Overall Statistics |
Total Trades 170 Average Win 2.70% Average Loss -0.84% Compounding Annual Return 16.407% Drawdown 7.400% Expectancy 0.409 Net Profit 35.499% Sharpe Ratio 1.305 Loss Rate 67% Win Rate 33% Profit-Loss Ratio 3.23 Alpha 0.135 Beta 0.114 Annual Standard Deviation 0.122 Annual Variance 0.015 Information Ratio -0.32 Tracking Error 0.156 Treynor Ratio 1.397 Total Fees $222.73 |
namespace QuantConnect { /* * 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 RollingWindowAlgorithm : QCAlgorithm { public const string Symbol = "SPY"; public ExponentialMovingAverage Fast; public ExponentialMovingAverage Slow; public MovingAverageConvergenceDivergence DailyMacd; public Momentum DailyMomentum; //Initialize the data and resolution you require for your strategy: public override void Initialize() { //Start and End Date range for the backtest: SetStartDate(2013, 1, 1); SetEndDate(2015, 1, 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, Symbol, Resolution.Minute); // define our 15 minute consolidator, this makes 15min bars from 1min bars var fifteenMinute = new TradeBarConsolidator(TimeSpan.FromMinutes(15)); // register the consolidator to receive data for our 'Symbol' SubscriptionManager.AddConsolidator(Symbol, fifteenMinute); // attach our 15 minute event handler, the 'OnFifteenMinuteData' will be called // at 9:45, 10:00, 10:15, ect... until 4:00pm fifteenMinute.DataConsolidated += OnFifteenMinuteData; // define our 15 minute fast EMA Fast = new ExponentialMovingAverage(12); // define our 15 minute slow EMA Slow = new ExponentialMovingAverage(36); // we can also define some daily indicators DailyMomentum = MOM(Symbol, 10); DailyMacd = MACD(Symbol, 12, 26, 9, MovingAverageType.Wilders, Resolution.Daily); } const decimal tolerance = 0.001m; public void OnFifteenMinuteData(object sender, TradeBar bar) { // update our indicators Fast.Update(Time, bar.Close); Slow.Update(Time, bar.Close); var quantity = Portfolio[Symbol].Quantity; // short or flat and longer term up if (quantity <= 0 && DailyMacd.Signal > DailyMacd && DailyMomentum > 0) { // check for short term up if (Fast > Slow*(1+tolerance)) { // move everything into a long position SetHoldings(Symbol, 1.5); } } // long or flat and longer term down else if (quantity >= 0 && DailyMacd.Signal < DailyMacd && DailyMomentum < 0) { // check for short term down if (Fast < Slow*(1-tolerance)) { // move everything into a short position SetHoldings(Symbol, -1.5); } } // check for exit conditions else if (quantity != 0) { // check for long exit if (quantity > 0 && Fast < Slow*(1-tolerance)) { Liquidate(Symbol); } // check for short exit else if (quantity < 0 && Fast > Slow*(1+tolerance)) { Liquidate(Symbol); } } } //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) { } } }