Fractal and Pattern Based Quantitative Trading Strategy

This article introduces a quantitative trading strategy that combines fractal analysis and candlestick patterns. By detecting key reversal points and bullish/bearish reversal candlestick patterns, this strategy…

Pine ScriptMachine learning Breakout Mean reversion

Author: ChaoZhang
Complexity: Starter · 49 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

This strategy is based on detailed price action analysis, using a combination of fractal analysis and candlestick pattern recognition to define clear entry and stop loss logic for capturing the trend.

Specifically, its entry condition is: price breaks above the high of the previous 2 bars, and a fractal breakout or bullish engulfing or hammer pattern occurs. This combination solidly confirms long signals. The stop loss logic which defines exit at price breaking below the low of the previous 2 bars ensures quick and effective stops.

For pattern detection, this strategy uses the commonly used fractal theory to identify key reversal points, as well as algorithms to detect the 3 classic candlestick reversal patterns.

The coding is done in Pine script. Fractal high/low is identified when price makes 3-bar new high/low, and strict rules on open/close prices are used for engulfing patterns.

Advantages

Main advantages of this strategy:

Accurate signal combining fractals and patterns
Clear entry and stop loss logic
Mature theories prevent overfitting
Pine script allows backtesting

Risks

There are still risks to note:

Subjectivity in fractal and pattern detection
Whipsaws potentially generating consecutive losing trades
Stop loss sizing requires adjustment for high frequency trading

Methods like optimized stops, trend filtering and walk forward analysis can help control the above risks.

Enhancements

Areas for further enhancements:

Fine tune candlestick pattern parameter for robustness
Add trend bias filter to avoid whipsaws
Introduce machine learning for automatic parameter optimization

These improvements will further strengthen the strategy's stability and profitability.

Conclusion

This article thoroughly covers a price action trading strategy combining fractals and candlestick patterns. With accurate signaling, easy implementation and effective trend following, this strategy can greatly benefit systematic traders and discretionary traders alike. Continual improvements and verification will further elevate its performance for practical trading.

Source Pine Script

/*backtest
start: 2023-02-12 00:00:00
end: 2024-02-18 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("Fractal & Pattern Entry/Exit Strategy", overlay=true)

// Fractal calculation
fractalHigh = high == highest(3)
fractalLow = low == lowest(3)

// Pattern detection
bullishEngulfing = open < close[1] and close > open[1] and close > open + (open[1] - close[1]) * 2 and low < min(open, close) and high > max(open, close) and open[1] > close[1]
bearishEngulfing = open > close[1] and close < open[1] and open > close + (close[1] - open[1]) * 2 and high > max(open, close) and low < min(open, close) and open[1] < close[1]
hammer = open < close and close > (high + low + open * 2) / 4 and close - open > (high - low) * 0.6 and high - close < (high - low) * 0.1 and open - low < (high - low) * 0.1
hangingMan = open > close and open < (high + low + close * 2) / 4 and open - close > (high - low) * 0.6 and high - open < (high - low) * 0.1 and close - low < (high - low) * 0.1

// Entry condition
longCondition = crossover(close, highest(2)[1]) and (fractalHigh or bullishEngulfing or hammer)
shortCondition = crossunder(close, lowest(2)[1]) and (fractalLow or bearishEngulfing or hangingMan)

// Exit condition
exitLongCondition = crossunder(close, lowest(2)[1])
exitShortCondition = crossover(close, highest(2)[1])

// Entry and exit orders
if (longCondition)
    strategy.entry("Long", strategy.long)
if (shortCondition)
    strategy.entry("Short", strategy.short)
if (exitLongCondition)
    strategy.close("Long")
if (exitShortCondition)
    strategy.close("Short")

// Plot fractals
plotshape(fractalHigh, title="Fractal High", style=shape.triangledown, location=location.abovebar, color=color.green, size=size.small)
plotshape(fractalLow, title="Fractal Low", style=shape.triangleup, location=location.belowbar, color=color.red, size=size.small)

// Plot patterns
plotshape(bullishEngulfing, title="Bullish Engulfing", style=shape.arrowup, location=location.belowbar, color=color.green, size=size.small)
plotshape(bearishEngulfing, title="Bearish Engulfing", style=shape.arrowdown, location=location.abovebar, color=color.red, size=size.small)
plotshape(hammer, title="Hammer", style=shape.arrowup, location=location.belowbar, color=color.green, size=size.small)
plotshape(hangingMan, title="Hanging Man", style=shape.arrowdown, location=location.abovebar, color=color.red, size=size.small)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-19. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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