即时趋势滤波策略
该策略利用约翰·埃勒斯的即时趋势线和触发线,在任何时间框架上产生交易信号。触发线计算为 2 * ITrend - ITrend[2],形成一条快速线与较慢的趋势线交叉。当触发线从上向下穿越趋势线时,关闭空头并开多;当触发线从下向上穿越趋势线时,关闭多头并开空。平滑参数 Alpha 控制反应速度:值越小,曲线越平滑;值越大,反应越快。
详情
- 入场条件:
- 多头:前一根柱子触发线在趋势线之上,当前柱子向下穿越趋势线。
- 空头:前一根柱子触发线在趋势线之下,当前柱子向上穿越趋势线。
- 多空方向:双向。
- 出场条件:
- 出现空头信号时平掉多头。
- 出现多头信号时平掉空头。
- 止损:默认没有。
- 默认值:
Alpha= 0.07。Candle Type= 4 小时周期。
- 过滤器:
- 类别:趋势跟随
- 方向:双向
- 指标:单一
- 止损:否
- 复杂度:简单
- 时间框架:中期
- 季节性:否
- 神经网络:否
- 背离:否
- 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>
/// Instantaneous Trend Filter strategy.
/// Uses a custom digital filter formula to detect trend changes.
/// </summary>
public class InstantaneousTrendFilterStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<decimal> _alpha;
private decimal _k0, _k1, _k2, _k3, _k4;
private decimal _prevClose;
private decimal _prevPrevClose;
private decimal _itrendPrev1;
private decimal _itrendPrev2;
private decimal _triggerPrev;
private int _bars;
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public decimal Alpha { get => _alpha.Value; set => _alpha.Value = value; }
public InstantaneousTrendFilterStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Timeframe for analysis", "General");
_alpha = Param(nameof(Alpha), 0.07m)
.SetDisplay("Alpha", "Filter smoothing coefficient", "Indicator");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_bars = default;
_prevClose = default;
_prevPrevClose = default;
_itrendPrev1 = default;
_itrendPrev2 = default;
_triggerPrev = default;
_k0 = default;
_k1 = default;
_k2 = default;
_k3 = default;
_k4 = default;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_bars = 0;
var a2 = Alpha * Alpha;
_k0 = Alpha - a2 / 4m;
_k1 = 0.5m * a2;
_k2 = Alpha - 0.75m * a2;
_k3 = 2m * (1m - Alpha);
_k4 = (1m - Alpha) * (1m - Alpha);
var subscription = SubscribeCandles(CandleType);
subscription.Bind(ProcessCandle).Start();
}
private void ProcessCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
var close = candle.ClosePrice;
decimal itrend;
if (_bars < 2)
itrend = close;
else if (_bars < 4)
itrend = (close + 2m * _prevClose + _prevPrevClose) / 4m;
else
itrend = _k0 * close + _k1 * _prevClose - _k2 * _prevPrevClose + _k3 * _itrendPrev1 - _k4 * _itrendPrev2;
var trigger = 2m * itrend - _itrendPrev2;
var crossDown = _triggerPrev > _itrendPrev1 && trigger < itrend;
var crossUp = _triggerPrev < _itrendPrev1 && trigger > itrend;
if (crossDown && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
else if (crossUp && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_itrendPrev2 = _itrendPrev1;
_itrendPrev1 = itrend;
_triggerPrev = trigger;
_prevPrevClose = _prevClose;
_prevClose = close;
_bars++;
}
}
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
class instantaneous_trend_filter_strategy(Strategy):
def __init__(self):
super(instantaneous_trend_filter_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Timeframe for analysis", "General")
self._alpha = self.Param("Alpha", 0.07) \
.SetDisplay("Alpha", "Filter smoothing coefficient", "Indicator")
self._k0 = 0.0
self._k1 = 0.0
self._k2 = 0.0
self._k3 = 0.0
self._k4 = 0.0
self._prev_close = 0.0
self._prev_prev_close = 0.0
self._itrend_prev1 = 0.0
self._itrend_prev2 = 0.0
self._trigger_prev = 0.0
self._bars = 0
@property
def candle_type(self):
return self._candle_type.Value
@property
def alpha(self):
return self._alpha.Value
def OnReseted(self):
super(instantaneous_trend_filter_strategy, self).OnReseted()
self._bars = 0
self._prev_close = 0.0
self._prev_prev_close = 0.0
self._itrend_prev1 = 0.0
self._itrend_prev2 = 0.0
self._trigger_prev = 0.0
self._k0 = 0.0
self._k1 = 0.0
self._k2 = 0.0
self._k3 = 0.0
self._k4 = 0.0
def OnStarted2(self, time):
super(instantaneous_trend_filter_strategy, self).OnStarted2(time)
self._bars = 0
a = float(self.alpha)
a2 = a * a
self._k0 = a - a2 / 4.0
self._k1 = 0.5 * a2
self._k2 = a - 0.75 * a2
self._k3 = 2.0 * (1.0 - a)
self._k4 = (1.0 - a) * (1.0 - a)
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self.process_candle).Start()
def process_candle(self, candle):
if candle.State != CandleStates.Finished:
return
close = float(candle.ClosePrice)
if self._bars < 2:
itrend = close
elif self._bars < 4:
itrend = (close + 2.0 * self._prev_close + self._prev_prev_close) / 4.0
else:
itrend = (self._k0 * close + self._k1 * self._prev_close -
self._k2 * self._prev_prev_close + self._k3 * self._itrend_prev1 -
self._k4 * self._itrend_prev2)
trigger = 2.0 * itrend - self._itrend_prev2
cross_down = self._trigger_prev > self._itrend_prev1 and trigger < itrend
cross_up = self._trigger_prev < self._itrend_prev1 and trigger > itrend
if cross_down and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif cross_up and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._itrend_prev2 = self._itrend_prev1
self._itrend_prev1 = itrend
self._trigger_prev = trigger
self._prev_prev_close = self._prev_close
self._prev_close = close
self._bars += 1
def CreateClone(self):
return instantaneous_trend_filter_strategy()