| Overall Statistics |
|
Total Trades 1 Average Win 40.61% Average Loss 0% Compounding Annual Return 18.551% Drawdown 7.700% Expectancy 0 Net Profit 40.609% Sharpe Ratio 1.593 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha -0.027 Beta 0.974 Annual Standard Deviation 0.11 Annual Variance 0.012 Information Ratio -1.595 Tracking Error 0.021 Treynor Ratio 0.181 |
using System;
using System.Collections;
using System.Collections.Generic;
using QuantConnect.Securities;
using QuantConnect.Models;
namespace QuantConnect
{
/*
* QuantConnect University: Generic Quandl Data Importer
*
* Using the underlying dynamic data class "Quandl" we take care of the data
* importing and definition for you. Simply point QuantConnect to the Quandl Short Code.
*
* The Quandl object has properties which match the spreadsheet headers.
* If you have multiple quandl streams look at data.Symbol to distinguish them.
*/
public class QCUQuandlImporter : QCAlgorithm
{
string _quandlCode = "YAHOO/INDEX_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(DateTime.Now.Date.AddDays(-1));
//Cash allocation
SetCash(25000);
//Add Generic Quandl Data:
AddData<Quandl>(_quandlCode, 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(Quandl data)
{
if (!Portfolio.HoldStock)
{
//Order function places trades: enter the string symbol and the quantity you want:
SetHoldings(_quandlCode, 100);
//Debug sends messages to the user console: "Time" is the algorithm time keeper object
Debug("Purchased " + _quandlCode + " >> " + Time.ToShortDateString());
}
}
}
}