| Overall Statistics |
|
Total Trades 4 Average Win 0.30% Average Loss -0.33% Compounding Annual Return -72.392% Drawdown 0.400% Expectancy -0.358 Net Profit -0.352% Sharpe Ratio -11.225 Loss Rate 67% Win Rate 33% Profit-Loss Ratio 0.93 Alpha -0.887 Beta -1.405 Annual Standard Deviation 0.04 Annual Variance 0.002 Information Ratio -1.889 Tracking Error 0.068 Treynor Ratio 0.316 Total Fees $2.00 |
class OptionExerciseAssignRegressionAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetCash(100000)
self.SetStartDate(2015,12,24)
self.SetEndDate(2015,12,24)
option = self.AddOption("GOOG")
# set our strike/expiry filter for this option chain
option.SetFilter(self.UniverseFunc)
self.SetBenchmark("GOOG")
self._assignedOption = False
def OnData(self, slice):
if self.Portfolio.Invested: return
for kvp in slice.OptionChains:
chain = kvp.Value
# find the call options expiring today
contracts = filter(lambda x:
x.Expiry.date() == self.Time.date() and
x.Strike < chain.Underlying.Price and
x.Right == OptionRight.Call, chain)
# sorted the contracts by their strikes, find the second strike under market price
sorted_contracts = sorted(contracts, key = lambda x: x.Strike, reverse = True)[:2]
if sorted_contracts:
self.MarketOrder(sorted_contracts[0].Symbol, 1)
self.MarketOrder(sorted_contracts[1].Symbol, -1)
# set our strike/expiry filter for this option chain
def UniverseFunc(self, universe):
return universe.IncludeWeeklys().Strikes(-2, 2).Expiration(timedelta(0), timedelta(10))
def OnOrderEvent(self, orderEvent):
if orderEvent.IsAssignment:
order = self.Transactions.GetOrderById(orderEvent.OrderId)
if order.Type == OrderType.OptionExercise:
self.Log(str(order))
def OnAssignmentOrderEvent(self, assignmentEvent):
self.Log(str(assignmentEvent))
self._assignedOption = True