Martin-Molinero
03f56481d4
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Python research import improvements - Improve start.py for research env - Remove unrequired imports * Centralize algorithm imports * Add regression test GH action * Unit test python import clean up * Join research and main imports * More python import clean up * Fix failing skipped regression algorithm
79 lines
3.4 KiB
Python
79 lines
3.4 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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### <summary>
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### Expiry Helper algorithm uses Expiry helper class in an Alpha Model
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### </summary>
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class ExpiryHelperAlphaModelFrameworkAlgorithm(QCAlgorithm):
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'''Expiry Helper framework algorithm uses Expiry helper class in an Alpha Model'''
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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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# Set requested data resolution
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self.UniverseSettings.Resolution = Resolution.Hour
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self.SetStartDate(2013,10,7) #Set Start Date
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self.SetEndDate(2014,1,1) #Set End Date
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self.SetCash(100000) #Set Strategy Cash
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symbols = [ Symbol.Create("SPY", SecurityType.Equity, Market.USA) ]
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# set algorithm framework models
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self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
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self.SetAlpha(self.ExpiryHelperAlphaModel())
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self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
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self.SetExecution(ImmediateExecutionModel())
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self.SetRiskManagement(MaximumDrawdownPercentPerSecurity(0.01))
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self.InsightsGenerated += self.OnInsightsGenerated
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def OnInsightsGenerated(self, s, e):
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for insight in e.Insights:
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self.Log(f"{e.DateTimeUtc.isoweekday()}: Close Time {insight.CloseTimeUtc} {insight.CloseTimeUtc.isoweekday()}")
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class ExpiryHelperAlphaModel(AlphaModel):
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nextUpdate = None
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direction = InsightDirection.Up
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def Update(self, algorithm, data):
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if self.nextUpdate is not None and self.nextUpdate > algorithm.Time:
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return []
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expiry = Expiry.EndOfDay
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# Use the Expiry helper to calculate a date/time in the future
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self.nextUpdate = expiry(algorithm.Time)
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weekday = algorithm.Time.isoweekday()
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insights = []
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for symbol in data.Bars.Keys:
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# Expected CloseTime: next month on the same day and time
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if weekday == 1:
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insights.append(Insight.Price(symbol, Expiry.OneMonth, self.direction))
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# Expected CloseTime: next month on the 1st at market open time
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elif weekday == 2:
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insights.append(Insight.Price(symbol, Expiry.EndOfMonth, self.direction))
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# Expected CloseTime: next Monday at market open time
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elif weekday == 3:
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insights.append(Insight.Price(symbol, Expiry.EndOfWeek, self.direction))
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# Expected CloseTime: next day (Friday) at market open time
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elif weekday == 4:
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insights.append(Insight.Price(symbol, Expiry.EndOfDay, self.direction))
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return insights
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