Michael Handschuh
fdc866fda0
We didn't experience the expected performance improvements. Locally under unit test there was aboout an order of magnitude throughput increase, but when run against the history benchmark, this new approach was 60% slower. We're reverting this for now to perform further analysis and better understand the performance profiling of the python history stack.
72 lines
2.8 KiB
Python
72 lines
2.8 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from datetime import datetime, timedelta
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### <summary>
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### This regression algorithm tests option exercise and assignment functionality
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### We open two positions and go with them into expiration. We expect to see our long position exercised and short position assigned.
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### </summary>
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### <meta name="tag" content="regression test" />
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### <meta name="tag" content="options" />
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class OptionExerciseAssignRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetCash(100000)
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self.SetStartDate(2015,12,24)
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self.SetEndDate(2015,12,24)
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option = self.AddOption("GOOG")
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# set our strike/expiry filter for this option chain
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option.SetFilter(self.UniverseFunc)
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self.SetBenchmark("GOOG")
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self._assignedOption = False
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def OnData(self, slice):
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if self.Portfolio.Invested: return
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for kvp in slice.OptionChains:
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chain = kvp.Value
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# find the call options expiring today
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contracts = filter(lambda x:
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x.Expiry.date() == self.Time.date() and
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x.Strike < chain.Underlying.Price and
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x.Right == OptionRight.Call, chain)
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# sorted the contracts by their strikes, find the second strike under market price
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sorted_contracts = sorted(contracts, key = lambda x: x.Strike, reverse = True)[:2]
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if sorted_contracts:
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self.MarketOrder(sorted_contracts[0].Symbol, 1)
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self.MarketOrder(sorted_contracts[1].Symbol, -1)
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# set our strike/expiry filter for this option chain
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def UniverseFunc(self, universe):
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return universe.IncludeWeeklys().Strikes(-2, 2).Expiration(timedelta(0), timedelta(10))
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def OnOrderEvent(self, orderEvent):
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self.Log(str(orderEvent))
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def OnAssignmentOrderEvent(self, assignmentEvent):
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self.Log(str(assignmentEvent))
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self._assignedOption = True |