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 |
from System import * from QuantConnect import * from QuantConnect.Algorithm import * from QuantConnect.Python import PythonQuandl from datetime import datetime, timedelta class QuandlFuturesDataAlgorithm(QCAlgorithm): def Initialize(self): ''' Initialize the data and resolution you require for your strategy ''' self.SetStartDate(2018, 1, 1) self.SetEndDate(datetime.now().date() - timedelta(1)) self.SetCash(25000); # Symbol corresponding to the quandl code self.AddData(QuandlVix, "CBOE/VIX", Resolution.Daily) # self.AddData[Quandl]("CBOE/VXV", Resolution.Daily) def OnData(self, data): '''Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.''' if not data.ContainsKey("CBOE/VIX"): return self.Plot("VIX", "Price", data["CBOE/VIX"].Price) self.Debug("vix close: %s" % (data["CBOE/VIX"].Price)) # self.Plot("VXV", "Close", data["CBOE/VXV"].Price) class QuandlVix(PythonQuandl): def __init__(self): self.ValueColumnName = "vix close"