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BladeRunner 策略
概述
BladeRunner 策略源自 MetaTrader 智能交易系统,结合了威廉姆斯分形突破、趋势判定以及多周期动量过滤。StockSharp 版本保留了原脚本的多时间框架结构:主周期负责产生信号,高一级周期用于动量过滤,慢速周期提供 MACD 趋势确认。策略以市价单入场,可按配置进行加仓,并自动按照价格步长设置止损与止盈。
交易逻辑
- 分形突破过滤:算法在完成的 K 线中寻找威廉姆斯分形。若两根之前的 K 线创出新高,且确认 K 线开盘价低于分形价位和 20 周期 LWMA(典型价),则产生看多分形;看空分形则要求对应的开盘价高于分形价位与 LWMA。
- 趋势过滤:在主周期上计算快慢两条线性加权移动平均线(LWMA)。只有当快线高于慢线时才允许做多,反之则允许做空。
- 动量过滤:在高一级周期计算动量指标,只要最近三个读数中有任意一个与 100 的偏差超过阈值,就认为动量充足。
- MACD 过滤:在慢速周期上计算 MACD,要求主线位于信号线之上(做多)或之下(做空)。
- 突破确认:最新主周期 K 线的收盘价必须突破存储的分形价位,才会真正发出交易。
当以上所有条件同时满足时,策略按设定手数开仓;如果存在反向仓位,会先行平掉再反手。只要未达到最大加仓次数,就可以继续分批入场。
实现细节
- 使用高级 API 创建三条蜡烛订阅,并直接与各自的指标绑定,无需加入全局指标列表。
- 所有 LWMA 均以典型价 (H+L+C)/3 为输入,MACD 同样采用该价格类型,以保持与 MQL 版本一致。
- 分形检测保存一个滑动窗口的历史 K 线及其过滤值,仅记录最后一个通过验证的分形方向,防止在同一结构上重复触发。
- 动量历史使用固定长度数组维护,既重现了原策略查看最近三个值的逻辑,又避免多余的内存分配。
- 下单前会按交易所的最小步长、最小/最大手数调整成交量。
- 调用
StartProtection 后,所有仓位都会自动附加以价格步长表示的止损和止盈。
参数
| 参数 |
说明 |
默认值 |
CandleType |
主周期蜡烛,用于生成信号。 |
15 分钟 |
MomentumCandleType |
动量过滤所用的高一级周期。 |
1 小时 |
MacdCandleType |
MACD 过滤所用的慢速周期。 |
日线 |
FastMaPeriod |
快速 LWMA 周期。 |
6 |
SlowMaPeriod |
慢速 LWMA 周期。 |
85 |
FilterMaPeriod |
分形验证所用的 LWMA 周期。 |
20 |
MomentumPeriod |
动量指标的计算周期。 |
14 |
MomentumThreshold |
动量偏离 100 的最小阈值。 |
0.3 |
FractalLookback |
分形检测的历史窗口长度。 |
200 |
MaxTrades |
单方向允许的最大加仓次数。 |
3 |
OrderVolume |
每次市价单的基础手数。 |
1 合约 |
TakeProfitSteps |
以价格步长表示的止盈距离。 |
50 |
StopLossSteps |
以价格步长表示的止损距离。 |
20 |
风险控制
StartProtection 会为每个仓位自动挂上止损和止盈。
- 在开新仓之前会先平掉反向持仓,避免形成对锁。
MaxTrades 限制了单向总加仓次数,同时成交量会按照交易所约束进行调整。
与原版 EA 的差异
- 未移植基于权益的强制平仓、资金追踪止损和保本功能,如有需要可通过 StockSharp 其他组件实现。
- 原代码中的资金追踪止盈和推送通知被省略,可改用平台的通知系统。
- 默认情况下 MACD 使用日线数据。若数据源支持月线,可将
MacdCandleType 改为月线以贴近原策略。
- 分形验证基于滑动窗口中的最新确认蜡烛,避免反复遍历 200 根历史数据但行为效果一致。
使用建议
- 根据实际数据源配置三个蜡烛周期,确保能够同时获取主周期、动量周期和 MACD 周期。
- 将
OrderVolume、TakeProfitSteps 与 StopLossSteps 调整为符合品种最小价位变动和合约乘数的值。
- 在历史测试或滚动验证中优化动量阈值及 LWMA 周期,以适配不同市场环境。
- 如需人工确认,可开启图表绘制功能观察三条 LWMA 以及分形突破的配合情况。
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 BladeRunnerStrategy : 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 BladeRunnerStrategy()
{
_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 blade_runner_strategy(Strategy):
def __init__(self):
super(blade_runner_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(blade_runner_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(blade_runner_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 blade_runner_strategy()