| 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"