Martin Molinero
93 lines
4.3 KiB
Python
93 lines
4.3 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.Common")
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AddReference("QuantConnect.Algorithm.Framework")
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from QuantConnect.Data.UniverseSelection 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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filterFineData,
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universeSettings = None,
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securityInitializer = None):
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'''Initializes a new instance of the FundamentalUniverseSelectionModel class
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Args:
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filterFineData: True to also filter using fine fundamental data, false to only filter on coarse data
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universeSettings: The settings used when adding symbols to the algorithm, specify null to use algorthm.UniverseSettings
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securityInitializer: Optional security initializer invoked when creating new securities, specify null to use algorithm.SecurityInitializer'''
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self.filterFineData = filterFineData
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self.universeSettings = universeSettings
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self.securityInitializer = securityInitializer
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def CreateUniverses(self, algorithm):
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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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universe = self.CreateCoarseFundamentalUniverse(algorithm)
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print(universe)
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if self.filterFineData:
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universe = FineFundamentalFilteredUniverse(universe, lambda fine: self.SelectFine(algorithm, fine))
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return [universe]
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def CreateCoarseFundamentalUniverse(self, algorithm):
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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, such as using algorithm.Universe.DollarVolume.Top(5)
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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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universeSettings = algorithm.UniverseSettings if self.universeSettings is None else self.universeSettings
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securityInitializer = algorithm.SecurityInitializer if self.securityInitializer is None else self.securityInitializer
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return CoarseFundamentalUniverse(universeSettings, securityInitializer, lambda coarse: self.FilteredSelectCoarse(algorithm, coarse))
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def FilteredSelectCoarse(self, algorithm, coarse):
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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.filterFineData:
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coarse = filter(lambda c: c.HasFundamentalData, coarse)
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return self.SelectCoarse(algorithm, coarse)
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def SelectCoarse(self, algorithm, coarse):
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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("SelectCoarse must be implemented")
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def SelectFine(self, algorithm, fine):
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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 fine] |