Overall Statistics |
Total Orders 29 Average Win 0.08% Average Loss -0.03% Compounding Annual Return -25.300% Drawdown 0.700% Expectancy 1.712 Net Profit -0.478% Sharpe Ratio -14.45 Sortino Ratio -19.176 Probabilistic Sharpe Ratio 0.000% Loss Rate 25% Win Rate 75% Profit-Loss Ratio 2.62 Alpha -0.251 Beta -0.036 Annual Standard Deviation 0.016 Annual Variance 0 Information Ratio 1.238 Tracking Error 0.123 Treynor Ratio 6.612 Total Fees $51.62 Estimated Strategy Capacity $12000000.00 Lowest Capacity Asset UNPH R735QTJ8XC9X Portfolio Turnover 20.01% |
#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 using QuantConnect.DataSource; namespace QuantConnect { public class KavoutCompositeFactorBundleAlgorithm : QCAlgorithm { private DateTime _time = DateTime.MinValue; public override void Initialize() { SetStartDate(2003, 1, 10); SetEndDate(2003, 1, 15); SetCash(100000); AddUniverse(MyCoarseFilterFunction); UniverseSettings.Resolution = Resolution.Minute; } private IEnumerable<Symbol> MyCoarseFilterFunction(IEnumerable<CoarseFundamental> coarse) { return (from c in coarse where c.HasFundamentalData orderby c.DollarVolume descending select c.Symbol).Take(100); } public override void OnData(Slice slice) { if (_time > Time) return; // Accessing Data var points = slice.Get<KavoutCompositeFactorBundle>(); var sortedByScore = from s in points.Values orderby TotalScore(s) descending select s.Symbol.Underlying; var longSymbols = sortedByScore.Take(10).ToList(); var shortSymbols = sortedByScore.TakeLast(10).ToList(); foreach (var kvp in Portfolio) { var symbol = kvp.Key; if (kvp.Value.Invested && !longSymbols.Contains(symbol) && !shortSymbols.Contains(symbol)) { Liquidate(symbol); } } var targets = new List<PortfolioTarget>(); targets.AddRange(longSymbols.Select(symbol => new PortfolioTarget(symbol, 0.05m))); targets.AddRange(shortSymbols.Select(symbol => new PortfolioTarget(symbol, -0.05m))); SetHoldings(targets); _time = Expiry.EndOfDay(Time); } public override void OnSecuritiesChanged(SecurityChanges changes) { foreach(var security in changes.AddedSecurities) { // Requesting Data var kavoutCompositeFactorBundleSymbol = AddData<KavoutCompositeFactorBundle>(security.Symbol).Symbol; // Historical Data var history = History(new[]{kavoutCompositeFactorBundleSymbol}, 60, Resolution.Daily); Debug($"We got {history.Count()} items from our history request"); } } private decimal TotalScore(KavoutCompositeFactorBundle value) { /// Return the total score to integrate overall likelihood to outcompete, take equal weighting for each factor return value.Growth + value.ValueFactor + value.Quality + value.Momentum + value.LowVolatility; } } }