Martin-Molinero
f8b258d329
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* New Fundamental Data * Minor CIK lookup fix * Handle live mode & delete unexisting properties * Minor coarse fundamental adjustment * Add fundamental history support * Fix unit tests * Performance improvements * Fixes * Minor regression algorithm fix * Improvements. Add FundamentalUniverseSelectionModel * Change default values * Fix unit test * Minor tweaks * Fix unit test * Minor error handling improvement * Fix rebase
80 lines
3.1 KiB
Python
80 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 AlgorithmImports import *
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### <summary>
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### Demonstration of how to define a universe using the fundamental data
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="universes" />
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### <meta name="tag" content="coarse universes" />
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### <meta name="tag" content="regression test" />
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class FundamentalUniverseSelectionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2014, 3, 25)
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self.SetEndDate(2014, 4, 7)
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self.UniverseSettings.Resolution = Resolution.Daily
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self.AddEquity("SPY")
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self.AddEquity("AAPL")
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self.SetUniverseSelection(FundamentalUniverseSelectionModel(self.Select))
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self.changes = None
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# return a list of three fixed symbol objects
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def SelectionFunction(self, fundamental):
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# sort descending by daily dollar volume
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sortedByDollarVolume = sorted([x for x in fundamental if x.Price > 1],
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key=lambda x: x.DollarVolume, reverse=True)
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# sort descending by P/E ratio
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sortedByPeRatio = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.PERatio, reverse=True)
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# take the top entries from our sorted collection
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return [ x.Symbol for x in sortedByPeRatio[:self.numberOfSymbolsFundamental] ]
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def OnData(self, data):
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# if we have no changes, do nothing
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if self.changes is None: return
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# liquidate removed securities
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for security in self.changes.RemovedSecurities:
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if security.Invested:
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self.Liquidate(security.Symbol)
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self.Debug("Liquidated Stock: " + str(security.Symbol.Value))
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# we want 50% allocation in each security in our universe
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for security in self.changes.AddedSecurities:
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self.SetHoldings(security.Symbol, 0.02)
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self.changes = None
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# this event fires whenever we have changes to our universe
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def OnSecuritiesChanged(self, changes):
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self.changes = changes
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def Select(self, fundamental):
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# sort descending by daily dollar volume
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sortedByDollarVolume = sorted([x for x in fundamental if x.HasFundamentalData and x.Price > 1],
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key=lambda x: x.DollarVolume, reverse=True)
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# sort descending by P/E ratio
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sortedByPeRatio = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.PERatio, reverse=True)
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# take the top entries from our sorted collection
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return [ x.Symbol for x in sortedByPeRatio[:2] ]
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