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Exp Adaptive Renko MMRec Duplex 策略
该策略将 MetaTrader 5 智能交易系统 Exp_AdaptiveRenko_MMRec_Duplex.mq5 迁移到 StockSharp 的高级 API。策略维护两条互不干扰的 Adaptive Renko 流:多头流跟踪新的支撑,空头流跟踪新的阻力。当多头通道出现新的支撑而空头通道失去阻力(或反过来)时,系统会开立相应方向的市价单。C# 实现保留了原始 EA 的 “MM Recounter” 资金管理模块——在连续亏损达到阈值后自动降低下单量,并在盈利恢复后恢复默认规模。
工作流程
- 数据订阅:多头与空头分别订阅各自的蜡烛类型(时间框架),并通过
SubscribeCandles().BindEx(...) 绑定波动率指标(ATR 或标准差),波动率决定自适应砖块的高度。
- Adaptive Renko 处理:辅助类
AdaptiveRenkoProcessor 重建 MQL 指标逻辑,返回包含趋势、支撑和阻力的快照。所有计算均基于收盘蜡烛。
- 入场逻辑:当多头快照出现向上的趋势(信号蜡烛上有支撑)时,策略开多;当空头快照出现向下趋势(信号蜡烛上出现阻力)时,开空。
- 离场逻辑:相反的 Renko 信号触发平仓。同时按价格步长检查止损和止盈阈值。
- MMRec 资金管理:每个方向维护一组最近交易盈亏的队列。若在配置窗口内的亏损次数达到
LossTrigger,下一笔交易使用缩减后的资金管理值(LongSmallMoneyManagement / ShortSmallMoneyManagement),否则使用常规值(LongMoneyManagement / ShortMoneyManagement)。MarginModeOption 枚举复现了原 EA 的所有下单模式(按手数、按余额比例、按风险比例等)。
- 交易登记:每次平仓都会调用
RegisterTradeResult 更新 MMRec 队列,队列裁剪逻辑与 MQL 中的 BuyTradeMMRecounterS / SellTradeMMRecounterS 完全一致,无需遍历历史订单。
参数分组
| 分组 |
关键参数 |
说明 |
| 多头 |
LongCandleType, LongVolatilityMode, LongVolatilityPeriod, LongSensitivity, LongPriceMode, LongMinimumBrickPoints, LongSignalBarOffset |
控制多头 Adaptive Renko 流的指标设置。 |
| 空头 |
ShortCandleType, ShortVolatilityMode, ShortVolatilityPeriod, ShortSensitivity, ShortPriceMode, ShortMinimumBrickPoints, ShortSignalBarOffset |
为空头流提供与多头对称的配置。 |
| MMRec |
LongTotalTrigger, LongLossTrigger, LongSmallMoneyManagement, LongMoneyManagement, LongMarginMode, ShortTotalTrigger, ShortLossTrigger, ShortSmallMoneyManagement, ShortMoneyManagement, ShortMarginMode |
资金管理恢复模块参数。TotalTrigger 定义滑动窗口长度,LossTrigger 决定何时切换到缩减手数。 |
| 风险控制 |
LongStopLossPoints, LongTakeProfitPoints, ShortStopLossPoints, ShortTakeProfitPoints, LongDeviationSteps, ShortDeviationSteps |
以价格步长表示的止损、止盈以及信息性的滑点设置。 |
实现细节
- 策略按净额账户模型工作,开多前会平掉现有的空单,开空同理。
CalculateVolume 将资金管理值转换为下单量,支持所有原始保证金模式,包括基于止损距离的风险控制。
- 指标计算仅在
CandleStates.Finished 的蜡烛上进行,严格遵循源 EA 的行为。
- 日志会记录当前使用的资金管理倍数以及预计的滑点(以价格步长表示),方便调试与复盘。
文件结构
CS/ExpAdaptiveRenkoMmrecDuplexStrategy.cs:策略实现,包含 Adaptive Renko 处理器与 MMRec 模块。
README.md:英文说明。
README_ru.md:俄文说明。
README_zh.md:中文说明(本文档)。
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
public class ExpAdaptiveRenkoMmrecDuplexStrategy : Strategy
{
private readonly StrategyParam<int> _fastPeriod;
private readonly StrategyParam<int> _slowPeriod;
private readonly StrategyParam<int> _stopLossPoints;
private readonly StrategyParam<int> _takeProfitPoints;
private ExponentialMovingAverage _fast;
private ExponentialMovingAverage _slow;
private decimal _prevFast;
private decimal _prevSlow;
private decimal _entryPrice;
private int _cooldown;
public int FastPeriod { get => _fastPeriod.Value; set => _fastPeriod.Value = value; }
public int SlowPeriod { get => _slowPeriod.Value; set => _slowPeriod.Value = value; }
public int StopLossPoints { get => _stopLossPoints.Value; set => _stopLossPoints.Value = value; }
public int TakeProfitPoints { get => _takeProfitPoints.Value; set => _takeProfitPoints.Value = value; }
public ExpAdaptiveRenkoMmrecDuplexStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 14).SetGreaterThanZero().SetDisplay("Fast Period", "Fast EMA period", "Indicator");
_slowPeriod = Param(nameof(SlowPeriod), 50).SetGreaterThanZero().SetDisplay("Slow Period", "Slow EMA period", "Indicator");
_stopLossPoints = Param(nameof(StopLossPoints), 200).SetNotNegative().SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk");
_takeProfitPoints = Param(nameof(TakeProfitPoints), 400).SetNotNegative().SetDisplay("Take Profit", "Take-profit in price steps", "Risk");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
yield return (Security, TimeSpan.FromMinutes(5).TimeFrame());
}
protected override void OnReseted()
{
base.OnReseted();
_fast = null; _slow = null;
_prevFast = 0; _prevSlow = 0; _entryPrice = 0; _cooldown = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_fast = new ExponentialMovingAverage { Length = FastPeriod };
_slow = new ExponentialMovingAverage { Length = SlowPeriod };
var subscription = SubscribeCandles(TimeSpan.FromMinutes(5).TimeFrame());
subscription.Bind(_fast, _slow, ProcessCandle);
subscription.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal fastValue, decimal slowValue)
{
if (candle.State != CandleStates.Finished) return;
if (!_fast.IsFormed || !_slow.IsFormed) { _prevFast = fastValue; _prevSlow = slowValue; return; }
if (_cooldown > 0) { _cooldown--; _prevFast = fastValue; _prevSlow = slowValue; return; }
var close = candle.ClosePrice;
var step = Security?.PriceStep ?? 1m;
if (Position > 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close <= _entryPrice - StopLossPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close >= _entryPrice + TakeProfitPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
else if (Position < 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close >= _entryPrice + StopLossPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close <= _entryPrice - TakeProfitPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
if (_prevFast <= _prevSlow && fastValue > slowValue && Position <= 0)
{ if (Position < 0) BuyMarket(); BuyMarket(); _entryPrice = close; _cooldown = 100; }
else if (_prevFast >= _prevSlow && fastValue < slowValue && Position >= 0)
{ if (Position > 0) SellMarket(); SellMarket(); _entryPrice = close; _cooldown = 100; }
_prevFast = fastValue; _prevSlow = slowValue;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class exp_adaptive_renko_mmrec_duplex_strategy(Strategy):
def __init__(self):
super(exp_adaptive_renko_mmrec_duplex_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 14) \
.SetDisplay("Fast Period", "Fast MA period", "Indicator")
self._slow_period = self.Param("SlowPeriod", 50) \
.SetDisplay("Slow Period", "Slow MA period", "Indicator")
self._stop_loss_points = self.Param("StopLossPoints", 200) \
.SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk")
self._take_profit_points = self.Param("TakeProfitPoints", 400) \
.SetDisplay("Take Profit", "Take-profit in price steps", "Risk")
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
@property
def fast_period(self):
return self._fast_period.Value
@property
def slow_period(self):
return self._slow_period.Value
@property
def stop_loss_points(self):
return self._stop_loss_points.Value
@property
def take_profit_points(self):
return self._take_profit_points.Value
def OnReseted(self):
super(exp_adaptive_renko_mmrec_duplex_strategy, self).OnReseted()
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
def OnStarted2(self, time):
super(exp_adaptive_renko_mmrec_duplex_strategy, self).OnStarted2(time)
self._fast = ExponentialMovingAverage()
self._fast.Length = self.fast_period
self._slow = ExponentialMovingAverage()
self._slow.Length = self.slow_period
subscription = self.SubscribeCandles(DataType.TimeFrame(TimeSpan.FromMinutes(5)))
subscription.Bind(self._fast, self._slow, self._process_candle)
subscription.Start()
def _process_candle(self, candle, fast_value, slow_value):
if candle.State != CandleStates.Finished:
return
fast_val = float(fast_value)
slow_val = float(slow_value)
if not self._fast.IsFormed or not self._slow.IsFormed:
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._cooldown > 0:
self._cooldown -= 1
self._prev_fast = fast_val
self._prev_slow = slow_val
return
close = float(candle.ClosePrice)
step = float(self.Security.PriceStep) if self.Security is not None and self.Security.PriceStep is not None else 1.0
if self.Position > 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close <= self._entry_price - self.stop_loss_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close >= self._entry_price + self.take_profit_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
elif self.Position < 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close >= self._entry_price + self.stop_loss_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close <= self._entry_price - self.take_profit_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._prev_fast <= self._prev_slow and fast_val > slow_val and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._entry_price = close
self._cooldown = 100
elif self._prev_fast >= self._prev_slow and fast_val < slow_val and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._entry_price = close
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
def CreateClone(self):
return exp_adaptive_renko_mmrec_duplex_strategy()