Martin-Molinero
03f56481d4
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Python research import improvements - Improve start.py for research env - Remove unrequired imports * Centralize algorithm imports * Add regression test GH action * Unit test python import clean up * Join research and main imports * More python import clean up * Fix failing skipped regression algorithm
65 lines
2.7 KiB
Python
65 lines
2.7 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 AlgorithmImports import *
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### <summary>
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### Example demonstrating how to define an option price model.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="options" />
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### <meta name="tag" content="filter selection" />
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### <meta name="tag" content="option price model" />
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class BasicTemplateOptionsPriceModel(QCAlgorithm):
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'''Example demonstrating how to define an option price model.'''
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def Initialize(self):
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self.SetStartDate(2020, 1, 1)
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self.SetEndDate(2020, 1, 5)
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self.SetCash(100000)
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# Add the option
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option = self.AddOption("AAPL")
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self.optionSymbol = option.Symbol
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# Add the initial contract filter
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option.SetFilter(-3, +3, 0, 31)
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# Define the Option Price Model
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option.PriceModel = OptionPriceModels.CrankNicolsonFD()
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#option.PriceModel = OptionPriceModels.BlackScholes()
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#option.PriceModel = OptionPriceModels.AdditiveEquiprobabilities()
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#option.PriceModel = OptionPriceModels.BaroneAdesiWhaley()
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#option.PriceModel = OptionPriceModels.BinomialCoxRossRubinstein()
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#option.PriceModel = OptionPriceModels.BinomialJarrowRudd()
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#option.PriceModel = OptionPriceModels.BinomialJoshi()
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#option.PriceModel = OptionPriceModels.BinomialLeisenReimer()
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#option.PriceModel = OptionPriceModels.BinomialTian()
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#option.PriceModel = OptionPriceModels.BinomialTrigeorgis()
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#option.PriceModel = OptionPriceModels.BjerksundStensland()
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#option.PriceModel = OptionPriceModels.Integral()
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# Set warm up with 30 trading days to warm up the underlying volatility model
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self.SetWarmUp(30, Resolution.Daily)
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def OnData(self,slice):
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'''OnData will test whether the option contracts has a non-zero Greeks.Delta'''
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if self.IsWarmingUp or not slice.OptionChains.ContainsKey(self.optionSymbol):
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return
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chain = slice.OptionChains[self.optionSymbol]
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if not any([x for x in chain if x.Greeks.Delta != 0]):
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self.Log(f'No contract with Delta != 0')
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