Overall Statistics |
Total Trades 1 Average Win 46.57% Average Loss 0% Compounding Annual Return 20.089% Drawdown 9.300% Expectancy 0 Net Profit 46.567% Sharpe Ratio 1.663 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 0.004 Beta 0.985 Annual Standard Deviation 0.114 Annual Variance 0.013 Information Ratio 0.038 Tracking Error 0.021 Treynor Ratio 0.192 |
namespace QuantConnect { /* * QuantConnect University: Full Basic Template: * * The underlying QCAlgorithm class is full of helper methods which enable you to use QuantConnect. * We have explained some of these here, but the full algorithm can be found at: * https://github.com/QuantConnect/QCAlgorithm/blob/master/QuantConnect.Algorithm/QCAlgorithm.cs */ public class BasicTemplateAlgorithm : QCAlgorithm { //Initialize the data and resolution you require for your strategy: LogReturn returnIndicator; SequentialIndicator<IndicatorDataPoint> sma; SimpleMovingAverage _sma; public override void Initialize() { //Start and End Date range for the backtest: SetStartDate(2013, 1, 1); SetStartDate(2013, 1, 10); //SetEndDate(DateTime.Now.Date.AddDays(-1)); //Cash allocation SetCash(25000); //Add as many securities as you like. All the data will be passed into the event handler: AddSecurity(SecurityType.Equity, "SPY", Resolution.Minute); //Set up Indicators: returnIndicator = new LogReturn("SPY"); RegisterIndicator("SPY", returnIndicator, Resolution.Minute, x => x.Value); _sma = new SimpleMovingAverage(5); sma = _sma.Of(returnIndicator); RegisterIndicator("SPY", sma, Resolution.Minute, x => x.Value); } //Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol. public void OnData(TradeBars data) { // "TradeBars" object holds many "TradeBar" objects: it is a dictionary indexed by the symbol: // // e.g. data["MSFT"] data["GOOG"] if (!Portfolio.HoldStock) { int quantity = (int)Math.Floor(Portfolio.Cash / data["SPY"].Close); //Order function places trades: enter the string symbol and the quantity you want: Order("SPY", quantity); //Debug sends messages to the user console: "Time" is the algorithm time keeper object Debug("Purchased SPY on " + Time.ToShortDateString()); } } public override void OnEndOfDay() { Plot("Return","Instantaneous",returnIndicator); Plot("Return","5 Period Average",sma); } } }
using System; using QuantConnect.Data.Market; namespace QuantConnect.Indicators { /// <summary> /// This indicator is meant to compute log returns. /// </summary> public class LogReturn : Indicator { public LogReturn() : this(string.Format("Return")) { } public int _count; decimal _last; public decimal Return; public LogReturn(String name) : base(name) { _count = 0; _last = 0m; Return = 0m; } /// <summary> /// Gets a flag indicating when this indicator is ready and fully initialized /// </summary> public override bool IsReady { get { return _count > 0; } } public decimal total; protected override decimal ComputeNextValue(IndicatorDataPoint input) { if (IsReady) Return = (decimal)Math.Log((double)(input / _last)); _last = input; return Return; } /// <summary> /// Resets this indicator to its initial state /// </summary> public override void Reset() { _count = 0; _last = 0m; Return = 0m; base.Reset(); } } }