Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio NaN Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio NaN Tracking Error NaN Treynor Ratio NaN Total Fees $0.00 |
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 { private string symbol = "IBB"; private IndicatorBase<IndicatorDataPoint> _volatility; //Initialize the data and resolution you require for your strategy: public override void Initialize() { //Start and End Date range for the backtest: SetStartDate(2010, 3, 31); 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, symbol, Resolution.Daily); var logr = new LogReturn(1); RegisterIndicator(symbol, logr, ResolveConsolidator(symbol, Resolution.Daily)); // normalize logr to a display percent 0->100 _volatility = new StandardDeviation("4Month Vol LOGR", 84).Of(logr.Times(100m)); // normalize it to a numeric percent var rocp = ROCP(symbol, 1); var rocpvol = new StandardDeviation("4Month Vol ROCP", 84).Of(rocp); PlotIndicator("volatility", _volatility, rocpvol); PlotIndicator("returns", rocp, logr); } //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) { } } public class LogReturn : WindowIndicator<IndicatorDataPoint> { public LogReturn(string name, int period) : base(name, period) { } public LogReturn(int period) : base("LOGR" + period, period) { } protected override decimal ComputeNextValue(IReadOnlyWindow<IndicatorDataPoint> window, IndicatorDataPoint input) { decimal valuef = input; decimal value0 = !window.IsReady ? window[window.Count - 1] : window.MostRecentlyRemoved; return (decimal) Math.Log((double) (valuef/value0)); } } }