# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from AlgorithmImports import * from BaseFrameworkRegressionAlgorithm import BaseFrameworkRegressionAlgorithm from Risk.MaximumSectorExposureRiskManagementModel import MaximumSectorExposureRiskManagementModel ### ### Regression algorithm to assert the behavior of . ### class MaximumSectorExposureRiskManagementModelFrameworkRegressionAlgorithm(BaseFrameworkRegressionAlgorithm): def Initialize(self): super().Initialize() # Set requested data resolution self.UniverseSettings.Resolution = Resolution.Daily self.SetStartDate(2014, 2, 1) #Set Start Date self.SetEndDate(2014, 5, 1) #Set End Date # set algorithm framework models tickers = [ "AAPL", "MSFT", "GOOG", "AIG", "BAC" ] self.SetUniverseSelection(FineFundamentalUniverseSelectionModel( lambda coarse: [ x.Symbol for x in coarse if x.Symbol.Value in tickers ], lambda fine: [ x.Symbol for x in fine ] )) # define risk management model such that maximum weight of a single sector be 10% # Number of of trades changed from 34 to 30 when using the MaximumSectorExposureRiskManagementModel self.SetRiskManagement(MaximumSectorExposureRiskManagementModel(0.1)) def OnEndOfAlgorithm(self): pass