AlexCatarino
9211b67286
CoarseFineFundamentalRegressionAlgorithm CoarseFundamentalTop5Algorithm DropboxUniverseSelectionAlgorithm FractionalQuantityRegressionAlgorithm
87 lines
3.5 KiB
Python
87 lines
3.5 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.Core")
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AddReference("QuantConnect.Common")
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AddReference("QuantConnect.Algorithm")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import QCAlgorithm
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from QuantConnect.Data.UniverseSelection import *
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from datetime import datetime
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### <summary>
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### Demonstration of how to define a universe as a combination of use the coarse fundamental data and fine 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 CoarseFineFundamentalRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2014,04,01) #Set Start Date
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self.SetEndDate(2014,04,30) #Set End Date
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self.SetCash(50000) #Set Strategy Cash
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self.UniverseSettings.Resolution = Resolution.Daily
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# this add universe method accepts two parameters:
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# - coarse selection function: accepts an IEnumerable<CoarseFundamental> and returns an IEnumerable<Symbol>
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# - fine selection function: accepts an IEnumerable<FineFundamental> and returns an IEnumerable<Symbol>
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self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
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self.changes = None
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self.numberOfSymbolsFine = 2
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# return a list of three fixed symbol objects
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def CoarseSelectionFunction(self, coarse):
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tickers = [ "GOOG", "BAC", "SPY" ]
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if self.Time < datetime(2014, 4, 5):
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tickers = [ "AAPL", "AIG", "IBM" ]
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return [ Symbol.Create(x, SecurityType.Equity, Market.USA) for x in tickers ]
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# sort the data by P/E ratio and take the top 'NumberOfSymbolsFine'
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def FineSelectionFunction(self, fine):
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# sort descending by P/E ratio
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sortedByPeRatio = sorted(fine, 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.numberOfSymbolsFine] ]
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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 == 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, 0.5)
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self.Debug("Purchased Stock: " + str(security.Symbol.Value))
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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 |