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AutoAdjustingStrategy
AutoAdjustingStrategy 将 MetaTrader 专家顾问 Aouto Adjusting1 迁移到 StockSharp 的高级 API。策略保留了原始的多周期动量过滤、月线 MACD 趋势确认以及三重 EMA 结构,用于识别趋势内回调。止损与止盈基于最近摆动高低点计算,并在每根完成的 K 线后自动更新。
策略逻辑
- 趋势结构:交易周期上的三条 EMA(6、14、26)必须同向排列(做多要求
EMA6 < EMA14 < EMA26,做空相反)。最近一根已完成 K 线需要触碰中间 EMA,再上一根 K 线形成更高的低点 / 更低的高点以确认回调。
- 动量确认:在更高周期(依据交易周期映射,例如 H1→D1)上计算的 Momentum 指标需在最近三根完成 K 线中任意一次相对 100 偏离至少
MomentumBuyThreshold / MomentumSellThreshold。
- 宏观过滤:月线 MACD(12, 26, 9) 用于确认大趋势方向(
MACD > Signal 允许做多,< 允许做空)。
- 执行:当所有过滤条件满足且不存在反向持仓时,以市价开仓;若存在反向仓位,先平仓再开新单。
- 风险防护:止损设置在最近
CandlesBack 根 K 线最低点/最高点之外 PadAmount 个点,止盈距离为止损距离乘以 RewardRatio。持仓期间,每根 K 线收盘都会重新布置保护单。
风险管理与仓位
RiskPercent 会在获取到组合权益和价格步长数据时,按风险金额 / 单位亏损的方式计算自适应手数。
- 若无法完成风险计算(例如缺少权益信息),则使用固定的
TradeVolume 作为下单量。
参数
| 名称 |
类型 |
默认值 |
说明 |
CandleType |
DataType |
TimeFrame(H1) |
交易周期,三条 EMA 在此周期上计算。 |
MomentumCandleType |
DataType |
基于 CandleType 映射 |
动量指标所用的更高周期(H1→D1、H4→W1 等)。 |
MacroMacdCandleType |
DataType |
TimeFrame(30 days) |
宏观 MACD 所用的时间框架,默认约等于月线。 |
PadAmount |
decimal |
3 |
在摆动低/高点之外追加的点数,用于设置止损。 |
RiskPercent |
decimal |
0.1 |
单笔交易允许的权益风险百分比。 |
RewardRatio |
decimal |
2 |
止盈距离 = 止损距离 × 此系数。 |
CandlesBack |
int |
3 |
回溯多少根 K 线来寻找最新的高低点。 |
MomentumBuyThreshold |
decimal |
0.3 |
触发多头信号所需的最小动量偏离值。 |
MomentumSellThreshold |
decimal |
0.3 |
触发空头信号所需的最小动量偏离值。 |
TradeVolume |
decimal |
1 |
当无法计算风险仓位时的备用下单手数。 |
可视化建议
- 在主图上绘制交易周期的 K 线与三条 EMA,观察价格回调情况。
- 在副图展示更高周期的 Momentum 指标,检查是否达到阈值。
- 关注宏观周期的 MACD 数值,确认趋势过滤方向。
备注
- 时间框架映射遵循原始 EA:M1→M15、M5→M30、M15→H1、M30→H4、H1→D1、H4→W1、D1→MN1,其余周期保持不变。
- 策略不调用指标的
GetValue,而是通过 Bind 回调保存最新值,符合项目要求。
- 按原策略思路,每根 K 线收盘后都会重新计算并布置止损与止盈,实现“自动调节”的行为。
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 AutoAdjustingStrategy : 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 AutoAdjustingStrategy()
{
_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 auto_adjusting_strategy(Strategy):
def __init__(self):
super(auto_adjusting_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(auto_adjusting_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(auto_adjusting_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 auto_adjusting_strategy()