Стратегия Volume Weighted MA StdDev
Эта стратегия использует объёмно-взвешенное скользящее среднее (VWMA) в сочетании с фильтром стандартного отклонения. Анализируется изменение VWMA на каждом баре. Если положительное изменение превышает порог, равный произведению стандартного отклонения и коэффициента K1, открывается длинная позиция. Если отрицательное изменение меньше отрицательного порога, открывается короткая позиция. Методика позволяет входить в сделки только при наличии устойчивого движения, подтверждённого объёмом.
Параметры
- Тип свечей
- Период VWMA
- Период StdDev
- K1
- K2
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>
/// Volume Weighted Moving Average with Standard Deviation filter.
/// Opens long when VWMA momentum exceeds threshold, short on opposite.
/// </summary>
public class VolumeWeightedMaStDevStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _vwmaLength;
private readonly StrategyParam<int> _stdPeriod;
private readonly StrategyParam<decimal> _k1;
private VolumeWeightedMovingAverage _vwma;
private StandardDeviation _stdDev;
private decimal? _prevVwma;
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public int VwmaLength { get => _vwmaLength.Value; set => _vwmaLength.Value = value; }
public int StdPeriod { get => _stdPeriod.Value; set => _stdPeriod.Value = value; }
public decimal K1 { get => _k1.Value; set => _k1.Value = value; }
public VolumeWeightedMaStDevStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Time frame for analysis", "General");
_vwmaLength = Param(nameof(VwmaLength), 12)
.SetDisplay("VWMA Length", "Period for Volume Weighted MA", "Indicators");
_stdPeriod = Param(nameof(StdPeriod), 9)
.SetDisplay("StdDev Period", "Period for standard deviation", "Indicators");
_k1 = Param(nameof(K1), 0.5m)
.SetDisplay("K1", "Deviation multiplier for signal threshold", "Signal");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_vwma = null;
_stdDev = null;
_prevVwma = null;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_prevVwma = null;
_vwma = new VolumeWeightedMovingAverage { Length = VwmaLength };
_stdDev = new StandardDeviation { Length = StdPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(_vwma, ProcessCandle)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, _vwma);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal vwmaValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!_vwma.IsFormed)
return;
var t = candle.ServerTime;
if (_prevVwma is null)
{
_prevVwma = vwmaValue;
return;
}
var diff = vwmaValue - _prevVwma.Value;
var stdResult = _stdDev.Process(new DecimalIndicatorValue(_stdDev, diff, t) { IsFinal = true });
if (!_stdDev.IsFormed)
{
_prevVwma = vwmaValue;
return;
}
var stdValue = stdResult.ToDecimal();
var filter = K1 * stdValue;
if (diff > filter && Position <= 0)
BuyMarket();
else if (diff < -filter && Position >= 0)
SellMarket();
_prevVwma = vwmaValue;
}
}
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 VolumeWeightedMovingAverage, StandardDeviation
from StockSharp.Algo.Strategies import Strategy
from indicator_extensions import *
class volume_weighted_ma_st_dev_strategy(Strategy):
def __init__(self):
super(volume_weighted_ma_st_dev_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Time frame for analysis", "General")
self._vwma_length = self.Param("VwmaLength", 12) \
.SetDisplay("VWMA Length", "Period for Volume Weighted MA", "Indicators")
self._std_period = self.Param("StdPeriod", 9) \
.SetDisplay("StdDev Period", "Period for standard deviation", "Indicators")
self._k1 = self.Param("K1", 0.5) \
.SetDisplay("K1", "Deviation multiplier for signal threshold", "Signal")
self._vwma = None
self._std_dev = None
self._prev_vwma = None
@property
def candle_type(self):
return self._candle_type.Value
@property
def vwma_length(self):
return self._vwma_length.Value
@property
def std_period(self):
return self._std_period.Value
@property
def k1(self):
return self._k1.Value
def OnReseted(self):
super(volume_weighted_ma_st_dev_strategy, self).OnReseted()
self._vwma = None
self._std_dev = None
self._prev_vwma = None
def OnStarted2(self, time):
super(volume_weighted_ma_st_dev_strategy, self).OnStarted2(time)
self._prev_vwma = None
self._vwma = VolumeWeightedMovingAverage()
self._vwma.Length = self.vwma_length
self._std_dev = StandardDeviation()
self._std_dev.Length = self.std_period
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self._vwma, self.process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, self._vwma)
self.DrawOwnTrades(area)
def process_candle(self, candle, vwma_value):
if candle.State != CandleStates.Finished:
return
if not self._vwma.IsFormed:
return
vwma_value = float(vwma_value)
if self._prev_vwma is None:
self._prev_vwma = vwma_value
return
diff = vwma_value - self._prev_vwma
std_result = process_float(self._std_dev, diff, candle.ServerTime, True)
if not self._std_dev.IsFormed:
self._prev_vwma = vwma_value
return
std_value = float(std_result)
k1 = float(self.k1)
filter_val = k1 * std_value
if diff > filter_val and self.Position <= 0:
self.BuyMarket()
elif diff < -filter_val and self.Position >= 0:
self.SellMarket()
self._prev_vwma = vwma_value
def CreateClone(self):
return volume_weighted_ma_st_dev_strategy()