| Overall Statistics |
|
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 43.916% Drawdown 0.700% Expectancy 0 Net Profit 0% Sharpe Ratio 4.669 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.503 Beta -1.132 Annual Standard Deviation 0.074 Annual Variance 0.006 Information Ratio 1.916 Tracking Error 0.109 Treynor Ratio -0.306 Total Fees $1.00 |
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 DailyConsolidatorEmitTimeAlgorithm : QCAlgorithm
{
const string Symbol = "SPY";
//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(2013, 01, 7);
//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);
var daily = new TradeBarConsolidator(TimeSpan.FromDays(1));
SubscriptionManager.AddConsolidator(Symbol, daily);
// print out the emit time
daily.DataConsolidated += (sender, args) =>
{
Log(">>Algo>>" + Time + ">>DataStart>>" + args.Time + ">>DataEnd>>" + args.EndTime);
};
}
//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)
{
if (!Portfolio.Invested) SetHoldings(Symbol, 1);
}
}
}