| Overall Statistics |
|
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 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
{
//ALSO NOT WORKING WITH THIS
//private Symbol _cashAsset = QuantConnect.Symbol.Create("IAG", SecurityType.Equity, Market.USA);
//Initialize the data and resolution you require for your strategy:
public override void Initialize()
{
//Start and End Date range for the backtest:
SetStartDate(2016, 1, 1);
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, "IAG", Resolution.Minute);
}
//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)
{
// "TradeBars" object holds many "TradeBar" objects: it is a dictionary indexed by the symbol:
//
// e.g. data["MSFT"] data["GOOG"]
if (!Portfolio.HoldStock)
{
int quantity = (int)Math.Floor(Portfolio.Cash / data["IAG"].Close);
//Order function places trades: enter the string symbol and the quantity you want:
Order("IAG", quantity);
//Debug sends messages to the user console: "Time" is the algorithm time keeper object
Debug("Purchased IAG on " + Time.ToShortDateString());
//You can also use log to send longer messages to a file. You are capped to 10kb
//Log("This is a longer message send to log.");
}
}
}
}