Стратегия Polarized Fractal Efficiency
Стратегия торгует по индикатору Polarized Fractal Efficiency (PFE), который оценивает эффективность движения цены и меняет знак при смене импульса.
Логика торговли
- Подписка на свечи выбранного таймфрейма и расчёт PFE.
- Если значение PFE на предыдущем баре ниже, чем двумя барами раньше, и текущее значение выше предыдущего — открывается длинная позиция.
- Если значение PFE на предыдущем баре выше, чем двумя барами раньше, и текущее значение ниже предыдущего — открывается короткая позиция.
- Перед открытием новой позиции закрываются противоположные позиции.
- При необходимости включается защита стоп-лоссом и тейк-профитом.
Параметры
| Имя | Описание |
|---|---|
CandleType |
Тип свечей для анализа. |
PfePeriod |
Период расчёта индикатора PFE. |
SignalBar |
Смещение бара, используемого для сигнала. |
TakeProfit |
Тейк-профит в шагах цены. |
StopLoss |
Стоп-лосс в шагах цены. |
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>
/// Polarized Fractal Efficiency strategy.
/// Computes PFE manually from close prices.
/// Buys on PFE turning up from negative, sells on PFE turning down from positive.
/// </summary>
public class PolarizedFractalEfficiencyStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _pfePeriod;
private readonly List<decimal> _closes = new();
private decimal _prevPfe;
private decimal _prevPrevPfe;
private int _formed;
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public int PfePeriod { get => _pfePeriod.Value; set => _pfePeriod.Value = value; }
public PolarizedFractalEfficiencyStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles", "General");
_pfePeriod = Param(nameof(PfePeriod), 9)
.SetDisplay("PFE Period", "Indicator calculation period", "Indicators")
.SetGreaterThanZero();
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
protected override void OnReseted()
{
base.OnReseted();
_closes.Clear();
_prevPfe = 0;
_prevPrevPfe = 0;
_formed = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_closes.Clear();
_prevPfe = 0;
_prevPrevPfe = 0;
_formed = 0;
var sma = new SimpleMovingAverage { Length = 1 };
var subscription = SubscribeCandles(CandleType);
subscription.Bind(sma, ProcessCandle).Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal _smaVal)
{
if (candle.State != CandleStates.Finished)
return;
_closes.Add(candle.ClosePrice);
var period = PfePeriod;
if (_closes.Count < period + 1)
return;
// Keep only what we need
while (_closes.Count > period + 2)
_closes.RemoveAt(0);
var n = _closes.Count;
var closeNow = _closes[n - 1];
var closePast = _closes[n - 1 - period];
// Direct distance
var diff = (double)(closeNow - closePast);
var directDist = Math.Sqrt(diff * diff + (double)(period * period));
// Sum of bar-to-bar distances
var sumDist = 0.0;
for (var i = n - period; i < n; i++)
{
var d = (double)(_closes[i] - _closes[i - 1]);
sumDist += Math.Sqrt(d * d + 1.0);
}
if (sumDist == 0)
return;
var sign = closeNow >= closePast ? 1.0 : -1.0;
var pfe = (decimal)(100.0 * sign * directDist / sumDist);
_formed++;
if (_formed < 3)
{
_prevPrevPfe = _prevPfe;
_prevPfe = pfe;
return;
}
if (!IsFormedAndOnline())
return;
// Trend reversal: PFE was falling and now rising => buy
if (_prevPfe < _prevPrevPfe && pfe > _prevPfe && Position <= 0)
BuyMarket();
// PFE was rising and now falling => sell
else if (_prevPfe > _prevPrevPfe && pfe < _prevPfe && Position >= 0)
SellMarket();
_prevPrevPfe = _prevPfe;
_prevPfe = pfe;
}
}
import clr
import math
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 SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class polarized_fractal_efficiency_strategy(Strategy):
def __init__(self):
super(polarized_fractal_efficiency_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles", "General")
self._pfe_period = self.Param("PfePeriod", 9) \
.SetDisplay("PFE Period", "Indicator calculation period", "Indicators")
self._closes = []
self._prev_pfe = 0.0
self._prev_prev_pfe = 0.0
self._formed = 0
@property
def candle_type(self):
return self._candle_type.Value
@property
def pfe_period(self):
return self._pfe_period.Value
def OnReseted(self):
super(polarized_fractal_efficiency_strategy, self).OnReseted()
self._closes = []
self._prev_pfe = 0.0
self._prev_prev_pfe = 0.0
self._formed = 0
def OnStarted2(self, time):
super(polarized_fractal_efficiency_strategy, self).OnStarted2(time)
self._closes = []
self._prev_pfe = 0.0
self._prev_prev_pfe = 0.0
self._formed = 0
sma = SimpleMovingAverage()
sma.Length = 1
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(sma, self.process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
def process_candle(self, candle, _sma_val):
if candle.State != CandleStates.Finished:
return
self._closes.append(float(candle.ClosePrice))
period = int(self.pfe_period)
if len(self._closes) < period + 1:
return
while len(self._closes) > period + 2:
self._closes.pop(0)
n = len(self._closes)
close_now = self._closes[n - 1]
close_past = self._closes[n - 1 - period]
diff = close_now - close_past
direct_dist = math.sqrt(diff * diff + period * period)
sum_dist = 0.0
for i in range(n - period, n):
d = self._closes[i] - self._closes[i - 1]
sum_dist += math.sqrt(d * d + 1.0)
if sum_dist == 0:
return
sign = 1.0 if close_now >= close_past else -1.0
pfe = 100.0 * sign * direct_dist / sum_dist
self._formed += 1
if self._formed < 3:
self._prev_prev_pfe = self._prev_pfe
self._prev_pfe = pfe
return
if self._prev_pfe < self._prev_prev_pfe and pfe > self._prev_pfe and self.Position <= 0:
self.BuyMarket()
elif self._prev_pfe > self._prev_prev_pfe and pfe < self._prev_pfe and self.Position >= 0:
self.SellMarket()
self._prev_prev_pfe = self._prev_pfe
self._prev_pfe = pfe
def CreateClone(self):
return polarized_fractal_efficiency_strategy()