chore: import upstream snapshot with attribution
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# 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 AlgorithmImports import *
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### <summary>
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### This regression algorithm verifies automatic option contract assignment behavior.
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### </summary>
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class OptionAssignmentRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2015, 12, 23)
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self.set_end_date(2015, 12, 28)
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self.set_cash(100000)
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self.stock = self.add_equity("GOOG", Resolution.MINUTE)
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contracts = list(self.option_chain(self.stock.symbol))
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self.put_option_symbol = sorted(
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[c for c in contracts if c.id.option_right == OptionRight.PUT and c.id.strike_price == 800],
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key=lambda c: c.id.date
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)[0]
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self.call_option_symbol = sorted(
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[c for c in contracts if c.id.option_right == OptionRight.CALL and c.id.strike_price == 600],
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key=lambda c: c.id.date
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)[0]
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self.put_option = self.add_option_contract(self.put_option_symbol)
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self.call_option = self.add_option_contract(self.call_option_symbol)
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def on_data(self, data):
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if not self.portfolio.invested and self.stock.price != 0 and self.put_option.price != 0 and self.call_option.price != 0:
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#this gets executed on start and after each auto-assignment, finally ending with expiration assignment
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if self.time < self.put_option_symbol.id.date:
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self.market_order(self.put_option_symbol, -1)
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if self.time < self.call_option_symbol.id.date:
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self.market_order(self.call_option_symbol, -1)
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