Adds demonstration Tiingo NLP Algorithms

* Adds `AltData` folder to Algorithm.CSharp|Python
2019-10-03 11:17:46 -07:00
parent 5f5a14c6f3
commit b61377cd37
4 changed files with 144 additions and 0 deletions
@@ -0,0 +1,67 @@
+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from clr import AddReference
+AddReference("System")
+AddReference("QuantConnect.Algorithm")
+AddReference("QuantConnect.Common")
+
+from System import *
+from QuantConnect import *
+from QuantConnect.Algorithm import *
+from QuantConnect.Data.Custom.Tiingo import *
+
+### <summary>
+### Look for positive and negative words in the news article description
+### and trade based on the sum of the sentiment
+### </summary>
+class TiingoNLPDemonstrationAlgorithm(QCAlgorithm):
+
+    def Initialize(self):
+        # Predefine a dictionary of words with scores to scan for in the description
+        # of the Tiingo news article
+        self.words = {
+            "bad": -0.5, "good": 0.5,
+            "negative": -0.5, "great": 0.5,
+            "growth": 0.5, "fail": -0.5,
+            "failed": -0.5, "success": 0.5, "nailed": 0.5,
+            "beat": 0.5, "missed": -0.5,
+        }
+
+        self.SetStartDate(2019, 6, 10)
+        self.SetEndDate(2019, 10, 3)
+        self.SetCash(100000)
+
+        aapl = self.AddEquity("AAPL", Resolution.Hour).Symbol
+        self.aaplCustom = self.AddData(TiingoNews, aapl).Symbol
+
+    def OnData(self, data):
+        # Confirm that the data is in the collection
+        if not data.ContainsKey(self.aaplCustom):
+            return
+
+        # Gets the data from the slice
+        article = data[self.aaplCustom]
+
+        # Article descriptions come in all caps. Lower and split by word
+        descriptionWords = article.Description.lower().split(" ")
+
+        # Take the intersection of predefined words and the words in the
+        # description to get a list of matching words
+        intersection = set(self.words.keys()).intersection(descriptionWords)
+
+        # Get the sum of the article's sentiment, and go long or short
+        # depending if it's a positive or negative description
+        sentiment = sum([self.words[i] for i in intersection])
+
+        self.SetHoldings(article.Symbol.Underlying, sentiment)
@@ -60,6 +60,7 @@
    <Content Include="Alphas\ShareClassMeanReversionAlpha.py" />
    <Content Include="Alphas\TripleLeverageETFPairVolatilityDecayAlpha.py" />
    <Content Include="Alphas\VIXDualThrustAlpha.py" />
+    <Content Include="AltData\TiingoNLPDemonstrationAlgorithm.py" />
    <Content Include="BasicCSharpIntegrationTemplateAlgorithm.py" />
    <Content Include="BasicSetAccountCurrencyAlgorithm.py" />
    <None Include="USTreasuryYieldCurveDataAlgorithm.py" />