该策略是一个基于RSI指标的动态止损交易系统,结合了SMA均线和ATR波幅指标来优化交易决策。策略采用多层次止盈方案,通过金字塔式平仓方式实现收益最大化,同时运用ATR动态止损来控制风险。策略具有高度的自适应性,能够根据市场波动情况自动调整交易参数。
策略主要依据RSI超卖区间(RSI<30)作为开仓信号,并要求价格位于200日均线之上,以确保处于上升趋势。系统采用三重止盈目标(5%、10%、15%),并结合ATR动态止损。具体来说: 1. 入场条件: RSI低于30且价格在SMA200上方 2. 仓位管理: 单次开仓使用75%资金 3. 止损设置: 基于1.5倍ATR值的动态止损 4. 止盈策略: 分别在5%、10%、15%位置设置三档止盈点,按33%、66%、100%比例分批平仓
该策略通过结合技术指标和动态风险管理,构建了一个相对完整的交易系统。其优势在于自适应性强、风险可控,但仍需根据实际市场情况进行参数优化。策略适合中长期投资者使用,可作为系统化交易的良好起点。
/*backtest start: 2019-12-23 08:00:00 end: 2024-11-11 00:00:00 period: 1d basePeriod: 1d exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA/4.0) https://creativecommons.org/licenses/by-nc-sa/4.0/ // © wielkieef //@version=5 strategy("Simple RSI stock Strategy [1D] ", overlay=true, pyramiding=1, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=75, calc_on_order_fills=false, slippage=0, commission_type=strategy.commission.percent, commission_value=0.03) // Rsi oversoldLevel = input(30, title="Oversold Level") overboughtLevel = input(70, title="Overbought Level") rsi = ta.rsi(close, 5) rsi_overbought = rsi > overboughtLevel rsi_oversold = rsi < oversoldLevel // Sma 200 lenghtSMA = input(200, title = "SMA lenght") sma200 = ta.sma(close, lenghtSMA) // ATR stop-loss atrLength = input.int(20, title="ATR Length") atrMultiplier = input.float(1.5, title="ATR Multiplier") atrValue = ta.atr(atrLength) var float long_stop_level = na var float short_stop_level = na var float tp1_level = na var float tp2_level = na var float tp3_level = na // Strategy entry long = (rsi_oversold ) and close > sma200 // Take Profit levels tp_1 = input.float(5.0, "TP 1", minval=0.1, step=0.1) tp_2 = input.float(10.0, "TP 2", minval=0.2, step=0.1) tp_3 = input.float(15.0, "TP 3", minval=0.3, step=0.1) if long strategy.entry('Long', strategy.long) long_stop_level := close - atrMultiplier * atrValue tp1_level := strategy.position_avg_price * (1 + tp_1 / 100) tp2_level := strategy.position_avg_price * (1 + tp_2 / 100) tp3_level := strategy.position_avg_price * (1 + tp_3 / 100) // basic SL - this code is from author RafaelZioni, modified by wielkieef sl = input.float(25.0, 'Basic Stop Loss %', step=0.1) per(procent) => strategy.position_size != 0 ? math.round(procent / 100 * strategy.position_avg_price / syminfo.mintick) : float(na) // ATR SL if (strategy.position_size > 0 and (close <= long_stop_level)) strategy.close("Long") tp1_level := na tp2_level := na tp3_level := na plot(long_stop_level, color=color.orange, linewidth=2, title="Long Stop Loss") // TP levels if (strategy.position_size > 0) if (not na(tp1_level) and close >= tp1_level) tp1_level := na if (not na(tp2_level) and close >= tp2_level) tp2_level := na if (not na(tp3_level) and close >= tp3_level) tp3_level := na plot(strategy.position_size > 0 and not na(tp1_level) ? tp1_level : na, color=color.gray, style=plot.style_circles , linewidth=1, title="Take Profit 1") plot(strategy.position_size > 0 and not na(tp2_level) ? tp2_level : na, color=color.gray, style=plot.style_circles , linewidth=1, title="Take Profit 2") plot(strategy.position_size > 0 and not na(tp3_level) ? tp3_level : na, color=color.gray, style=plot.style_circles , linewidth=1, title="Take Profit 3") // Strategy exit points for Take Profits strategy.exit('TP 1', from_entry="Long", qty_percent=33, profit=per(tp_1), loss=per(sl)) strategy.exit('TP 2', from_entry="Long", qty_percent=66, profit=per(tp_2), loss=per(sl)) strategy.exit('TP 3', from_entry="Long", qty_percent=100, profit=per(tp_3), loss=per(sl)) // by wielkieef