Strategi ini memanfaatkan EMA ganda dinamis sebagai sinyal masuk dikombinasikan dengan mekanisme target stop loss dan profit trailing untuk manajemen risiko. Ini memanfaatkan sifat smoothing EMA untuk mengidentifikasi tren dan mengendalikan biaya melalui entri multi-DCA. Selain itu, integrasi fitur stop loss dan profit taking adaptif meningkatkan proses otomatisasi.
Memicu entri panjang ketika harga melintasi atau bergerak dalam rentang periode EMA yang dipilih. EMA khas termasuk 5, 10, 20, 50, 100, 200 periode. Strategi ini menggunakan rentang 1% dari EMA sebagai kriteria masuk.
Menggabungkan beberapa mekanisme pengendalian risiko:
Tetapkan target harga keuntungan untuk keluar
Strategi ini mencakup deteksi tren EMA, rata-rata biaya multi-DCA, stop loss, target profit taking dan banyak lagi. Masih ada potensi yang luas dalam menyesuaikan parameter dan meningkatkan kontrol risiko. Secara keseluruhan, strategi yang sangat adaptif dan serbaguna ini menawarkan investor kemampuan generasi alfa yang stabil.
/*backtest start: 2023-01-12 00:00:00 end: 2024-01-18 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=4 strategy("EMA DCA Strategy with Trailing Stop and Profit Target", overlay=true ) // Define the investment amount for when the condition is met investment_per_condition = 6 // Define the EMAs ema5 = ema(close, 5) ema10 = ema(close, 10) ema20 = ema(close, 20) ema50 = ema(close, 50) ema100 = ema(close, 100) ema200 = ema(close, 200) // Define ATR sell threshold atr_sell_threshold = input(title="ATR Sell Threshold", type=input.integer, defval=10, minval=1) // Helper function to find if the price is within 1% of the EMA isWithin1Percent(price, ema) => ema_min = ema * 0.99 ema_max = ema * 1.01 price >= ema_min and price <= ema_max // Control the number of buys var int buy_count = 0 buy_limit = input(title="Buy Limit", type=input.integer, defval=3000) // Calculate trailing stop and profit target levels trail_percent = input(title="Trailing Stop Percentage", type=input.integer, defval=1, minval=0, maxval=10) profit_target_percent = input(title="Profit Target Percentage", type=input.integer, defval=3, minval=1, maxval=10) // Determine if the conditions are met and execute the strategy checkConditionAndBuy(emaValue, emaName) => var int local_buy_count = 0 // Create a local mutable variable if isWithin1Percent(close, emaValue) and local_buy_count < buy_limit strategy.entry("Buy at " + emaName, strategy.long, qty=investment_per_condition / close, alert_message ="Buy condition met for " + emaName) local_buy_count := local_buy_count + 1 // alert("Buy Condition", "Buy condition met for ", freq_once_per_bar_close) local_buy_count // Return the updated local_buy_count // Add ATR sell condition atr_condition = atr(20) > atr_sell_threshold if atr_condition strategy.close_all() buy_count := 0 // Reset the global buy_count when selling // Strategy execution buy_count := checkConditionAndBuy(ema5, "EMA5") buy_count := checkConditionAndBuy(ema10, "EMA10") buy_count := checkConditionAndBuy(ema20, "EMA20") buy_count := checkConditionAndBuy(ema50, "EMA50") buy_count := checkConditionAndBuy(ema100, "EMA100") buy_count := checkConditionAndBuy(ema200, "EMA200") // Calculate trailing stop level trail_offset = close * trail_percent / 100 trail_level = close - trail_offset // Set profit target level profit_target_level = close * (1 + profit_target_percent / 100) // Exit strategy: Trailing Stop and Profit Target strategy.exit("TrailingStop", from_entry="Buy at EMA", trail_offset=trail_offset, trail_price=trail_level) strategy.exit("ProfitTarget", from_entry="Buy at EMA", when=close >= profit_target_level) // Plot EMAs plot(ema5, title="EMA 5", color=color.red) plot(ema10, title="EMA 10", color=color.orange) plot(ema20, title="EMA 20", color=color.yellow) plot(ema50, title="EMA 50", color=color.green) plot(ema100, title="EMA 100", color=color.blue) plot(ema200, title="EMA 200", color=color.purple)