| 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 QuantConnect.Securities.Option import OptionPriceModels
from datetime import timedelta
class TestingIB(QCAlgorithm):
def Initialize(self):
# self.SetStartDate(2019, 3, 11) # Set Start Date
# self.SetCash(100000) # Set Strategy Cash
# self.AddEquity("SPY", Resolution.Minute)
self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage)
if self.LiveMode:
self.Debug("Trading Live!")
self.has_printed = False
self.option_holdings = [this for this in self.Portfolio.Values \
if this.Invested and this.Type == SecurityType.Option]
self.option_contract_securities = []
for option_holding in self.option_holdings:
option_contract_security = self.AddOptionContract(option_holding.Symbol)
option_contract_security.PriceModel = OptionPriceModels.CrankNicolsonFD()
self.option_contract_securities.append(option_contract_security)
self.SetWarmUp(TimeSpan.FromDays(4))
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm.
Each new data point will be pumped in here.
Arguments:
data: Slice object keyed by symbol containing the stock data
'''
if not self.has_printed:
for this_option_chain in data.OptionChains.Value:
this_option_holding in self.option_holdings[0]
this_option_contract = [oc for oc in this_option_chain if oc.Symbol == this_option_holding.Symbol][0]
this_delta = this_option_contract.Greeks.Delta
self.Debug("Sym: {}, Delta: {}".format(this_option_contract.Symbol, str(this_delta)))
self.has_printed = True
# these_option_holdings = [this for this in self.Portfolio.Values \
# if this.Invested and this.Type == SecurityType.Option]
# if not self.Portfolio.Invested:
# self.SetHoldings("SPY", 1)