Gerardo Salazar
bc1f608dce
* Makes BenzingaNewsAlgorithm throw a hard error if the Symbol is not found inside the BenzingaNews object in OnData
79 lines
3.3 KiB
Python
79 lines
3.3 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.Algorithm import *
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from QuantConnect.Algorithm.Framework.Selection import *
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from QuantConnect.Data.Custom.Benzinga import *
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from QuantConnect.Data.UniverseSelection import *
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class BenzingaNewsAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2018, 10, 12)
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self.SetEndDate(2018, 11, 25)
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self.SetCash(100000)
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self.UniverseSettings.Resolution = Resolution.Daily
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self.AddUniverseSelection(CoarseFundamentalUniverseSelectionModel(self.CoarseSelector))
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def CoarseSelector(self, coarse):
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# Add Benzinga news data from the filtered coarse selection
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symbols = [i.Symbol for i in coarse if i.HasFundamentalData and i.DollarVolume > 50000000][:10]
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for symbol in symbols:
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self.AddData(BenzingaNews, symbol)
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return symbols
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def OnData(self, data):
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# Get all Benzinga data and loop over it
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for article in data.Get(BenzingaNews).Values:
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selectedSymbol = None
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# Use loop instead of list comprehension for clarity purposes
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# Select the same Symbol we're getting a data point for
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# from the articles list so that we can get the sentiment of the article
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# We use the underlying Symbol because the Symbols included in the `Symbols` property
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# are equity Symbols.
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for x in article.Symbols:
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if x.Symbol == article.Symbol.Underlying:
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selectedSymbol = x
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break
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if selectedSymbol is None:
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raise Exception(f"Could not find current Symbol {article.Symbol.Underlying} even though it should exist")
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# Sometimes sentiment is not included with the article by Benzinga.
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# We have to check for null values before using it.
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sentimentScore = selectedSymbol = selectedSymbol.Sentiment
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if sentimentScore is None:
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continue
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# Set holdings equal to 1/10th of the sentiment score we get
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self.SetHoldings(article.Symbol.Underlying, sentimentScore / 10.0)
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def OnSecuritiesChanged(self, changes):
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for r in changes.RemovedSecurities:
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# If removed from the universe, liquidate and remove the custom data from the algorithm
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self.Liquidate(r.Symbol)
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self.RemoveSecurity(Symbol.CreateBase(BenzingaNews, r.Symbol, Market.USA))
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