Diese Strategie überwacht den Parabolic SAR (Stop and Reverse) Indikator, um potenzielle Trendumkehrungen zu erkennen. Wenn der SAR-Wert von oberhalb des Preises nach unterhalb wechselt, interpretiert der Algorithmus dies als bullisches Signal und eröffnet eine Long-Position. Wenn der SAR sich von unterhalb des Preises nach oben bewegt, wird eine Short-Position eröffnet.
Der Standard-Beschleunigungsfaktor (0.02) und die maximale Beschleunigung (0.2) folgen der klassischen Parabolic SAR-Konfiguration. Diese Parameter steuern, wie schnell sich der Indikator dem Preis nähert: höhere Werte lassen den SAR schneller reagieren, können aber zu Fehlsignalen führen. Die Strategie verarbeitet nur abgeschlossene Kerzen und speichert vorherige SAR- und Preiswerte, um Kreuzungen ohne historische Datenbankabfragen zu identifizieren.
Das Risikomanagement ist nicht explizit definiert; das Beispiel verlässt sich auf entgegengesetzte Signale zum Ausstieg. Zusätzlicher Schutz kann über die integrierten Mechanismen des Frameworks aktiviert werden.
Details
Einstiegskriterien: Parabolic SAR kreuzt den Schlusskurs.
Long/Short: Beide.
Ausstiegskriterien: Gegensignal.
Stops: Nicht definiert.
Standardwerte:
InitialAcceleration = 0.02
MaxAcceleration = 0.2
CandleType = 5 minute
Filter:
Kategorie: Trendfolge
Richtung: Beide
Indikatoren: Parabolic SAR
Stops: Optional
Komplexität: Grundlegend
Zeitrahmen: Intraday
Saisonalität: Nein
Neuronale Netze: Nein
Divergenz: Nein
Risikolevel: Mittel
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>
/// Parabolic SAR Alert Strategy.
/// Opens long or short positions when Parabolic SAR flips relative to price.
/// </summary>
public class ParabolicSarAlertStrategy : Strategy
{
private readonly StrategyParam<decimal> _initialAcceleration;
private readonly StrategyParam<decimal> _maxAcceleration;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevSar;
private decimal _prevClose;
private bool _initialized;
public decimal InitialAcceleration { get => _initialAcceleration.Value; set => _initialAcceleration.Value = value; }
public decimal MaxAcceleration { get => _maxAcceleration.Value; set => _maxAcceleration.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public ParabolicSarAlertStrategy()
{
_initialAcceleration = Param(nameof(InitialAcceleration), 0.02m)
.SetDisplay("Initial Acceleration", "Initial acceleration factor for Parabolic SAR", "SAR Settings");
_maxAcceleration = Param(nameof(MaxAcceleration), 0.2m)
.SetDisplay("Max Acceleration", "Maximum acceleration factor for Parabolic SAR", "SAR Settings");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
protected override void OnReseted()
{
base.OnReseted();
_prevSar = 0;
_prevClose = 0;
_initialized = false;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var parabolicSar = new ParabolicSar
{
Acceleration = InitialAcceleration,
AccelerationMax = MaxAcceleration
};
SubscribeCandles(CandleType)
.Bind(parabolicSar, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal sarValue)
{
if (candle.State != CandleStates.Finished) return;
if (!_initialized)
{
_prevSar = sarValue;
_prevClose = candle.ClosePrice;
_initialized = true;
return;
}
var crossUp = _prevSar > _prevClose && sarValue < candle.ClosePrice;
var crossDown = _prevSar < _prevClose && sarValue > candle.ClosePrice;
if (crossUp && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
else if (crossDown && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_prevSar = sarValue;
_prevClose = candle.ClosePrice;
}
}
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 ParabolicSar
from StockSharp.Algo.Strategies import Strategy
class parabolic_sar_alert_strategy(Strategy):
def __init__(self):
super(parabolic_sar_alert_strategy, self).__init__()
self._initial_acceleration = self.Param("InitialAcceleration", 0.02) \
.SetDisplay("Initial Acceleration", "Initial acceleration factor for Parabolic SAR", "SAR Settings")
self._max_acceleration = self.Param("MaxAcceleration", 0.2) \
.SetDisplay("Max Acceleration", "Maximum acceleration factor for Parabolic SAR", "SAR Settings")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles to use", "General")
self._prev_sar = 0.0
self._prev_close = 0.0
self._initialized = False
@property
def initial_acceleration(self):
return self._initial_acceleration.Value
@property
def max_acceleration(self):
return self._max_acceleration.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(parabolic_sar_alert_strategy, self).OnReseted()
self._prev_sar = 0.0
self._prev_close = 0.0
self._initialized = False
def OnStarted2(self, time):
super(parabolic_sar_alert_strategy, self).OnStarted2(time)
parabolic_sar = ParabolicSar()
parabolic_sar.Acceleration = self.initial_acceleration
parabolic_sar.AccelerationMax = self.max_acceleration
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(parabolic_sar, self.on_process).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
def on_process(self, candle, sar_value):
if candle.State != CandleStates.Finished:
return
if not self._initialized:
self._prev_sar = sar_value
self._prev_close = candle.ClosePrice
self._initialized = True
return
cross_up = self._prev_sar > self._prev_close and sar_value < candle.ClosePrice
cross_down = self._prev_sar < self._prev_close and sar_value > candle.ClosePrice
if cross_up and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif cross_down and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._prev_sar = sar_value
self._prev_close = candle.ClosePrice
def CreateClone(self):
return parabolic_sar_alert_strategy()