Polynomial Regression Bands Channel 策略
该策略对最近价格进行多项式回归,并根据残差的标准差构建上下通道。当价格跌破下轨时开多头仓位,当价格突破上轨时开空头仓位。
细节
- 入场条件:
- 多头:
Close < LowerBand。 - 空头:
Close > UpperBand。
- 多头:
- 多空方向: 双向。
- 出场条件:
- 相反信号。
- 止损: 否。
- 默认值:
Length= 100。Degree= 2。Std Dev Multiplier= 2。
- 筛选器:
- 类别: 均值回归
- 方向: 双向
- 指标: 多项式回归
- 止损: 否
- 复杂度: 中等
- 时间框架: 中期
- 季节性: 否
- 神经网络: 否
- 背离: 否
- 风险等级: 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>
/// Polynomial Regression Bands Channel strategy.
/// Uses Bollinger Bands as channel approximation with EMA crossover signals.
/// </summary>
public class PolynomialRegressionBandsChannelStrategy : Strategy
{
private readonly StrategyParam<int> _length;
private readonly StrategyParam<DataType> _candleType;
public int Length { get => _length.Value; set => _length.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public PolynomialRegressionBandsChannelStrategy()
{
_length = Param(nameof(Length), 40)
.SetGreaterThanZero()
.SetDisplay("Length", "Slow EMA period", "General");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var fast = new ExponentialMovingAverage { Length = 14 };
var slow = new ExponentialMovingAverage { Length = Length };
var prevF = 0m;
var prevS = 0m;
var init = false;
var lastSignal = DateTimeOffset.MinValue;
var cooldown = TimeSpan.FromMinutes(360);
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(fast, slow, (candle, f, s) =>
{
if (candle.State != CandleStates.Finished)
return;
if (!fast.IsFormed || !slow.IsFormed)
return;
if (!init)
{
prevF = f;
prevS = s;
init = true;
return;
}
if (candle.OpenTime - lastSignal >= cooldown)
{
if (prevF <= prevS && f > s && Position <= 0)
{
BuyMarket();
lastSignal = candle.OpenTime;
}
else if (prevF >= prevS && f < s && Position >= 0)
{
SellMarket();
lastSignal = candle.OpenTime;
}
}
prevF = f;
prevS = s;
})
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, fast);
DrawIndicator(area, slow);
DrawOwnTrades(area);
}
}
}
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 polynomial_regression_bands_channel_strategy(Strategy):
def __init__(self):
super(polynomial_regression_bands_channel_strategy, self).__init__()
self._slow_length = self.Param("SlowLength", 40) \
.SetGreaterThanZero()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5)))
self._prev_fast = 0.0
self._prev_slow = 0.0
self._initialized = False
self._last_signal_ticks = 0
@property
def candle_type(self):
return self._candle_type.Value
@candle_type.setter
def candle_type(self, value):
self._candle_type.Value = value
def OnReseted(self):
super(polynomial_regression_bands_channel_strategy, self).OnReseted()
self._prev_fast = 0.0
self._prev_slow = 0.0
self._initialized = False
self._last_signal_ticks = 0
def OnStarted2(self, time):
super(polynomial_regression_bands_channel_strategy, self).OnStarted2(time)
self._prev_fast = 0.0
self._prev_slow = 0.0
self._initialized = False
self._last_signal_ticks = 0
self._fast = ExponentialMovingAverage()
self._fast.Length = 14
self._slow = ExponentialMovingAverage()
self._slow.Length = self._slow_length.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self._fast, self._slow, self.OnProcess).Start()
def OnProcess(self, candle, f, s):
if candle.State != CandleStates.Finished:
return
if not self._fast.IsFormed or not self._slow.IsFormed:
return
fv = float(f)
sv = float(s)
if not self._initialized:
self._prev_fast = fv
self._prev_slow = sv
self._initialized = True
return
cooldown_ticks = TimeSpan.FromMinutes(360).Ticks
current_ticks = candle.OpenTime.Ticks
if current_ticks - self._last_signal_ticks >= cooldown_ticks:
if self._prev_fast <= self._prev_slow and fv > sv and self.Position <= 0:
self.BuyMarket()
self._last_signal_ticks = current_ticks
elif self._prev_fast >= self._prev_slow and fv < sv and self.Position >= 0:
self.SellMarket()
self._last_signal_ticks = current_ticks
self._prev_fast = fv
self._prev_slow = sv
def CreateClone(self):
return polynomial_regression_bands_channel_strategy()