Jhonathan Abreu
372c197890
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* Send one-time warning about mismatching canonicals/contracts models * Add regression algorithms
97 lines
3.7 KiB
Python
97 lines
3.7 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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from System import Action
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from QuantConnect.Logging import *
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### <summary>
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### Regression algorithm asserting that when setting custom models for canonical securities, a one-time warning is sent
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### informing the user that the contracts models are different (not the custom ones).
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### </summary>
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class OptionModelsConsistencyRegressionAlgorithm(QCAlgorithm):
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def Initialize(self) -> None:
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self.warning_sent = False
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# Set a functional log handler in order to be able to assert on the warning message
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self.original_log_handler = Log.LogHandler
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Log.LogHandler = CompositeLogHandler(
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[
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Log.LogHandler,
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FunctionalLogHandler(
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Action[String](lambda debug_message: None),
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Action[String](self.CheckWarningMessage),
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Action[String](lambda error_message: None))
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])
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security = self.InitializeAlgorithm()
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self.SetModels(security)
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# Using a custom security initializer derived from BrokerageModelSecurityInitializer
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# to check that the models are correctly set in the security even when the
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# security initializer is derived from said class in Python
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self.SetSecurityInitializer(CustomSecurityInitializer(self.BrokerageModel, SecuritySeeder.Null))
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self.SetBenchmark(lambda x: 0)
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def InitializeAlgorithm(self) -> Security:
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self.SetStartDate(2015, 12, 24)
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self.SetEndDate(2015, 12, 24)
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equity = self.AddEquity("GOOG", leverage=4)
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option = self.AddOption(equity.Symbol)
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option.SetFilter(lambda u: u.Strikes(-2, +2).Expiration(0, 180))
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return option
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def SetModels(self, security: Security) -> None:
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security.SetFillModel(CustomFillModel())
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security.SetFeeModel(CustomFeeModel())
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security.SetBuyingPowerModel(CustomBuyingPowerModel())
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security.SetSlippageModel(CustomSlippageModel())
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security.SetVolatilityModel(CustomVolatilityModel())
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def OnEndOfAlgorithm(self) -> None:
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Log.LogHandler = self.original_log_handler
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if not self.warning_sent:
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raise Exception("On-time warning about canonical models mismatch was not sent.")
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def CheckWarningMessage(self, message: str) -> None:
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if ("Debug: Warning: Security " in message and
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"To avoid this, consider using a security initializer to set the right models to each security type according to your algorithm's requirements." in message):
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self.warning_sent = True
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class CustomSecurityInitializer(BrokerageModelSecurityInitializer):
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def __init__(self, brokerage_model: BrokerageModel, security_seeder: SecuritySeeder):
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super().__init__(brokerage_model, security_seeder)
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class CustomFillModel(FillModel):
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pass
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class CustomFeeModel(FeeModel):
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pass
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class CustomBuyingPowerModel(BuyingPowerModel):
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pass
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class CustomSlippageModel(ConstantSlippageModel):
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def __init__(self):
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super().__init__(0)
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class CustomVolatilityModel(BaseVolatilityModel):
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pass
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