Overall Statistics
Total Orders
31
Average Win
2.55%
Average Loss
-2.21%
Compounding Annual Return
5.807%
Drawdown
7.300%
Expectancy
0.124
Net Profit
4.328%
Sharpe Ratio
0.177
Sortino Ratio
0.262
Probabilistic Sharpe Ratio
30.252%
Loss Rate
48%
Win Rate
52%
Profit-Loss Ratio
1.15
Alpha
0.014
Beta
0.017
Annual Standard Deviation
0.082
Annual Variance
0.007
Information Ratio
-0.127
Tracking Error
0.157
Treynor Ratio
0.848
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
XAGUSD 8I
Portfolio Turnover
15.47%
#region imports
    using System;
    using System.Collections;
    using System.Collections.Generic;
    using System.Linq;
    using System.Globalization;
    using System.Drawing;
    using QuantConnect;
    using System.Text.RegularExpressions;
    using QuantConnect.Algorithm.Framework;
    using QuantConnect.Algorithm.Framework.Selection;
    using QuantConnect.Algorithm.Framework.Alphas;
    using QuantConnect.Algorithm.Framework.Portfolio;
    using QuantConnect.Algorithm.Framework.Execution;
    using QuantConnect.Algorithm.Framework.Risk;
    using QuantConnect.Algorithm.Selection;
    using QuantConnect.Parameters;
    using QuantConnect.Benchmarks;
    using QuantConnect.Brokerages;
    using QuantConnect.Util;
    using QuantConnect.Interfaces;
    using QuantConnect.Algorithm;
    using QuantConnect.Indicators;
    using QuantConnect.Data;
    using QuantConnect.Data.Consolidators;
    using QuantConnect.Data.Custom;
    using QuantConnect.DataSource;
    using QuantConnect.Data.Fundamental;
    using QuantConnect.Data.Market;
    using QuantConnect.Data.UniverseSelection;
    using QuantConnect.Notifications;
    using QuantConnect.Orders;
    using QuantConnect.Orders.Fees;
    using QuantConnect.Orders.Fills;
    using QuantConnect.Orders.Slippage;
    using QuantConnect.Scheduling;
    using QuantConnect.Securities;
    using QuantConnect.Securities.Equity;
    using QuantConnect.Securities.Future;
    using QuantConnect.Securities.Option;
    using QuantConnect.Securities.Forex;
    using QuantConnect.Securities.Crypto;   
    using QuantConnect.Securities.Interfaces;
    using QuantConnect.Storage;
    using QCAlgorithmFramework = QuantConnect.Algorithm.QCAlgorithm;
    using QCAlgorithmFrameworkBridge = QuantConnect.Algorithm.QCAlgorithm;
#endregion

namespace QuantConnect
{
    public class GoldSilverPairsTradingAlgorithm : QCAlgorithm
    {
        private SimpleMovingAverage _spreadMean = new SimpleMovingAverage(500);
        private StandardDeviation _spreadStd = new StandardDeviation(500);
        private Security[] _pair = new Security[2];

        public override void Initialize()
        {
            SetStartDate(2018, 7, 1);  
            SetEndDate(2019, 3, 31);  
            SetCash(100000);  

            AddCfd("XAUUSD", Resolution.Hour);
            AddCfd("XAGUSD", Resolution.Hour);
        }

        public override void OnData(Slice slice) 
        {
            var spread = _pair[1].Price - _pair[0].Price;
            _spreadMean.Update(Time, spread);
            _spreadStd.Update(Time, spread);
            
            var upperthreshold = _spreadMean + _spreadStd;
            var lowerthreshold = _spreadMean - _spreadStd;
            
            if (spread > upperthreshold)
            {
                SetHoldings(_pair[0].Symbol, 1);
                SetHoldings(_pair[1].Symbol, -1);
            }
            
            if (spread < lowerthreshold)
            {
                SetHoldings(_pair[0].Symbol, -1);
                SetHoldings(_pair[1].Symbol, 1);
            }
        }
        
        public override void OnSecuritiesChanged(SecurityChanges changes)
        {    
            _pair = changes.AddedSecurities.ToArray();
            
            //1. Call for 500 days of history data for each symbol in the pair and save to the variable history
            var history = History(_pair.Select(x => x.Symbol), 500);
            
            //2. Iterate through the history tuple and update the mean and standard deviation with historical data 
            foreach(var slice in history)
            {
                var spread = slice[_pair[1].Symbol].Close - slice[_pair[0].Symbol].Close;
                _spreadMean.Update(slice.Time, spread);
                _spreadStd.Update(slice.Time, spread);
            }
        }
    }
}