Overall Statistics |
Total Trades 158 Average Win 4.88% Average Loss -2.22% Compounding Annual Return 2.775% Drawdown 35.700% Expectancy 0.334 Net Profit 63.732% Sharpe Ratio 0.298 Loss Rate 58% Win Rate 42% Profit-Loss Ratio 2.19 Alpha 0.035 Beta -0.017 Annual Standard Deviation 0.113 Annual Variance 0.013 Information Ratio -0.194 Tracking Error 0.23 Treynor Ratio -1.932 Total Fees $834.20 |
using System; using System.Linq; using QuantConnect.Indicators; using QuantConnect.Models; namespace QuantConnect.Algorithm.Examples { /// <summary> /// /// QuantConnect University: SMA + SMA Cross /// /// In this example we look at the canonical 15/30 day moving average cross. This algorithm /// will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses /// back below the 30. /// </summary> public class QCUMovingAverageCross : QCAlgorithm { private const string Symbol = "SPY"; private SimpleMovingAverage fast; private SimpleMovingAverage slow; public override void Initialize() { // set up our analysis span SetStartDate(1998, 01, 01); SetEndDate(2016, 01, 01); // request SPY data with minute resolution AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute); // create a 15 day exponential moving average fast = SMA(Symbol, 5, Resolution.Daily); // create a 30 day exponential moving average slow = SMA(Symbol, 50, Resolution.Daily); } private DateTime previous; public void OnData(TradeBars data) { // a couple things to notice in this method: // 1. We never need to 'update' our indicators with the data, the engine takes care of this for us // 2. We can use indicators directly in math expressions // 3. We can easily plot many indicators at the same time // wait for our slow ema to fully initialize if (!slow.IsReady) return; // only once per day if (previous.Date == data.Time.Date) return; // define a small tolerance on our checks to avoid bouncing const decimal tolerance = 0.00015m; var holdings = Portfolio[Symbol].Quantity; // we only want to go long if we're currently short or flat if (holdings <= 0) { // if the fast is greater than the slow, we'll go long if (fast > slow * (1 + tolerance)) { Log("BUY >> " + Securities[Symbol].Price); SetHoldings(Symbol, 1.0); } } // we only want to liquidate if we're currently long // if the fast is less than the slow we'll liquidate our long if (holdings > 0 && fast < slow) { Log("SELL >> " + Securities[Symbol].Price); Order(Symbol, -holdings); // Liquidate(Symbol); } Plot(Symbol, "SPY ", data[Symbol].Price); // Plot("Ribbon", "Price", data[Symbol].Price); // easily plot indicators, the series name will be the name of the indicator Plot(Symbol, fast, slow); // Plot("Ribbon", ribbon); previous = data.Time; } } }