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# 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.Algorithm import *
from QuantConnect.Algorithm.Framework import *
from QuantConnect.Algorithm.Framework.Portfolio import PortfolioTarget, PortfolioTargetCollection
from QuantConnect.Algorithm.Framework.Risk import RiskManagementModel
from itertools import groupby
class MaximumSectorExposureRiskManagementModel(RiskManagementModel):
'''Provides an implementation of IRiskManagementModel that that limits the sector exposure to the specified percentage'''
def __init__(self, maximumSectorExposure = 0.20):
'''Initializes a new instance of the MaximumSectorExposureRiskManagementModel class
Args:
maximumDrawdownPercent: The maximum exposure for any sector, defaults to 20% sector exposure.'''
if maximumSectorExposure <= 0:
raise ValueError('MaximumSectorExposureRiskManagementModel: the maximum sector exposure cannot be a non-positive value.')
self.maximumSectorExposure = maximumSectorExposure
self.targetsCollection = PortfolioTargetCollection()
def ManageRisk(self, algorithm, targets):
'''Manages the algorithm's risk at each time step
Args:
algorithm: The algorithm instance'''
maximumSectorExposureValue = float(algorithm.Portfolio.TotalPortfolioValue) * self.maximumSectorExposure
self.targetsCollection.AddRange(targets)
risk_targets = list()
# Group the securities by their sector
filtered = list(filter(lambda x: x.Value.Fundamentals is not None and x.Value.Fundamentals.HasFundamentalData, algorithm.UniverseManager.ActiveSecurities))
filtered.sort(key = lambda x: x.Value.Fundamentals.CompanyReference.IndustryTemplateCode)
groupBySector = groupby(filtered, lambda x: x.Value.Fundamentals.CompanyReference.IndustryTemplateCode)
for code, securities in groupBySector:
# Compute the sector absolute holdings value
# If the construction model has created a target, we consider that
# value to calculate the security absolute holding value
quantities = {}
sectorAbsoluteHoldingsValue = 0
for security in securities:
symbol = security.Value.Symbol
quantities[symbol] = security.Value.Holdings.Quantity
absoluteHoldingsValue = security.Value.Holdings.AbsoluteHoldingsValue
if self.targetsCollection.ContainsKey(symbol):
quantities[symbol] = self.targetsCollection[symbol].Quantity
absoluteHoldingsValue = (security.Value.Price * abs(quantities[symbol]) *
security.Value.SymbolProperties.ContractMultiplier *
security.Value.QuoteCurrency.ConversionRate)
sectorAbsoluteHoldingsValue += absoluteHoldingsValue
# If the ratio between the sector absolute holdings value and the maximum sector exposure value
# exceeds the unity, it means we need to reduce each security of that sector by that ratio
# Otherwise, it means that the sector exposure is below the maximum and there is nothing to do.
ratio = float(sectorAbsoluteHoldingsValue) / maximumSectorExposureValue
if ratio > 1:
for symbol, quantity in quantities.items():
if quantity != 0:
risk_targets.append(PortfolioTarget(symbol, float(quantity) / ratio))
return risk_targets
def OnSecuritiesChanged(self, algorithm, changes):
'''Event fired each time the we add/remove securities from the data feed
Args:
algorithm: The algorithm instance that experienced the change in securities
changes: The security additions and removals from the algorithm'''
anyFundamentalData = any([
kvp.Value.Fundamentals is not None and
kvp.Value.Fundamentals.HasFundamentalData for kvp in algorithm.ActiveSecurities
]);
if not anyFundamentalData:
raise Exception("MaximumSectorExposureRiskManagementModel.OnSecuritiesChanged: Please select a portfolio selection model that selects securities with fundamental data.")
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