Advanced Fair Value Gap Detection Strategy with Dynamic Risk Management and Fixed Take Profit

Pine ScriptBreakout Trend following Volatility

Author: ChaoZhang
Complexity: Starter · 63 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This is a trading strategy based on Fair Value Gap (FVG) detection, combining dynamic risk management with fixed take profit targets. Operating on a 15-minute timeframe, the strategy identifies potential trading opportunities by detecting price gaps in the market. According to backtest data from November 2023 to August 2024, the strategy achieved a net profit of 284.40% with 153 total trades, maintaining a win rate of 71.24% and a profit factor of 2.422.

Strategy Principle

The core mechanism revolves around detecting Fair Value Gaps by monitoring price relationships across three consecutive candles:

Bullish FVG: When the high of the middle candle is below the low of the first candle
Bearish FVG: When the low of the middle candle is above the high of the first candle
Entry signals are controlled by an FVG threshold parameter
Risk control uses a fixed percentage (1%) of account equity as stop loss
Take profit is set at a fixed 50 points

Strategy Advantages

Scientific risk management: Uses account equity percentage for stop loss
Clear trading rules: Fixed take profit targets eliminate subjective judgment
Excellent performance: High win rate and profit factor indicate strategy stability
Simple implementation: Clear code logic, easy to understand and maintain
High adaptability: Can be adjusted for different market conditions

Strategy Risks

Market volatility risk: Fixed point take profit may be inflexible in highly volatile markets
Slippage risk: Frequent trading may lead to higher slippage costs
Parameter dependency: Performance heavily relies on FVG threshold settings
False breakout risk: Some FVG signals might be false breakouts
Money management risk: Fixed percentage stop loss might lead to quick drawdowns

Optimization Directions

Introduce volatility indicators for dynamic take profit adjustment
Add trend filters to avoid ranging market trades
Develop multiple timeframe confirmation mechanism
Optimize position sizing algorithm with floating position system
Add trading time filters to avoid high volatility periods
Develop signal strength scoring system for high-quality trade selection

Summary

This strategy demonstrates impressive results by combining Fair Value Gap theory with scientific risk management. The high win rate and stable profit factor indicate its practical value. Through the suggested optimization directions, there is potential for further improvement. Traders are advised to conduct thorough parameter optimization and backtesting before live implementation.

Source Pine Script

/*backtest
start: 2019-12-23 08:00:00
end: 2024-11-28 00:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Fair Value Gap Strategy with % SL and Fixed TP", overlay=true, initial_capital=500, default_qty_type=strategy.fixed, default_qty_value=1)

// Parameters
fvgThreshold = input.float(0.5, "FVG Threshold (%)", minval=0.1, step=0.1)

// Fixed take profit in pips
takeProfitPips = 50

// Function to convert pips to price
pipsToPriceChange(pips) =>
    syminfo.mintick * pips * 10

// Function to detect Fair Value Gap
detectFVG(dir) =>
    gap = 0.0
    if dir > 0  // Bullish FVG
        gap := low[2] - high[1]
    else  // Bearish FVG
        gap := low[1] - high[2]
    math.abs(gap) > (close * fvgThreshold / 100)

// Detect FVGs
bullishFVG = detectFVG(1)
bearishFVG = detectFVG(-1)

// Entry conditions
longCondition = bullishFVG
shortCondition = bearishFVG

// Calculate take profit level
longTakeProfit = strategy.position_avg_price + pipsToPriceChange(takeProfitPips)
shortTakeProfit = strategy.position_avg_price - pipsToPriceChange(takeProfitPips)

// Calculate stop loss amount (5% of capital)
stopLossAmount = strategy.equity * 0.01

// Execute trades
if (longCondition)
    strategy.entry("Long", strategy.long)

if (shortCondition)
    strategy.entry("Short", strategy.short)

// Set exit conditions
if (strategy.position_size > 0)
    strategy.exit("Long TP", "Long", limit=longTakeProfit)
    strategy.close("Long SL", when=strategy.openprofit < -stopLossAmount)
else if (strategy.position_size < 0)
    strategy.exit("Short TP", "Short", limit=shortTakeProfit)
    strategy.close("Short SL", when=strategy.openprofit < -stopLossAmount)

// Plot signals
plotshape(longCondition, "Buy Signal", location = location.belowbar, color = color.green, style = shape.triangleup, size = size.small)
plotshape(shortCondition, "Sell Signal", location = location.abovebar, color = color.red, style = shape.triangledown, size = size.small)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-11-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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