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iMA iStochastic Custom 策略
概览
本策略在 StockSharp 环境中复刻 MetaTrader 专家顾问 “iMA iStochastic Custom”。它将移动平均包络与随机振荡器相结合,只在所选时间框架(CandleType)的完整 K 线收盘后评估信号。下文使用与原始 EA 相同的术语。
核心模块:
- 移动平均包络 – 在基准移动平均值上分别加上
LevelUpPips 与 LevelDownPips(以点为单位)形成阻力和支撑通道,可选择简单、指数、平滑(SMMA)或线性加权(LWMA)四种算法。
- 随机振荡器 – %K、%D 以及平滑参数完全对应原版输入,通过
StochasticLevel1 与 StochasticLevel2 判定超买/超卖区域。
- 资金管理 –
ManagementMode 继承了 MQL 的“定量/风险百分比”开关。FixedLot 模式下下单量等于 VolumeValue;RiskPercent 模式则按 VolumeValue 指定的权益百分比计算仓位,等价于 CMoneyFixedMargin 的行为。
- 保护机制 – 止损、止盈及追踪距离均以点填写,并在每根收盘 K 线时检查。追踪止损需要价格先运行
TrailingStopPips,随后每次至少改善 TrailingStepPips 才会上调,逻辑与原 EA 一致。
交易规则
多空规则对称:
- 做多:K 线收盘价高于上轨(
ma + LevelUpPips),且随机指标任一分量高于 StochasticLevel1。
- 做空:K 线收盘价低于下轨(
ma + LevelDownPips),且随机指标任一分量低于 StochasticLevel2。
- 将
ReverseSignals 设为 true 可反转方向。
策略始终保持单一净头寸。信号翻转时,会自动下达足够的反向委托以平仓并建立新的方向。
风险控制与退出
- 止损 / 止盈:按
PriceStep 将点值换算成价格距离,并以当根 K 线的最高/最低价触发。
- 追踪止损:价格获利达到
TrailingStopPips 后启动,每次至少再改善 TrailingStepPips 才会上移/下移止损。
- 资金管理:风险模式下的手数为
权益 * VolumeValue / 100 / perUnitRisk,其中 perUnitRisk 表示止损前每单位手数的货币损失。
参数一览
| 参数 |
说明 |
CandleType |
使用的时间框架。 |
StopLossPips、TakeProfitPips |
止损与止盈距离(点)。 |
TrailingStopPips、TrailingStepPips |
追踪止损启动距离与步长(点),为 0 时关闭。 |
ManagementMode、VolumeValue |
定量或风险百分比仓位控制。 |
MaPeriod、MaShift、MaMethod |
移动平均周期、回溯偏移与计算方式。 |
LevelUpPips、LevelDownPips |
上下轨偏移(点),下轨可填负值。 |
StochasticKPeriod、StochasticDPeriod、StochasticSlowing |
随机指标设置。 |
StochasticLevel1、StochasticLevel2 |
进场确认阈值。 |
ReverseSignals |
是否反向开仓。 |
实现细节
- 通过高阶 API (
SubscribeCandles().BindEx(...)) 订阅蜡烛与指标,避免手动管理数据缓冲。
- 点值会根据品种小数位数自动转换:3/5 位报价将
PriceStep 乘以 10。
- 追踪止损在收盘 K 线上执行,若需要更细粒度的移动,可改为订阅逐笔或价格流。
- 按要求未提供 Python 版本,因此没有
PY 目录。
与原始 EA 的差异
- 风险计算显式依赖 StockSharp 的账户权益与步长报价,等价替代
CMoneyFixedMargin。若未配置止损,则风险距离为 0,系统拒绝开仓,与 MQL 的返回零手数完全一致。
- 止损、止盈与追踪判断基于完整 K 线,契合 StockSharp 事件驱动的运行方式,便于回测复现。
- 原版的
InpPrintLog 调试输出未移植,改用框架内建的日志机制。
该策略适用于在 StockSharp Designer、Runner 等环境中复用原有的 MetaTrader 交易逻辑,可根据标的和时间框架调整参数。
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 IMAIStochasticCustomStrategy : 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 IMAIStochasticCustomStrategy()
{
_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 imai_stochastic_custom_strategy(Strategy):
def __init__(self):
super(imai_stochastic_custom_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(imai_stochastic_custom_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(imai_stochastic_custom_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 imai_stochastic_custom_strategy()