FX Strategy Based on Fractal Waves and SMMA

Author: ChaoZhang, Date: 2023-11-13 16:39:41
Tags:

Overview

This strategy combines fractal wave theory and SMMA to identify trend opportunities, and uses proper stop loss and trailing stop to control risks for profit maximization. It only enters positions during specified trading sessions to avoid market swings at certain times.

Strategy Logic

Use SMMA to calculate average price and filter market noise for trend direction
Identify trend reversal points using highest/lowest price within certain periods as fractal waves
Go short when price wave breaks above SMMA, go long when breaks below
Set stop loss and trailing stop based on ATR to control risks
Only trade within specified sessions, avoiding weekend and intraday swings

Advantage Analysis

Fractal wave theory accurately identifies trend reversal points, combined with SMMA for trend direction
Stop loss and ATR trailing stop effectively limits loss per trade
Only trading during liquid sessions avoids excessive slippage and volatility
Following parabolic SAR strictly to exit at reversal signal maximizes profit

Risk Analysis

Inaccurate fractal wave may cause whipsaws in non-trending periods
SMMA lag may miss ideal trend reversal points
Stop loss too tight may get stopped out easily, too loose may incur larger loss
Fixed profit taking unable to adjust to different market conditions

Solutions:

Optimize parameters for fractal period and SMMA
Add Stochastics to confirm reversal signals
Dynamically optimize stop loss, profit target

Optimization Directions

Optimize fractal period and SMMA parameters
Add Stochastics indicator to filter false breakouts
Experiment with dynamic stop loss and profit taking
Widen stop loss to avoid getting stopped out
Optimize parameters for different products and trading sessions

Summary

This strategy integrates fractal wave theory and SMMA to identify trend and reversal points to trade, with proper stop loss and profit taking. It can be further improved by optimizing parameters and adding confirming indicators for higher stability and profitability.

/*backtest
start: 2022-11-12 00:00:00
end: 2023-11-12 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("FX Strategy Based on Fractals and SMMA", overlay=true)

// パラメータ
SMMAPeriod1 = input(30, title="SMMA Period")
StopLoss1 = input(7, title="Stop Loss %")
TrailingStopCoef1 = input(2.7, title="Trailing Stop Coefficient")
fractalPeriod = input(5, title="Fractal Period")

// SMMAの計算関数
smma(src, length) =>
    var float smma = na
    if na(smma[1])
        smma := sma(src, length)
    else
        smma := (smma[1] * (length - 1) + src) / length
    smma

// フラクタルの近似
highFractal = high[2] > high[1] and high[2] > high[3] and high[2] > high[4] and high[2] > high
lowFractal = low[2] < low[1] and low[2] < low[3] and low[2] < low[4] and low[2] < low

// エントリー条件
longEntrySignal = lowFractal and close[1] < smma(close, SMMAPeriod1)
shortEntrySignal = highFractal and close[1] > smma(close, SMMAPeriod1)

// エントリー実行
if (longEntrySignal)
    strategy.entry("Long", strategy.long)

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

// トレーリングストップの計算
atrValue = atr(10)
longStopPrice = close - atrValue * TrailingStopCoef1
shortStopPrice = close + atrValue * TrailingStopCoef1

// トレーリングストップの設定
strategy.exit("Exit Long", "Long", stop=longStopPrice)
strategy.exit("Exit Short", "Short", stop=shortStopPrice)

// バックテスト期間の設定（MetaTraderのバックテストと同じ期間）
startYear = 2007
startMonth = 05
startDay = 01
endYear = 2022
endMonth = 04
endDay = 01

startDate = timestamp(startYear, startMonth, startDay, 00, 00)
endDate = timestamp(endYear, endMonth, endDay, 23, 59)

// バックテスト期間内でのみトレードを実行
if (time >= startDate and time <= endDate)
    if (longEntrySignal)
        strategy.entry("Long", strategy.long)
    if (shortEntrySignal)
        strategy.entry("Short", strategy.short)

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