Overall Statistics |
Total Trades 261 Average Win 3.22% Average Loss -0.79% Compounding Annual Return 9.568% Drawdown 25.200% Expectancy 0.111 Net Profit 26.084% Sharpe Ratio 0.501 Loss Rate 78% Win Rate 22% Profit-Loss Ratio 4.07 Alpha 0.175 Beta -0.309 Annual Standard Deviation 0.239 Annual Variance 0.057 Information Ratio -0.215 Tracking Error 0.279 Treynor Ratio -0.387 Total Fees $1006.84 |
using System; using System.Linq; using QuantConnect.Indicators; using QuantConnect.Models; namespace QuantConnect.Algorithm.Examples { /// <summary> /// /// QuantConnect University: EMA + SMA Cross /// /// In this example we look at the canonical 20/50 day moving average cross. This algorithm /// will go long when the 20 crosses above the 50 and will liquidate when the 20 crosses /// back below the 50. // -------VATS CHANGES ----------- // 1) Intraday - Hourly // 2) 1/50 period SMA cross // // -------VATS CHANGES ----------- /// </summary> public class QCUMovingAverageCross : QCAlgorithm { private const string Symbol = "USO"; private SimpleMovingAverage fast; private SimpleMovingAverage slow; //Initialize the data and resolution you require for your strategy: public override void Initialize() { SetStartDate(2013, 01, 01); SetEndDate(2015, 07, 15); SetCash(10000); // request SPY data with minute resolution AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute); // create a 15 day exponential moving average fast = SMA(Symbol, 1, Resolution.Hour); // create a 30 day exponential moving average slow = SMA(Symbol, 50, Resolution.Hour); //SetRunMode(RunMode.Series); } 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 // Commented the following line to simulate intraday - Vats //if (previous.Date == data.Time.Date) return; // define a small tolerance on our checks to avoid bouncing const decimal tolerance = 0.00010m; var holdings = Portfolio[Symbol].Quantity; // we only want to go long if we're currently short or flat // if the fast is greater than the slow, we'll go long if (fast > slow * (1 + tolerance)) { if (holdings <= 0) { Log("L >> " + holdings + "@ price " + Securities[Symbol].Price); SetHoldings(Symbol, 0.95); Log("NET POSITION BEFORE NEXT TRANSACTION >> " + holdings); } } // we only want to liquidate if we're currently long // if the fast is less than the slow we'll liquidate our long if (fast < slow) { if (holdings > 0) { Log("SELL >> " + holdings + "@ price " + Securities[Symbol].Price); SetHoldings(Symbol, -0.95); } } Plot(Symbol, "Price", data[Symbol].Price); // easily plot indicators, the series name will be the name of the indicator Plot(Symbol, fast, slow); previous = data.Time; } } }