close, Length))
* Volume Confirmation
A breakout is only valid if:
Volume > SMA(Volume, Length)
* ATR (Average True Range)
Measures volatility.
Formula:
ATR = SMA(True Range, Length)
where True Range = max(High–Low, |High–Close |, |Low–Close |)
* EMA (Exponential Moving Average)
Weighted moving average giving more weight to recent prices.
Formula:
EMA = (Price × α) + (EMA × (1–α))
with α = 2 / (Length + 1)
* RSI (Relative Strength Index)
Momentum oscillator scaled 0–100.
Formula:
RSI = 100 – (100 / (1 + RS))
where RS = Avg(Gain, Length) ÷ Avg(Loss, Length)
* Candle Confirmation
Bullish candle: Close > Open AND Close > Close
Bearish candle: Close < Open AND Close < Close
Win Rate (%)
Formula:
Win Rate = (Winning Trades ÷ Total Trades) × 100
* Average Trade P&L
Formula:
Avg Trade = Net Profit ÷ Total Trades
📊 Performance Notes
The Universal Breakout Strategy is designed as a framework rather than a single-asset optimized system. Results will vary depending on the chart, timeframe, and asset chosen.
On the current defaults (15-minute, INR-denominated example), the backtest produced 132 trades over the selected period. This provides a statistically sufficient sample size.
Win rate (~35%) is relatively low, but this is balanced by a positive reward-to-risk ratio (~1.8). In practice, a lower win rate with larger wins versus smaller losses is sustainable.
The average P&L per trade is close to breakeven under default settings. This is expected, as the strategy is not tuned for a single symbol but offered as a universal breakout framework.
Commissions (0.1%) and slippage (1 tick) are included in the simulation, ensuring realistic conditions.
Risk management is conservative, with order sizing set at 1 unit per trade. This avoids over-leveraging and keeps exposure well under the 5-10% equity risk guideline.
👉 Traders are encouraged to:
Experiment with inputs such as ATR period, breakout length, or Bollinger parameters.
Test across different timeframes and instruments (equities, futures, forex, crypto) to find optimal setups.
Combine with filters (trend direction, volatility regimes, or volume conditions) for further refinement.
⚠️ Disclaimer This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
SRFRZ EMA Crossover with RSI StrategySRFRZ EMA Crossover with RSI Strategy
1. Overview
Strategy Name: SRFRZ EMA Crossover with RSI Strategy
Summary: A trend-following strategy designed for Indian stock and index markets, operating on any timeframe (optimized for 1H or 4H charts). It combines a 9-period and 21-period EMA crossover with RSI confirmation to identify high-probability long entries during the Indian trading session (9:15 AM–3:25 PM IST). Backtested with a fixed 20% capital allocation per trade, 3% stop loss, and 50% take profit, it aims for consistent returns in trending markets.
Intended Audience: Intermediate traders familiar with EMA and RSI, seeking automated signals for Indian markets.
2. How It Works (Core Logic)
Entry Conditions (Long/Buy Signal):
Primary Trigger: A "Golden Cross" occurs when the 9-period EMA crosses above the 21-period EMA, signaling bullish momentum.
RSI Confirmation: RSI (14-period) must be above 55, or cross above 55, to confirm strong momentum.
Trend Filter: The 9-period EMA must remain above the 21-period EMA for delayed RSI-triggered entries.
Session Filter: Trades are only executed during the Indian market session (9:15 AM–3:25 PM IST, Monday–Friday).
Exit Conditions:
Take Profit (TP): Fixed at 50% above the entry price (e.g., entry at ₹100, TP at ₹150).
Stop Loss (SL): Fixed at 3% below the entry price (e.g., entry at ₹100, SL at ₹97).
Indicator-Based Exit: Close the position if a "Death Cross" occurs (21-period EMA crosses above 9-period EMA).
Position Sizing: Allocates 20% of initial capital (₹100,000 default) per trade, calculated as (initial_capital * 0.20) / entry_price.
3. Key Indicators & Parameters
Primary Indicators:
EMA (9-period): Fast-moving average to capture short-term trends (plotted in blue).
EMA (21-period): Slower-moving average for trend confirmation (plotted in red).
RSI (14-period): Measures momentum, with a threshold of 55 for bullish confirmation (plotted in purple).
Customizable Settings in Pine Script:
initial_capital: Default ₹100,000 (adjust based on your account size).
qty_percent: Default 20% of capital per trade (adjust for risk tolerance).
sl_percent: Default 3% stop loss (adjust for volatility).
tp_percent: Default 50% take profit (adjust for reward targets).
session_time: Default "0915-1525:1234567" (Indian session, adjustable for other markets).
Default Values: Optimized for Indian stocks/indices (e.g., NIFTY 50) on 1H or 4H charts.
Risk Management:
Always use the built-in 3% stop loss.
Avoid trading during major news events (e.g., RBI announcements), as Pine Script cannot filter these.
Risk only 20% of capital per trade to diversify exposure.
Pro Tips:
Combine with support/resistance levels for manual confirmation.
Test on a demo account to validate performance on your chosen asset.
Monitor RSI for overbought conditions (>70) to anticipate reversals.
4. Visuals on Chart
Plotted Indicators:
Blue line: 9-period EMA.
Red line: 21-period EMA.
Purple line: RSI (14-period) in a separate pane.
Trade Signals:
Green triangle (below bar): Long entry.
Red triangle (above bar): Long exit (via TP, SL, or Death Cross).
5. Disclaimer & Notes
Risk Warning: Past performance is not indicative of future results. Trading involves significant risk. This strategy is for educational purposes only and is not financial advice.
Customization: The script is open-source (modify freely). Fork it to add short-selling logic or additional filters.
Note: The strategy avoids trades during non-session hours but cannot filter news events. Manually check economic calendars.
Add the script to your chart and adjust inputs (e.g., capital, TP/SL percentages).
Enable alerts for "Long Entry" and "Long Exit TP/SL" or "EMA Exit" to automate signals.
Optionally, connect to a broker via webhooks for auto-trading (consult your broker’s API).
DEMARED with ATR StopLoss & Dynamic Risk (v5)DEMARED with ATR StopLoss & Dynamic Risk
This strategy combines Double Exponential Moving Averages (DEMA) with EMA and Donchian midline filters to capture trend-following signals. A long entry is triggered when both DEMA pairs are aligned bullishly, price is above EMA, and above the Donchian midpoint. Exits occur on opposite signals or when the ATR-based stop loss is hit.
Key features:
ATR Stop Loss: dynamic stop based on ATR with user-defined multiplier.
Dynamic Risk Management: position size is automatically calculated based on account equity and risk percentage.
Visualization: plots stop loss, EMA, Donchian midline, and optional bar coloring.
Flexible Display: toggle all indicator visuals on/off with a single input.
The goal is to provide a trend-following system with controlled risk and adaptability across different markets and timeframes.
BTC Momentum Strategy - RSI & Stoch RSI Entry and EMA ExitBTC Momentum Strategy: RSI & Stoch RSI Entry with EMA Exit
This strategy is designed to identify potentially strong entry points for Bitcoin (BTC) during periods of shifting momentum and then ride the trend until it shows signs of weakness. It's a straightforward, long-only strategy, meaning it only looks for opportunities to buy and then sell for a profit.
How It Works:
The strategy combines a few classic indicators to make its decisions. Think of it as a two-step confirmation system for buying, with a simple rule for selling.
1. The Buy Signal (Green Triangle)
To generate a buy signal, the strategy looks for two things to happen at the same time:
RSI Confirmation: It first waits for the Relative Strength Index (RSI) to show signs of bullish momentum. Specifically, it's looking for the RSI line to cross above its own moving average, suggesting that strength is starting to build from a lower level. This helps catch moves as they begin to turn positive.
Stochastic RSI Confirmation: As an extra layer of confirmation, it also checks the Stochastic RSI. This helps filter out weaker signals and confirm that momentum is truly shifting upwards from an oversold or "bottomed-out" condition.
When both of these conditions are met, a green "buy" triangle will appear below the candle, and the strategy will enter a long position.
2. The Sell Signal (Red Triangle)
The exit rule is simple and designed to let your winners run while protecting you when the trend reverses.
* EMA-Based Exit: The strategy plots an orange line on your chart, which is an Exponential Moving Average (EMA). The strategy will hold the position as long as the price stays above this line. If a candle closes *below* the orange EMA line, it's taken as a sign that the short-term trend is weakening, and the strategy will close the position to lock in profits or cut losses. A red "sell" triangle will appear above that candle.
Best Use:
This strategy was built with Bitcoin in mind and tends to perform best on higher timeframes like the Weekly charts. It aims to capture major swings rather than small, quick scalps.
You can adjust all the settings for the RSI, Stochastic RSI, and the Exit EMA to fine-tune the strategy to your own trading style.
EMA 8/33 Optimized Crossover w/FilterThis strategy is ideal for fast-moving assets like cryptocurrencies (e.g., SOLUSDT) on intraday to swing trading timeframes. Its robust filtering aims for fewer trades but with higher accuracy, producing a smoother equity curve and lower drawdown in your backtests.
You can further optimize the EMA lengths, minimum candle size, and TP/SL percentages to suit your preferred asset and timeframe.
Extremum Range MA Crossover Strategy1. Principle of Work & Strategy Logic ⚙️📈
Main idea: The strategy tries to catch the moment of a breakout from a price consolidation range (flat) and the start of a new trend. It combines two key elements:
Moving Average (MA) 📉: Acts as a dynamic support/resistance level and trend filter.
Range Extremes (Range High/Low) 🔺🔻: Define the borders of the recent price channel or consolidation.
The strategy does not attempt to catch absolute tops and bottoms. Instead, it enters an already formed move after the breakout, expecting continuation.
Type: Trend-following, momentum-based.
Timeframes: Works on different TFs (H1, H4, D), but best suited for H4 and higher, where breakouts are more meaningful.
2. Justification of Indicators & Settings ⚙️
A. Moving Average (MA) 📊
Why used: Core of the strategy. It smooths price fluctuations and helps define the trend. The price (via extremes) must cross the MA → signals a potential trend shift or strengthening.
Parameters:
maLength = 20: Default length (≈ one trading month, 20-21 days). Good balance between sensitivity & smoothing.
Lower TF → reduce (10–14).
Higher TF → increase (50).
maSource: Defines price source (default = Close). Alternatives (HL2, HLC3) → smoother, less noisy MA.
maType: Default = EMA (Exponential MA).
Why EMA? Faster reaction to recent price changes vs SMA → useful for breakout strategies.
Other options:
SMA 🟦 – classic, slowest.
WMA 🟨 – weights recent data stronger.
HMA 🟩 – near-zero lag, but “nervous,” more false signals.
DEMA/TEMA 🟧 – even faster & more sensitive than EMA.
VWMA 🔊 – volume-weighted.
ZLEMA ⏱ – reduced lag.
👉 Choice = tradeoff between speed of reaction & false signals.
B. Range Extremes (Previous High/Low) 📏
Why used: Define borders of recent trading range.
prevHigh = local resistance.
prevLow = local support.
Break of these levels on close = trigger.
Parameters:
lookbackPeriod = 5: Searches for highest high / lowest low of last 5 candles. Very recent range.
Higher value (10–20) → wider, stronger ranges but rarer signals.
3. Entry & Exit Rules 🎯
Long signals (BUY) 🟢📈
Condition (longCondition): Previous Low crosses MA from below upwards.
→ Price bounced from the bottom & strong enough to push range border above MA.
Execution: Auto-close short (if any) → open long.
Short signals (SELL) 🔴📉
Condition (shortCondition): Previous High crosses MA from above downwards.
→ Price rejected from the top, upper border failed above MA.
Execution: Auto-close long (if any) → open short.
Exit conditions 🚪
Exit Long (exitLongCondition): Close below prevLow.
→ Uptrend likely ended, range shifts down.
Exit Short (exitShortCondition): Close above prevHigh.
→ Downtrend likely ended, range shifts up.
⚠️ Important: Exit = only on candle close beyond extremes (not just wick).
4. Trading Settings ⚒️
overlay = true → indicators shown on chart.
initial_capital = 10000 💵.
default_qty_type = strategy.cash, default_qty_value = 100 → trades fixed $100 per order (not lots). Can switch to % of equity.
commission_type = strategy.commission.percent, commission_value = 0.1 → default broker fee = 0.1%. Adjust for your broker!
slippage = 3 → slippage = 3 ticks. Adjust to asset liquidity.
currency = USD.
margin_long = 100, margin_short = 100 → no leverage (100% margin).
5. Visualization on Chart 📊
The strategy draws 3 lines:
🔵 MA line (thickness 2).
🔴 Previous High (last N candles).
🟢 Previous Low (last N candles).
Also: entry/exit arrows & equity curve shown in backtest.
Disclaimer ⚠️📌
Risk Warning: This description & code are for educational purposes only. Not financial advice. Trading (Forex, Stocks, Crypto) carries high risk and may lead to full capital loss. You trade at your own risk.
Testing: Always backtest & demo test first. Past results ≠ future profits.
Responsibility: Author of this strategy & description is not responsible for your trading decisions or losses.
Liquidation Strategy📈 It enters a long trade when long liquidation spikes above a set threshold.
📉 It enters a short trade when short liquidation drops below the negative threshold.
🧮 It optionally filters entries using an EMA multiplier.
🔁 It exits long when RSI crosses below its smoothed version.
🔄 It exits short when RSI crosses above its smoothed version.
🔗 It requires linking to the Liquidations indicator on Bybit or OKX charts.
Penguin Volatility State StrategyThe Penguin Volatility State Strategy is a comprehensive technical analysis framework designed to identify the underlying "state" or "regime" of the market. Instead of just providing simple buy or sell signals, its primary goal is to classify the market into one of four distinct states by combining trend, momentum, and volatility analysis.
The core idea is to trade only when these three elements align, focusing on periods of volatility expansion (a "squeeze breakout") that occur in the direction of a confirmed trend and are supported by strong momentum.
Key Components
The strategy is built upon two main engines
The Volatility Engine (Bollinger Bands vs. Keltner Channels)
This engine detects periods of rapidly increasing volatility. It measures the percentage difference (diff) between the upper bands of Bollinger Bands (which are based on standard deviation) and Keltner Channels (based on Average True Range). During a volatility "squeeze," both bands are close. When price breaks out, the Bollinger Band expands much faster than the Keltner Channel, causing the diff value to become positive. A positive diff signals a volatility breakout, which is the moment the strategy becomes active.
The Trend & Momentum Engine (Multi-EMA System)
This engine determines the market's direction and strength. It uses:
A Fast EMA (e.g., 12-period) and a Slow EMA (e.g., 26-period): The crossover of these two moving averages defines the primary, underlying trend (similar to a MACD).
An Ultra-Fast EMA (e.g., 2-period of ohlc4): This is used to measure the immediate, short-term momentum of the price.
The Four Market States
By combining the Trend and Momentum engines, the strategy categorizes the market into four visually distinct states, represented by the chart's background color. This is the most crucial aspect of the system.
💚 Green State: Strong Bullish
The primary trend is UP (Fast EMA > Slow EMA) AND the immediate momentum is STRONG (Price > Fast EMA).
Interpretation: This represents a healthy, robust uptrend where both the underlying trend and short-term price action are aligned. It is considered the safest condition for taking long positions.
❤️ Red State: Strong Bearish
Condition: The primary trend is DOWN (Fast EMA < Slow EMA) AND the immediate momentum is WEAK (Price < Fast EMA).
Interpretation: This represents a strong, confirmed downtrend. It is considered the safest condition for taking short positions.
💛 Yellow State: Weakening Bullish / Pullback
Condition: The primary trend is UP (Fast EMA > Slow EMA) BUT the immediate momentum is WEAK (Price < Fast EMA).
Interpretation: This is a critical warning signal for bulls. While the larger trend is still up, the short-term price action is showing weakness. This could be a minor pullback, a period of consolidation, or the very beginning of a trend reversal. Caution is advised.
💙 Blue State: Weakening Bearish / Relief Rally
Condition: The primary trend is DOWN (Fast EMA < Slow EMA) BUT the immediate momentum is STRONG (Price > Fast EMA).
Interpretation: This signals that a downtrend is losing steam. It often represents a short-covering rally (a "bear market rally") or the first potential sign of a market bottom. Bears should be cautious and consider taking profits.
How the Strategy Functions
The strategy uses these four states as its foundation for making trading decisions. The entry and exit arrows (Long, Short, Close) are generated based on a set of rules that can be customized by the user. For instance, a trader can configure the strategy to
Only take long trades during the Green State.
Require a confirmed volatility breakout (diff > 0) before entering a trade.
Use the "RSI on Diff" indicator to ensure that the breakout is supported by accelerating momentum.
Summary
In essence, the Penguin Volatility State Strategy provides a powerful "dashboard" for viewing the market. It moves beyond simple indicators to offer a contextual understanding of price action. By waiting for the alignment of Trend (the State), Volatility (the Breakout), and Momentum (the Acceleration), it helps traders to identify higher-probability setups and, just as importantly, to know when it is better to stay out of the market.
License / disclaimer
© waranyu.trkm — MIT License. Educational use only; not financial advice.
VWAP Trend Strategy (Intraday) [KedarArc Quant]Description:
An intraday strategy that anchors to VWAP and only trades when a local EMA trend gate and a volume participation gate are both open. It offers two entry templates—Cross and Cross-and-Retest—with an optional Momentum Exception for impulsive moves. Exits combine a TrendBreak (structure flips) with an ATR emergency stop (risk cap).
Updates will be published under this script.
Why this merits a new script
This is not a simple “VWAP + EMA + ATR” overlay. The components are sequenced as gates and branches that *change the trade set* in ways a visual mashup cannot:
1. Trend Gate first (EMA fast vs. slow on the entry timeframe)
Counter-trend VWAP crosses are suppressed. Many VWAP scripts fire on every cross; here, no entry logic even evaluates unless the trend gate is open.
2. Participation Gate second (Volume SMA × multiplier)
This gate filters thin liquidity moves around VWAP. Without it, the same visuals would produce materially more false triggers.
3. Branching entries with structure awareness
* Cross: Immediate VWAP cross in the trend direction.
* Cross-and-Retest: Requires a revisit to VWAP vicinity within a lookback window (recent low near VWAP for longs; recent high for shorts). This explicitly removes first-touch fakeouts that a plain cross takes.
* Momentum Exception (optional): A quantified body% + volume condition can bypass the retest when flow is impulsive—intentional risk-timing, not “just another indicator.”
4. Dual exits that reference both anchor and structure
* TrendBreak: Close only when price loses VWAP and EMA alignment flips.
* ATR stop: Placed at entry to cap tail risk.
These exits complement the entry structure rather than being generic stop/target add-ons.
What it does
* Trades the session’s fair value anchor (VWAP), but only with local-trend agreement (EMA fast vs. slow) and sufficient participation (volume filter).
* Lets you pick Cross or Cross-and-Retest entries; optionally allow a fast Momentum Exception when candles expand with volume.
* Manages positions with a structure exit (TrendBreak) and an emergency ATR stop from entry.
How it works (concepts & calculations)
* VWAP (session anchor):
Standard VWAP of the active session; entries reference the cross and the retest proximity to VWAP.
* Trend gate:
Long context only if `EMA(fast) > EMA(slow)`; short only if `EMA(fast) < EMA(slow)`.
A *gate*, not a trigger—entries aren’t considered unless this is true.
* Participation (volume) gate:
Require `volume > SMA(volume, volLen) × volMult`.
Screens out low-participation wiggles around VWAP.
Entries:
* Cross: Price crosses VWAP in the trend direction while volume gate is open.
* Cross-and-Retest: After crossing, price revisits VWAP vicinity within `lookback` (recent *low near VWAP* for longs; recent *high near VWAP* for shorts).
* Momentum Exception (optional): If body% (|close−open| / range) and volume exceed thresholds, enter without waiting for the retest.
Exits:
* TrendBreak (structure):
* Longs close when `price < VWAP` and `EMA(fast) < EMA(slow)` (mirror for shorts).
* ATR stop (risk):
* From entry: `stop = entry ± ATR(atrLen) × atrMult`.
How to use it ?
1. Select market & timeframe: Intraday on liquid symbols (equities, futures, crypto).
2. Pick entry mode:
* Start with Cross-and-Retest for fewer, more selective signals.
* Enable Momentum Exception if strong moves leave without retesting.
3. Tune guards:
* Raise `volMult` to ignore thin periods; lower it for more activity.
* Adjust `lookback` if retests come late/early on your symbol.
4. Risk:
* `atrLen` and `atrMult` set the emergency stop distance.
5. Read results per session: Optional panel (if enabled) summarizes Net-R, Win%, and PF for today’s session to evaluate
behavior regime by regime.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Liquidation Strategy💣 Liquidation Strategy (High-Level Overview + Usage)
This strategy is built to trade extreme liquidation events on crypto exchanges like Bybit or OKX, using TradingView’s Liquidations indicator as input.
🔧 Core Logic
Long entries: Triggered when long liquidation values spike above a set threshold.
Short entries: Triggered when short liquidation values drop below a negative threshold.
Optional EMA filter ensures liquidation values are significantly above/below their moving average.
RSI crossover logic is used to exit trades.
🛠️ Usage Instructions
Add the Liquidations Indicator: Go to TradingView → Indicators → Search for “Liquidations” under the Financials section.
Select the Correct Chart: Use a chart from Bybit or OKX, as these exchanges provide liquidation data.
Link the Data Sources: In the strategy settings, set: Long Liquidation Data to the long liquidation series from the indicator. Short Liquidation Data to the short liquidation series.
Overlay the Strategy: You can overlay this strategy directly on the Liquidations indicator for better visual alignment.
