Einfaches APF-Strategie-Backtesting
Diese Strategie implementiert ein vereinfachtes Autokorrelations-Preisvorhersage-Modell (APF). Sie erkennt Preiszyklen über Autokorrelation und prognostiziert zukünftige Preise mithilfe einer linearen Regression der jüngsten Renditen. Eine Long-Position wird eröffnet, wenn der vorhergesagte Gewinn einen angegebenen Schwellenwert überschreitet. Die Position wird geschlossen, wenn der Zielpreis erreicht ist.
Parameter
Length– Anzahl der Balken für Autokorrelation und Regression.Threshold Gain– minimaler erwarteter Kursanstieg für einen Einstieg.Signal Threshold– Autokorrelationsniveau, das zum Speichern einer Prognose erforderlich ist.Candle Type– Kerzentyp für Berechnungen.
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>
/// Simple APF backtesting strategy using EMA crossover.
/// </summary>
public class SimpleApfBacktestingStrategy : Strategy
{
private readonly StrategyParam<int> _slowLength;
private readonly StrategyParam<DataType> _candleType;
public int SlowLength { get => _slowLength.Value; set => _slowLength.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public SimpleApfBacktestingStrategy()
{
_slowLength = Param(nameof(SlowLength), 40)
.SetGreaterThanZero()
.SetDisplay("Slow Length", "Slow EMA period", "General");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
.SetDisplay("Candle Type", "Candle type", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var fast = new ExponentialMovingAverage { Length = 14 };
var slow = new ExponentialMovingAverage { Length = SlowLength };
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 simple_apf_backtesting_strategy(Strategy):
def __init__(self):
super(simple_apf_backtesting_strategy, self).__init__()
self._slow_length = self.Param("SlowLength", 40) \
.SetGreaterThanZero() \
.SetDisplay("Slow Length", "Slow EMA period", "General")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))) \
.SetDisplay("Candle Type", "Candle type", "General")
self._prev_f = 0.0
self._prev_s = 0.0
self._init = False
self._last_signal_ticks = 0
@property
def slow_length(self):
return self._slow_length.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(simple_apf_backtesting_strategy, self).OnReseted()
self._prev_f = 0.0
self._prev_s = 0.0
self._init = False
self._last_signal_ticks = 0
def OnStarted2(self, time):
super(simple_apf_backtesting_strategy, self).OnStarted2(time)
self._fast = ExponentialMovingAverage()
self._fast.Length = 14
self._slow = ExponentialMovingAverage()
self._slow.Length = self.slow_length
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self._fast, self._slow, self.on_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, self._fast)
self.DrawIndicator(area, self._slow)
self.DrawOwnTrades(area)
def on_candle(self, candle, f, s):
if candle.State != CandleStates.Finished:
return
if not self._fast.IsFormed or not self._slow.IsFormed:
return
f = float(f)
s = float(s)
if not self._init:
self._prev_f = f
self._prev_s = s
self._init = 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_f <= self._prev_s and f > s and self.Position <= 0:
self.BuyMarket()
self._last_signal_ticks = current_ticks
elif self._prev_f >= self._prev_s and f < s and self.Position >= 0:
self.SellMarket()
self._last_signal_ticks = current_ticks
self._prev_f = f
self._prev_s = s
def CreateClone(self):
return simple_apf_backtesting_strategy()