Martin Molinero
64 lines
2.7 KiB
Python
64 lines
2.7 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.Algorithm")
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AddReference("QuantConnect.Algorithm.Framework")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Orders 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.Selection import *
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# we load the python version of these models:
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from Alphas.ConstantAlphaModel import *
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from Execution.ImmediateExecutionModel import *
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from Portfolio.EqualWeightingPortfolioConstructionModel import *
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from datetime import timedelta
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### <summary>
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### Basic template framework algorithm uses framework components to define the algorithm.
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### </summary>
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class PortfolioRebalanceOnCustomFuncRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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''' Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.UniverseSettings.Resolution = Resolution.Daily
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self.SetStartDate(2015, 1, 5)
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self.SetEndDate(2017, 1, 1)
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self.Settings.RebalancePortfolioOnInsightChanges = False;
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self.SetUniverseSelection(CustomUniverseSelectionModel("CustomUniverseSelectionModel", lambda time: [ "AAPL", "IBM", "FB", "SPY" ]))
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self.SetAlpha(ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromMinutes(20), 0.025, None));
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self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel(self.RebalanceFunction))
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self.SetExecution(ImmediateExecutionModel())
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self.lastRebalanceTime = self.StartDate
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def RebalanceFunction(self, time):
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self.lastRebalanceTime = time
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if self.Portfolio.MarginRemaining > 60000 or self.Portfolio.MarginRemaining < 40000:
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return time
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return None
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def OnOrderEvent(self, orderEvent):
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if orderEvent.Status == OrderStatus.Submitted:
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if self.UtcTime != self.lastRebalanceTime:
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raise ValueError(f"{self.UtcTime} {orderEvent.Symbol}")
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