This pair trading strategy measures the Spearman rank correlation between two securities. When the correlation exceeds a positive threshold the strategy goes short the first security and long the second. When it drops below the negative threshold it takes the opposite position. Positions are closed when the correlation returns toward zero.
Details
Entry Criteria:
Long First / Short Second: correlation < -Threshold.
Short First / Long Second: correlation > Threshold.
Long/Short: Pair trading.
Exit Criteria:
Correlation absolute value < Threshold / 2.
Stops: No.
Default Values:
CorrelationPeriod = 10
Threshold = 0.8
Filters:
Category: Correlation
Direction: Both
Indicators: Spearman Rank Correlation
Stops: No
Complexity: Intermediate
Timeframe: Medium-term
Seasonality: No
Neural networks: No
Divergence: No
Risk level: Medium
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>
/// Spearman rank correlation coefficient strategy using EMA crossover.
/// </summary>
public class SpearmanRankCorrelationCoefficientStrategy : 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 SpearmanRankCorrelationCoefficientStrategy()
{
_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 spearman_rank_correlation_coefficient_strategy(Strategy):
def __init__(self):
super(spearman_rank_correlation_coefficient_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(spearman_rank_correlation_coefficient_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(spearman_rank_correlation_coefficient_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 spearman_rank_correlation_coefficient_strategy()