Amstell SL 平均策略
基于 MetaTrader 顾问 exp_Amstell-SL 的移植版本。策略启动后立即同时开出一笔买单和卖单,当价格相对于最近一次进场逆向移动到达设定的点数时继续加仓,并通过程序化的虚拟止盈与止损来逐笔平仓。
策略逻辑
- 初始建仓:启动时若没有持仓,立即以市价在卖价(Ask)买入一单,同时在买价(Bid)卖出一单。
- 逆势加仓:
- 多头方向:当当前卖价比最后一次买入价低
ReentryPoints(默认 10 点)时,再买入同样手数。 - 空头方向:当当前买价比最后一次卖出价高
ReentryPoints时,再卖出同样手数。
- 多头方向:当当前卖价比最后一次买入价低
- 退出规则(虚拟管理):
- 对每笔买入单同时监控最优买价与卖价。当买价较开仓价上升
TakeProfitPoints点,或卖价较开仓价下降StopLossPoints点时,通过市价卖出平仓。 - 对每笔卖出单,当卖价比开仓价低
TakeProfitPoints点,或买价比开仓价高StopLossPoints点时,通过市价买入回补。
- 对每笔买入单同时监控最优买价与卖价。当买价较开仓价上升
- 处理顺序:优先检查平仓条件,只要有订单被关闭,本次数据处理即结束,不再考虑新的入场,完全复制原始 EA 在每个 tick 上的行为。
参数
TakeProfitPoints– 止盈距离(以价格最小变动单位计)。默认值:30。StopLossPoints– 止损距离(价格最小变动单位)。默认值:30。Volume– 每次开仓的手数。默认值:0.01。ReentryPoints– 逆势加仓所需的点数距离。默认值:10。
额外说明
- 点值来自
Security.PriceStep;如果交易所未提供,则使用1作为最小价位变动。 - 策略独立跟踪多头与空头仓位,因此可以同时持有多单与空单,符合原始顾问的对冲模式。
- 止盈与止损并不会在交易所挂出真实委托,而是通过市价单虚拟执行。
- 若市场单边趋势延续,仓位会持续加码,风险暴露增长迅速,应谨慎控制最大仓位与资金使用。
- 更适合用于点值等于最小价格跳动的品种,例如多数基于 MetaTrader 报价的外汇品种。
using System;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Amstell SL: Grid averaging strategy with ATR-based take profit and stop loss.
/// Adds positions on adverse moves and exits on profit/stop targets.
/// </summary>
public class AmstellSlStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _atrLength;
private readonly StrategyParam<int> _emaLength;
private decimal _entryPrice;
private decimal _prevEma;
private int _gridCount;
private int _cooldown;
public AmstellSlStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(8).TimeFrame())
.SetDisplay("Candle Type", "Timeframe.", "General");
_atrLength = Param(nameof(AtrLength), 14)
.SetDisplay("ATR Length", "ATR period.", "Indicators");
_emaLength = Param(nameof(EmaLength), 50)
.SetDisplay("EMA Length", "EMA trend filter.", "Indicators");
}
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public int AtrLength
{
get => _atrLength.Value;
set => _atrLength.Value = value;
}
public int EmaLength
{
get => _emaLength.Value;
set => _emaLength.Value = value;
}
/// <inheritdoc />
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_entryPrice = 0;
_prevEma = 0;
_gridCount = 0;
_cooldown = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_entryPrice = 0;
_prevEma = 0;
_gridCount = 0;
_cooldown = 0;
var atr = new AverageTrueRange { Length = AtrLength };
var ema = new ExponentialMovingAverage { Length = EmaLength };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(atr, ema, ProcessCandle)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, ema);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal atrVal, decimal emaVal)
{
if (candle.State != CandleStates.Finished)
return;
if (atrVal <= 0 || _prevEma == 0)
{
_prevEma = emaVal;
return;
}
if (_cooldown > 0)
{
_cooldown--;
_prevEma = emaVal;
if (Position == 0) return;
}
var close = candle.ClosePrice;
// Position management with grid and stops
if (Position > 0)
{
if (close >= _entryPrice + atrVal * 2.5m)
{
SellMarket();
_entryPrice = 0;
_gridCount = 0;
_cooldown = 10;
}
else if (close <= _entryPrice - atrVal * 4m)
{
SellMarket();
_entryPrice = 0;
_gridCount = 0;
_cooldown = 10;
}
else if (_gridCount < 1 && close <= _entryPrice - atrVal * 2m)
{
_entryPrice = (_entryPrice + close) / 2m;
_gridCount++;
BuyMarket();
}
}
else if (Position < 0)
{
if (close <= _entryPrice - atrVal * 2.5m)
{
BuyMarket();
_entryPrice = 0;
_gridCount = 0;
_cooldown = 10;
}
else if (close >= _entryPrice + atrVal * 4m)
{
BuyMarket();
_entryPrice = 0;
_gridCount = 0;
_cooldown = 10;
}
else if (_gridCount < 1 && close >= _entryPrice + atrVal * 2m)
{
_entryPrice = (_entryPrice + close) / 2m;
_gridCount++;
SellMarket();
}
}
// Entry on EMA trend
if (Position == 0 && _cooldown == 0)
{
if (close > emaVal && emaVal > _prevEma)
{
_entryPrice = close;
_gridCount = 0;
BuyMarket();
}
else if (close < emaVal && emaVal < _prevEma)
{
_entryPrice = close;
_gridCount = 0;
SellMarket();
}
}
_prevEma = emaVal;
}
}
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.Strategies import Strategy
from StockSharp.Algo.Indicators import AverageTrueRange, ExponentialMovingAverage
class amstell_sl_strategy(Strategy):
def __init__(self):
super(amstell_sl_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(8))) \
.SetDisplay("Candle Type", "Timeframe.", "General")
self._atr_length = self.Param("AtrLength", 14) \
.SetDisplay("ATR Length", "ATR period.", "Indicators")
self._ema_length = self.Param("EmaLength", 50) \
.SetDisplay("EMA Length", "EMA trend filter.", "Indicators")
self._entry_price = 0.0
self._prev_ema = 0.0
self._grid_count = 0
self._cooldown = 0
@property
def CandleType(self):
return self._candle_type.Value
@property
def AtrLength(self):
return self._atr_length.Value
@property
def EmaLength(self):
return self._ema_length.Value
def OnStarted2(self, time):
super(amstell_sl_strategy, self).OnStarted2(time)
self._entry_price = 0.0
self._prev_ema = 0.0
self._grid_count = 0
self._cooldown = 0
self._atr = AverageTrueRange()
self._atr.Length = self.AtrLength
self._ema = ExponentialMovingAverage()
self._ema.Length = self.EmaLength
subscription = self.SubscribeCandles(self.CandleType)
subscription.Bind(self._atr, self._ema, self.ProcessCandle).Start()
def ProcessCandle(self, candle, atr_val, ema_val):
if candle.State != CandleStates.Finished:
return
av = float(atr_val)
ev = float(ema_val)
if av <= 0 or self._prev_ema == 0:
self._prev_ema = ev
return
if self._cooldown > 0:
self._cooldown -= 1
self._prev_ema = ev
if self.Position == 0:
return
close = float(candle.ClosePrice)
# Position management with grid and stops
if self.Position > 0:
if close >= self._entry_price + av * 2.5:
self.SellMarket()
self._entry_price = 0.0
self._grid_count = 0
self._cooldown = 10
elif close <= self._entry_price - av * 4.0:
self.SellMarket()
self._entry_price = 0.0
self._grid_count = 0
self._cooldown = 10
elif self._grid_count < 1 and close <= self._entry_price - av * 2.0:
self._entry_price = (self._entry_price + close) / 2.0
self._grid_count += 1
self.BuyMarket()
elif self.Position < 0:
if close <= self._entry_price - av * 2.5:
self.BuyMarket()
self._entry_price = 0.0
self._grid_count = 0
self._cooldown = 10
elif close >= self._entry_price + av * 4.0:
self.BuyMarket()
self._entry_price = 0.0
self._grid_count = 0
self._cooldown = 10
elif self._grid_count < 1 and close >= self._entry_price + av * 2.0:
self._entry_price = (self._entry_price + close) / 2.0
self._grid_count += 1
self.SellMarket()
if not self.IsFormedAndOnlineAndAllowTrading():
self._prev_ema = ev
return
# Entry on EMA trend
if self.Position == 0 and self._cooldown == 0:
if close > ev and ev > self._prev_ema:
self._entry_price = close
self._grid_count = 0
self.BuyMarket()
elif close < ev and ev < self._prev_ema:
self._entry_price = close
self._grid_count = 0
self.SellMarket()
self._prev_ema = ev
def OnReseted(self):
super(amstell_sl_strategy, self).OnReseted()
self._entry_price = 0.0
self._prev_ema = 0.0
self._grid_count = 0
self._cooldown = 0
def CreateClone(self):
return amstell_sl_strategy()