wehub-resource-sync
48 lines
2.0 KiB
Python
48 lines
2.0 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 MaximumDrawdownPercentPerSecurity(RiskManagementModel):
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'''Provides an implementation of IRiskManagementModel that limits the drawdown per holding to the specified percentage'''
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def __init__(self, maximum_drawdown_percent = 0.05):
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'''Initializes a new instance of the MaximumDrawdownPercentPerSecurity class
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Args:
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maximum_drawdown_percent: The maximum percentage drawdown allowed for any single security holding'''
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self.maximum_drawdown_percent = -abs(maximum_drawdown_percent)
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def manage_risk(self, algorithm, targets):
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'''Manages the algorithm's risk at each time step
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Args:
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algorithm: The algorithm instance
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targets: The current portfolio targets to be assessed for risk'''
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targets = []
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for kvp in algorithm.securities:
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security = kvp.value
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if not security.invested:
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continue
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pnl = security.holdings.unrealized_profit_percent
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if pnl < self.maximum_drawdown_percent:
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symbol = security.symbol
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# Cancel insights
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algorithm.insights.cancel([symbol])
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# liquidate
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targets.append(PortfolioTarget(symbol, 0))
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return targets
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