wehub-resource-sync
116 lines
5.8 KiB
Python
116 lines
5.8 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 AlgorithmImports import *
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class FundamentalUniverseSelectionModel:
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'''Provides a base class for defining equity coarse/fine fundamental selection models'''
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def __init__(self,
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filter_fine_data = None,
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universe_settings = None):
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'''Initializes a new instance of the FundamentalUniverseSelectionModel class
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Args:
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filter_fine_data: [Obsolete] Fine and Coarse selection are merged
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universeSettings: The settings used when adding symbols to the algorithm, specify null to use algorithm.universe_settings'''
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self.filter_fine_data = filter_fine_data
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if self.filter_fine_data == None:
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self.fundamental_data = True
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else:
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self.fundamental_data = False
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self.market = Market.USA
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self.universe_settings = universe_settings
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def create_universes(self, algorithm: QCAlgorithm) -> list[Universe]:
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'''Creates a new fundamental universe using this class's selection functions
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Args:
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algorithm: The algorithm instance to create universes for
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Returns:
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The universe defined by this model'''
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if self.fundamental_data:
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universe_settings = algorithm.universe_settings if self.universe_settings is None else self.universe_settings
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# handle both 'Select' and 'select' for backwards compatibility
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selection = lambda fundamental: self.select(algorithm, fundamental)
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if hasattr(self, "Select") and callable(self.Select):
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selection = lambda fundamental: self.Select(algorithm, fundamental)
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universe = FundamentalUniverseFactory(self.market, universe_settings, selection)
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return [universe]
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else:
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universe = self.create_coarse_fundamental_universe(algorithm)
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if self.filter_fine_data:
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if universe.universe_settings.asynchronous:
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raise ValueError("Asynchronous universe setting is not supported for coarse & fine selections, please use the new Fundamental single pass selection")
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selection = lambda fine: self.select_fine(algorithm, fine)
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if hasattr(self, "SelectFine") and callable(self.SelectFine):
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selection = lambda fine: self.SelectFine(algorithm, fine)
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universe = FineFundamentalFilteredUniverse(universe, selection)
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return [universe]
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def create_coarse_fundamental_universe(self, algorithm: QCAlgorithm) -> Universe:
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'''Creates the coarse fundamental universe object.
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This is provided to allow more flexibility when creating coarse universe.
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Args:
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algorithm: The algorithm instance
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Returns:
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The coarse fundamental universe'''
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universe_settings = algorithm.universe_settings if self.universe_settings is None else self.universe_settings
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return CoarseFundamentalUniverse(universe_settings, lambda coarse: self.filtered_select_coarse(algorithm, coarse))
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def filtered_select_coarse(self, algorithm: QCAlgorithm, fundamental: list[Fundamental]) -> list[Symbol]:
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'''Defines the coarse fundamental selection function.
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If we're using fine fundamental selection than exclude symbols without fine data
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Args:
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algorithm: The algorithm instance
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coarse: The coarse fundamental data used to perform filtering
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Returns:
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An enumerable of symbols passing the filter'''
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if self.filter_fine_data:
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fundamental = filter(lambda c: c.has_fundamental_data, fundamental)
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if hasattr(self, "SelectCoarse") and callable(self.SelectCoarse):
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# handle both 'select_coarse' and 'SelectCoarse' for backwards compatibility
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return self.SelectCoarse(algorithm, fundamental)
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return self.select_coarse(algorithm, fundamental)
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def select(self, algorithm: QCAlgorithm, fundamental: list[Fundamental]) -> list[Symbol]:
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'''Defines the fundamental selection function.
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Args:
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algorithm: The algorithm instance
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fundamental: The fundamental data used to perform filtering
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Returns:
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An enumerable of symbols passing the filter'''
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raise NotImplementedError("Please overrride the 'select' fundamental function")
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def select_coarse(self, algorithm: QCAlgorithm, fundamental: list[Fundamental]) -> list[Symbol]:
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'''Defines the coarse fundamental selection function.
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Args:
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algorithm: The algorithm instance
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coarse: The coarse fundamental data used to perform filtering
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Returns:
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An enumerable of symbols passing the filter'''
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raise NotImplementedError("Please overrride the 'select' fundamental function")
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def select_fine(self, algorithm: QCAlgorithm, fundamental: list[Fundamental]) -> list[Symbol]:
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'''Defines the fine fundamental selection function.
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Args:
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algorithm: The algorithm instance
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fine: The fine fundamental data used to perform filtering
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Returns:
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An enumerable of symbols passing the filter'''
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return [f.symbol for f in fundamental]
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