wehub-resource-sync
74 lines
3.8 KiB
Python
74 lines
3.8 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 TrailingStopRiskManagementModel(RiskManagementModel):
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'''Provides an implementation of IRiskManagementModel that limits the maximum possible loss
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measured from the highest unrealized profit'''
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def __init__(self, maximum_drawdown_percent = 0.05):
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'''Initializes a new instance of the TrailingStopRiskManagementModel class
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Args:
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maximum_drawdown_percent: The maximum percentage drawdown allowed for algorithm portfolio compared with the highest unrealized profit, defaults to 5% drawdown'''
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self.maximum_drawdown_percent = abs(maximum_drawdown_percent)
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self.trailing_absolute_holdings_state = dict()
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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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risk_adjusted_targets = list()
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for kvp in algorithm.securities:
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symbol = kvp.key
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security = kvp.value
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# Remove if not invested
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if not security.invested:
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self.trailing_absolute_holdings_state.pop(symbol, None)
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continue
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position = PositionSide.LONG if security.holdings.is_long else PositionSide.SHORT
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absolute_holdings_value = security.holdings.absolute_holdings_value
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trailing_absolute_holdings_state = self.trailing_absolute_holdings_state.get(symbol)
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# Add newly invested security (if doesn't exist) or reset holdings state (if position changed)
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if trailing_absolute_holdings_state == None or position != trailing_absolute_holdings_state.position:
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self.trailing_absolute_holdings_state[symbol] = trailing_absolute_holdings_state = self.HoldingsState(position, security.holdings.absolute_holdings_cost)
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trailing_absolute_holdings_value = trailing_absolute_holdings_state.absolute_holdings_value
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# Check for new max (for long position) or min (for short position) absolute holdings value
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if ((position == PositionSide.LONG and trailing_absolute_holdings_value < absolute_holdings_value) or
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(position == PositionSide.SHORT and trailing_absolute_holdings_value > absolute_holdings_value)):
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self.trailing_absolute_holdings_state[symbol].absolute_holdings_value = absolute_holdings_value
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continue
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drawdown = abs((trailing_absolute_holdings_value - absolute_holdings_value) / trailing_absolute_holdings_value)
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if self.maximum_drawdown_percent < drawdown:
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# Cancel insights
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algorithm.insights.cancel([ symbol ]);
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self.trailing_absolute_holdings_state.pop(symbol, None)
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# liquidate
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risk_adjusted_targets.append(PortfolioTarget(symbol, 0))
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return risk_adjusted_targets
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class HoldingsState:
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def __init__(self, position, absolute_holdings_value):
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self.position = position
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self.absolute_holdings_value = absolute_holdings_value
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