Overall Statistics |
Total Orders 69 Average Win 14.22% Average Loss -10.58% Compounding Annual Return 45.182% Drawdown 66.300% Expectancy 0.233 Net Profit 69.732% Sharpe Ratio 1.297 Sortino Ratio 2.237 Probabilistic Sharpe Ratio 33.905% Loss Rate 47% Win Rate 53% Profit-Loss Ratio 1.34 Alpha 1.572 Beta 1.2 Annual Standard Deviation 1.378 Annual Variance 1.898 Information Ratio 1.193 Tracking Error 1.348 Treynor Ratio 1.489 Total Fees $20732.10 Estimated Strategy Capacity $23000.00 Lowest Capacity Asset ABP RXBFGHC4AV6T Portfolio Turnover 19.40% |
#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 USEnergyDataAlgorithm : QCAlgorithm { private decimal? previousValue; private Symbol tradableSymbol; public override void Initialize() { SetStartDate(2020, 1, 1); SetEndDate(2021, 6, 1); SetCash(100000); // Requesting data tradableSymbol = AddEquity("AXAS", Resolution.Daily).Symbol; var USEnergySymbol = AddData<USEnergy>(USEnergy.Petroleum.UnitedStates.WeeklyNetImportsOfTotalPetroleumProducts).Symbol; // Historical data var history = History<USEnergy>(USEnergySymbol, 60, Resolution.Daily); Debug($"We got {history.Count()} items from our history request"); // Get latest value for net imports of petroleum products previousValue = history.Last().Value; } public override void OnData(Slice slice) { // Gather the current net imports of petroleum products var points = slice.Get<USEnergy>(); decimal? currentValue = null; foreach (var point in points.Values) { currentValue = point.Value; } if (currentValue == null) { return; } // Buy when net imports of petroleum products are increasing if (currentValue > previousValue) { SetHoldings(tradableSymbol, 1); } // Short sell when net imports of petroleum products are decreasing if (currentValue < previousValue) { SetHoldings(tradableSymbol, -1); } previousValue = currentValue; } } }