Strategi ini menggunakan EMA berbilang dinamik sebagai isyarat kemasukan digabungkan dengan mekanisme sasaran stop loss dan keuntungan untuk pengurusan risiko. Ia memanfaatkan sifat kelancaran EMA untuk mengenal pasti trend dan mengawal kos melalui entri multi-DCA. Di samping itu, integrasi ciri stop loss dan mengambil keuntungan adaptif meningkatkan proses automasi.
Memicu entri panjang apabila harga melintasi atau bergerak dalam julat tempoh EMA yang dipilih. EMA biasa termasuk 5, 10, 20, 50, 100, 200 tempoh. Strategi ini menggunakan julat 1% EMA sebagai kriteria kemasukan.
Merangkumi pelbagai mekanisme kawalan risiko:
Tetapkan paras harga sasaran keuntungan untuk keluar
Strategi ini merangkumi pengesanan trend EMA, purata kos multi-DCA, penangguhan stop loss, pengambilan keuntungan sasaran dan banyak lagi. Masih ada potensi yang banyak dalam menyesuaikan parameter dan meningkatkan kawalan risiko. Secara keseluruhan, strategi yang sangat adaptif dan serba boleh ini menawarkan pelabur keupayaan penjanaan alpha 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)