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); } } } }