Die Universeller Investor Strategie nutzt das Kreuzen zwischen dem Exponentiellen Gleitenden Durchschnitt (EMA) und dem Linear Gewichteten Gleitenden Durchschnitt (LWMA), um die Marktrichtung zu bestimmen. Die Trendstärke wird bestätigt, indem geprüft wird, dass sich beide Durchschnitte in dieselbe Richtung bewegen.
Logik
Kauf-Einstieg: LWMA liegt über EMA und beide Durchschnitte steigen.
Verkauf-Einstieg: LWMA liegt unter EMA und beide Durchschnitte fallen.
Kauf-Ausstieg: LWMA kreuzt unter EMA.
Verkauf-Ausstieg: LWMA kreuzt über EMA.
Die Strategie reduziert die Positionsgröße nach aufeinanderfolgenden Verlusttrades, wenn der Reduktionsfaktor aktiviert ist.
Parameter
Name
Beschreibung
MovingPeriod
Länge für EMA- und LWMA-Berechnungen.
DecreaseFactor
Lot-Reduktionsfaktor nach Verlusten (0 deaktiviert die Reduktion).
CandleType
Kerzendatentyp für Berechnungen.
Volume
Basis-Handelsvolumen aus den Strategieeinstellungen.
Hinweise
Funktioniert nur mit abgeschlossenen Kerzen.
Verwendet die High-Level-StockSharp-API mit Indikatorbindung.
Keine Python-Version vorhanden.
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>
/// Strategy based on EMA and WMA crossover with trend confirmation.
/// </summary>
public class UniversalInvestorStrategy : Strategy
{
private readonly StrategyParam<int> _movingPeriod;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevEma;
private decimal _prevLwma;
private bool _hasPrev;
public int MovingPeriod { get => _movingPeriod.Value; set => _movingPeriod.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public UniversalInvestorStrategy()
{
_movingPeriod = Param(nameof(MovingPeriod), 23)
.SetGreaterThanZero()
.SetDisplay("Moving Period", "Smoothing period for EMA and WMA", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles for calculations", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
protected override void OnReseted()
{
base.OnReseted();
_prevEma = 0;
_prevLwma = 0;
_hasPrev = false;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var ema = new ExponentialMovingAverage { Length = MovingPeriod };
var lwma = new WeightedMovingAverage { Length = MovingPeriod };
SubscribeCandles(CandleType)
.Bind(ema, lwma, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal emaValue, decimal lwmaValue)
{
if (candle.State != CandleStates.Finished) return;
if (!_hasPrev)
{
_prevEma = emaValue;
_prevLwma = lwmaValue;
_hasPrev = true;
return;
}
var openBuy = lwmaValue > emaValue && lwmaValue > _prevLwma && emaValue > _prevEma;
var openSell = lwmaValue < emaValue && lwmaValue < _prevLwma && emaValue < _prevEma;
var closeBuy = lwmaValue < emaValue;
var closeSell = lwmaValue > emaValue;
if (Position > 0 && closeBuy)
{
SellMarket();
}
else if (Position < 0 && closeSell)
{
BuyMarket();
}
else if (Position == 0)
{
if (openBuy && !closeBuy)
BuyMarket();
else if (openSell && !closeSell)
SellMarket();
}
_prevEma = emaValue;
_prevLwma = lwmaValue;
}
}
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, WeightedMovingAverage
from StockSharp.Algo.Strategies import Strategy
class universal_investor_strategy(Strategy):
def __init__(self):
super(universal_investor_strategy, self).__init__()
self._moving_period = self.Param("MovingPeriod", 23) \
.SetDisplay("Moving Period", "Smoothing period for EMA and WMA", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles for calculations", "General")
self._prev_ema = 0.0
self._prev_lwma = 0.0
self._has_prev = False
@property
def moving_period(self):
return self._moving_period.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(universal_investor_strategy, self).OnReseted()
self._prev_ema = 0.0
self._prev_lwma = 0.0
self._has_prev = False
def OnStarted2(self, time):
super(universal_investor_strategy, self).OnStarted2(time)
ema = ExponentialMovingAverage()
ema.Length = self.moving_period
lwma = WeightedMovingAverage()
lwma.Length = self.moving_period
self.SubscribeCandles(self.candle_type).Bind(ema, lwma, self.process_candle).Start()
def process_candle(self, candle, ema_value, lwma_value):
if candle.State != CandleStates.Finished:
return
ev = float(ema_value)
lv = float(lwma_value)
if not self._has_prev:
self._prev_ema = ev
self._prev_lwma = lv
self._has_prev = True
return
open_buy = lv > ev and lv > self._prev_lwma and ev > self._prev_ema
open_sell = lv < ev and lv < self._prev_lwma and ev < self._prev_ema
close_buy = lv < ev
close_sell = lv > ev
if self.Position > 0 and close_buy:
self.SellMarket()
elif self.Position < 0 and close_sell:
self.BuyMarket()
elif self.Position == 0:
if open_buy and not close_buy:
self.BuyMarket()
elif open_sell and not close_sell:
self.SellMarket()
self._prev_ema = ev
self._prev_lwma = lv
def CreateClone(self):
return universal_investor_strategy()