| Overall Statistics |
|
Total Trades 20 Average Win 17.71% Average Loss -5.05% Compounding Annual Return 9.426% Drawdown 43.600% Expectancy 2.157 Net Profit 163.253% Sharpe Ratio 0.546 Loss Rate 30% Win Rate 70% Profit-Loss Ratio 3.51 Alpha 0.088 Beta -0.041 Annual Standard Deviation 0.158 Annual Variance 0.025 Information Ratio 0.12 Tracking Error 0.245 Treynor Ratio -2.115 Total Fees $165.80 |
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 SellinMay : QCAlgorithm
{
//string symbol = "RTH";
string symbol = "XRT";
int quantity = 0;
public override void Initialize()
{
SetStartDate(2006, 1, 1);
SetEndDate(DateTime.Now.Date.AddDays(-1));
SetCash(25000);
AddSecurity(SecurityType.Equity, symbol, Resolution.Minute, true, 4, false);
}
//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(Time.ToString("MMM") == "May"){
if (Portfolio.HoldStock)
{
Order(symbol, -Portfolio[symbol].Quantity);
Debug("Sell in May: Flat " + Time.ToShortDateString() + " Quantity: -" + Portfolio[symbol].Quantity);
}
} else if (Time.ToString("MMM") == "Nov"){
if (!Portfolio.HoldStock)
{
quantity = (int)(Portfolio.Cash / data[symbol].Close);
Order(symbol, quantity);
Debug("Sell in May: Long " + Time.ToShortDateString() + " Quantity: -" + quantity);
}
}
}
}
}