| 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 NaN Beta NaN Annual Standard Deviation NaN Annual Variance NaN Information Ratio NaN Tracking Error NaN Treynor Ratio NaN Total Fees $0.00 |
using System;
using QuantConnect.Algorithm;
using QuantConnect.Data.Market;
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 Series scatter;
//Initialize the data and resolution you require for your strategy:
public override void Initialize()
{
//Start and End Date range for the backtest:
SetStartDate(2015, 01, 07);
SetEndDate(2015, 01, 07);
//Cash allocation
SetCash(25000);
//Add as many securities as you like. All the data will be passed into the event handler:
AddSecurity(SecurityType.Equity, "SPY", Resolution.Minute);
var chart = new Chart("data");
scatter = new Series("scatter", SeriesType.Scatter);
chart.AddSeries(scatter);
AddChart(chart);
}
//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)
{
var x = Time.Millisecond + Time.Ticks;
scatter.AddPoint(new DateTime(x), (decimal) (Time.Hour*Math.Cos(x)));
}
}
}