Overall Statistics |
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 742.260% Drawdown 5.900% Expectancy 0 Net Profit 9.152% Sharpe Ratio 4.477 Probabilistic Sharpe Ratio 85.859% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 1.672 Beta -0.094 Annual Standard Deviation 0.367 Annual Variance 0.135 Information Ratio 3.464 Tracking Error 0.381 Treynor Ratio -17.518 Total Fees $18.20 |
namespace QuantConnect.Algorithm.CSharp { public class ProblemWithVXXDataDemo : QCAlgorithm { public override void Initialize() { SetStartDate(2018, 1, 17); //Set Start Date SetEndDate(2018, 1, 31); //Set Start Date //SetStartDate(2013, 10, 11); //Set Start Date SetCash(100000); //Set Strategy Cash // Universe Selection. In this case we just buy the market, VXX. UniverseSettings.Resolution = Resolution.Minute; var symbols = new [] { QuantConnect.Symbol.Create("VXX", SecurityType.Equity, Market.USA) }; AddUniverseSelection( new ManualUniverseSelectionModel(symbols) ); // Alpha Creation. We want to be long the entire time. AddAlpha( new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(5*365) )); // Portfolio Construction. Equal Weight will just assign 100% to our single symbol. SetBrokerageModel(new DefaultBrokerageModel(AccountType.Margin)); SetPortfolioConstruction( new EqualWeightingPortfolioConstructionModel()); // Risk Management. No risk management. AddRiskManagement( new NullRiskManagementModel() ); // Execution. Execute with market order. SetExecution( new ImmediateExecutionModel() ); } /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. /// Slice object keyed by symbol containing the stock data public override void OnData(Slice data) { // if (!Portfolio.Invested) // { // SetHoldings(_spy, 1); // Debug("Purchased Stock"); //} } } }