text: ﻿# 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 clr import AddReference
  AddReference("System")
  AddReference("QuantConnect.Common")
  AddReference("QuantConnect.Algorithm")
  AddReference("QuantConnect.Algorithm.Framework")
  
  from QuantConnect import *
  from QuantConnect.Algorithm import *
  from QuantConnect.Algorithm.Framework import *
  from QuantConnect.Algorithm.Framework.Risk import RiskManagementModel
  
  class CompositeRiskManagementModel(RiskManagementModel):
      '''Provides an implementation of IRiskManagementModel that combines multiple risk models
      into a single risk management model and properly sets each insights 'SourceModel' property.'''
  
      def __init__(self, *riskManagementModels):
          '''Initializes a new instance of the CompositeRiskManagementModel class
          Args:
              riskManagementModels: The individual risk management models defining this composite model.'''
          for model in riskManagementModels:
              for attributeName in ['ManageRisk', 'OnSecuritiesChanged']:
                  if not hasattr(model, attributeName):
                      raise Exception(f'IRiskManagementModel.{attributeName} must be implemented. Please implement this missing method on {model.__class__.__name__}')
  
          self.riskManagementModels = riskManagementModels
  
      def ManageRisk(self, algorithm, targets):
          '''Manages the algorithm's risk at each time step
          Args:
              algorithm: The algorithm instance
              targets: The current portfolio targets to be assessed for risk'''
          for model in self.riskManagementModels:
              # take into account the possibility of ManageRisk returning nothing
              riskAdjusted = model.ManageRisk(algorithm, targets)
  
              # produce a distinct set of new targets giving preference to newer targets
              symbols = [x.Symbol for x in riskAdjusted]
              for target in targets:
                  if target.Symbol not in symbols:
                      riskAdjusted.append(target)
  
              targets = riskAdjusted
  
          return targets
  
      def OnSecuritiesChanged(self, algorithm, changes):
          '''Event fired each time the we add/remove securities from the data feed.
          This method patches this call through the each of the wrapped models.
          Args:
              algorithm: The algorithm instance that experienced the change in securities
              changes: The security additions and removals from the algorithm'''
          for model in self.riskManagementModels:
              model.OnSecuritiesChanged(algorithm, changes)
  