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The Predator 策略
概述
该策略是 MQL 专家顾问 “The Predator” 的 StockSharp 高级 API 版本。原策略通过趋势过滤、动量、布林带和随机指标的组合来寻找信号,并提供两个可选模板(Strategy 1 与 Strategy 2)。这些模板在移植中完整保留。
实现全部基于一条可配置的 K 线序列,通过 SubscribeCandles 订阅和指示器 Bind/BindEx 方式获得数据,无需手动维护历史缓存。
使用的指标
- 线性加权移动平均 (LWMA):快线与慢线评估趋势方向。
- DMI + ADX:衡量趋势强度与方向性。
- Momentum(默认 14):计算价格相对 100 的偏离度。
- 布林带:宽带与窄带共同判断前一根 K 线所处区间。
- 随机指标 (Stochastic):Strategy 2 的额外过滤条件。
- MACD:通过主线与信号线关系确认动量。
交易逻辑
通用规则
- 仅处理已经收盘的 K 线。
- 在交易前确认指标已经形成(
IsFormedAndOnlineAndAllowTrading)。
- ADX 必须高于指定阈值。
- 维护最近三次 Momentum 偏差,用以模拟 MQL 中的多周期检查。
Strategy 1
- 多头 需要:
- ADX > 阈值且 +DI > −DI。
- 快速 LWMA 高于慢速 LWMA。
- 最近三次 Momentum 偏差中至少一次超过买入阈值。
- MACD 主线高于信号线。
- 空头 条件相反。
Strategy 2
- 多头 额外要求:
- 前一根 K 线收盘价位于窄带下轨或以上。
- 随机指标的主线和信号线都高于上阈值。
- 最近三次 Momentum 偏差中至少一次低于买入阈值(趋势回调)。
- 空头 额外要求:
- 前一根 K 线收盘价位于窄带上轨或以下。
- 随机指标信号线高于上阈值,而主线低于下阈值。
- 最近三次 Momentum 偏差中至少一次低于卖出阈值。
仓位管理
- 在进场前取消所有挂单。
- 当方向反转时,用组合市价单同时平掉现有仓位并建立反向仓位。
风险控制
- 通过
StartProtection 设置:
- 止损距离(以点数为单位)。
- 止盈距离(点)。
- 可选的固定距离追踪止损。
- 点数会根据标的物的最小价格步长转换成绝对价格。
- 原 MQL 中的金额型止损、无损移动和通知系统未移植,使用了固定点数替代。
参数
| 参数 |
含义 |
Mode |
选择 Strategy 1 或 Strategy 2。 |
FastMaLength, SlowMaLength |
LWMA 快线/慢线周期。 |
DmiPeriod, AdxSmoothing |
DMI 与 ADX 设置。 |
MomentumPeriod |
Momentum 周期。 |
MomentumBuyThreshold, MomentumSellThreshold |
接受信号所需的最小偏差。 |
AdxThreshold |
ADX 最低触发值。 |
BollingerPeriod, TightBandWidth, WideBandWidth |
布林带参数。 |
StochasticLength, StochasticSmooth, StochasticUpper, StochasticLower |
随机指标参数(Strategy 2)。 |
TradeVolume |
交易数量。 |
StopLossPips, TakeProfitPips, TrailingStopPips |
风险距离(点)。 |
CandleType |
使用的 K 线类型。 |
与 MQL 版本的差异
- 金额型止损/止盈/追踪转换为点数,通过
StartProtection 管理。
- 未实现原策略中的无损移动和邮件/推送通知功能。
- MQL 中部分指标调用了更高周期,这里仅使用单一订阅;若需要多周期可自行添加。
- 未实现阶梯加仓或马丁系数,StockSharp 版本采用固定
TradeVolume。
使用步骤
- 按 StockSharp 示例建立连接与投资组合。
- 实例化
ThePredatorStrategy,设置 Security、Portfolio 及参数。
- 启动策略,可选地绑定图表以查看指标和成交。
该移植保留了原始决策逻辑,并结合 StockSharp 的绑定机制与保护模块,便于进一步优化和扩展。
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 ThePredatorStrategy : 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 ThePredatorStrategy()
{
_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 the_predator_strategy(Strategy):
def __init__(self):
super(the_predator_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(the_predator_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(the_predator_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 the_predator_strategy()