自适应市场水平
基于自适应市场水平(Adaptive Market Level,AML)指标的策略。该指标根据当前波动率动态调整价格水平。当AML线转向上时开多单,转向下时开空单。出现反向颜色变化或触发止损/止盈时平仓。
系统跟随中期趋势,默认在较高时间框架上运行。
细节
- 入场条件:AML线向上转折做多,向下转折做空。
- 多空方向:双向。
- 退出条件:AML方向改变或到达止损/止盈。
- 止损:有。
- 默认参数:
Fractal= 6Lag= 7StopLossTicks= 1000TakeProfitTicks= 2000BuyPosOpen= trueSellPosOpen= trueBuyPosClose= trueSellPosClose= trueCandleType= TimeSpan.FromHours(4)
- 过滤器:
- 类别: 趋势
- 方向: 双向
- 指标: Adaptive Market Level
- 止损: 有
- 复杂度: 中等
- 时间框架: H4
- 季节性: 无
- 神经网络: 无
- 背离: 无
- 风险级别: 中等
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;
/// <summary>
/// Adaptive market level strategy using SMA slope direction changes.
/// </summary>
public class AdaptiveMarketLevelStrategy : Strategy
{
private readonly StrategyParam<int> _period;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevSma;
private decimal _prevPrevSma;
private int _count;
public int Period { get => _period.Value; set => _period.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public AdaptiveMarketLevelStrategy()
{
_period = Param(nameof(Period), 14)
.SetGreaterThanZero()
.SetDisplay("Period", "SMA period", "Indicator");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevSma = 0;
_prevPrevSma = 0;
_count = 0;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var sma = new SimpleMovingAverage { Length = Period };
SubscribeCandles(CandleType)
.Bind(sma, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal smaValue)
{
if (candle.State != CandleStates.Finished)
return;
_count++;
if (_count < 3)
{
_prevPrevSma = _prevSma;
_prevSma = smaValue;
return;
}
var turnUp = _prevSma < _prevPrevSma && smaValue > _prevSma;
var turnDown = _prevSma > _prevPrevSma && smaValue < _prevSma;
if (turnUp && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
else if (turnDown && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_prevPrevSma = _prevSma;
_prevSma = smaValue;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class adaptive_market_level_strategy(Strategy):
def __init__(self):
super(adaptive_market_level_strategy, self).__init__()
self._period = self.Param("Period", 14) \
.SetDisplay("Period", "SMA period", "Indicator")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles", "General")
self._prev_sma = 0.0
self._prev_prev_sma = 0.0
self._count = 0
@property
def Period(self):
return self._period.Value
@Period.setter
def Period(self, value):
self._period.Value = value
@property
def CandleType(self):
return self._candle_type.Value
@CandleType.setter
def CandleType(self, value):
self._candle_type.Value = value
def OnStarted2(self, time):
super(adaptive_market_level_strategy, self).OnStarted2(time)
sma = SimpleMovingAverage()
sma.Length = self.Period
self.SubscribeCandles(self.CandleType) \
.Bind(sma, self.ProcessCandle) \
.Start()
def ProcessCandle(self, candle, sma_value):
if candle.State != CandleStates.Finished:
return
sma_val = float(sma_value)
self._count += 1
if self._count < 3:
self._prev_prev_sma = self._prev_sma
self._prev_sma = sma_val
return
turn_up = self._prev_sma < self._prev_prev_sma and sma_val > self._prev_sma
turn_down = self._prev_sma > self._prev_prev_sma and sma_val < self._prev_sma
if turn_up and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif turn_down and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._prev_prev_sma = self._prev_sma
self._prev_sma = sma_val
def OnReseted(self):
super(adaptive_market_level_strategy, self).OnReseted()
self._prev_sma = 0.0
self._prev_prev_sma = 0.0
self._count = 0
def CreateClone(self):
return adaptive_market_level_strategy()