Louis Szeto
20e9fd7899
* Fail on restart investing after liquidation I added a line so that the trailing high value could be rebalanced and the investment process won't be stop by high value always more than current value by drawdown percent. * Update MaximumDrawdownPercentPortfolio.py * Fix for MaximumDrawdownPercentPortfolio - Fix C# MaximumDrawdownPercentPortfolio to reset portfolio value after liquidation. Only reset once we have actually adjusted some targets. Updating regression algorithms. Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
65 lines
3.1 KiB
Python
65 lines
3.1 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 clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Common")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Algorithm.Framework")
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Algorithm.Framework import *
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from QuantConnect.Algorithm.Framework.Portfolio import PortfolioTarget
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from QuantConnect.Algorithm.Framework.Risk import RiskManagementModel
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class MaximumDrawdownPercentPortfolio(RiskManagementModel):
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'''Provides an implementation of IRiskManagementModel that limits the drawdown of the portfolio to the specified percentage.'''
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def __init__(self, maximumDrawdownPercent = 0.05, isTrailing = False):
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'''Initializes a new instance of the MaximumDrawdownPercentPortfolio class
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Args:
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maximumDrawdownPercent: The maximum percentage drawdown allowed for algorithm portfolio compared with starting value, defaults to 5% drawdown</param>
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isTrailing: If "false", the drawdown will be relative to the starting value of the portfolio.
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If "true", the drawdown will be relative the last maximum portfolio value'''
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self.maximumDrawdownPercent = -abs(maximumDrawdownPercent)
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self.isTrailing = isTrailing
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self.initialised = False
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self.portfolioHigh = 0;
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def ManageRisk(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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currentValue = algorithm.Portfolio.TotalPortfolioValue
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if not self.initialised:
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self.portfolioHigh = currentValue # Set initial portfolio value
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self.initialised = True
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# Update trailing high value if in trailing mode
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if self.isTrailing and self.portfolioHigh < currentValue:
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self.portfolioHigh = currentValue
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return [] # return if new high reached
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pnl = self.GetTotalDrawdownPercent(currentValue)
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if pnl < self.maximumDrawdownPercent and len(targets) != 0:
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self.initialised = False # reset the trailing high value for restart investing on next rebalcing period
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return [ PortfolioTarget(target.Symbol, 0) for target in targets ]
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return []
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def GetTotalDrawdownPercent(self, currentValue):
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return (float(currentValue) / float(self.portfolioHigh)) - 1.0
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