Overall Statistics |
Total Trades 3 Average Win 0% Average Loss 0% Compounding Annual Return 6.860% Drawdown 4.400% Expectancy 0 Net Profit 0% Sharpe Ratio 1.004 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.01 Beta 0.432 Annual Standard Deviation 0.068 Annual Variance 0.005 Information Ratio -1.424 Tracking Error 0.08 Treynor Ratio 0.159 Total Fees $3.00 |
namespace QuantConnect { /* * QuantConnect University: How can I model a basket of securities * * Combining securities into a single symbol. */ public class BasketAlgorithm : QCAlgorithm { TradeBar _basket = new TradeBar(); public static List<string> _symbols = new List<string>() { "SPY", "AAPL", "IBM" }; public override void Initialize() { SetStartDate(2013, 1, 1); SetEndDate(DateTime.Now.Date.AddDays(-1)); SetCash(25000); foreach (var symbol in _symbols) { AddSecurity(SecurityType.Equity, symbol, Resolution.Minute); } } //Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol. public override void OnData(Slice data) { if (data.Bars.Count != _symbols.Count) return; //Build the basket value: _basket.Open = (from bar in data.Bars.Values select bar.Open).Sum(); _basket.High = (from bar in data.Bars.Values select bar.High).Sum(); _basket.Low = (from bar in data.Bars.Values select bar.High).Sum(); _basket.Close = (from bar in data.Bars.Values select bar.Close).Sum(); //Basket value here: if (!Portfolio.HoldStock) { BasketBuy(0.5m); } } public void BasketBuy(decimal fraction) { var symbolFraction = fraction / _symbols.Count; foreach(var symbol in _symbols) { SetHoldings(symbol, symbolFraction); } } } }