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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "That👇👇 was my status just a few days ago but thanks to @BP_plc @BP_Press Ive changed my mind because BP blessed me… https://t.co/wvoE9C8Z3h" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "BP" STOCK: 14/09/2018 DATE: 550.4
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @BP_plc.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: 0.0045421511627906 2_DAY_RETURN: -0.0116279069767441 3_DAY_RETURN: -0.0245276162790697 7_DAY_RETURN: 19538831.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.0025436046511627 PX_VOLUME: 15.361 VOLATILITY_10D: 16.758 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @BP_plc
Predicted 1_DAY_RETURN: 0.0045421511627906 Predicted 2_DAY_RETURN: -0.0116279069767441 Predicted 7_DAY_RETURN: 19538831.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Check out 99-03 Ford Diesel XC3F-12B599-AC IDM Injector Driver Control Module #Ford https://t.co/AlgVElxTaj via @eBay" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Ford" STOCK: 14/09/2018 DATE: 9.45
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0116402116402115 2_DAY_RETURN: -0.0148148148148146 3_DAY_RETURN: -0.019047619047619 7_DAY_RETURN: 30013336.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.0084656084656084 PX_VOLUME: 14.26 VOLATILITY_10D: 21.895 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0116402116402115 Predicted 2_DAY_RETURN: -0.0148148148148146 Predicted 7_DAY_RETURN: 30013336.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Check out this Amazon deal: MeeQee New Halloween Trick or Treat Banner Se... by MeeQee https://t.co/jS13Q8dt0W via @amazon" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Amazon" STOCK: 14/09/2018 DATE: 1970.19
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.13636363636363635 and the TextBlob polarity score is @amazon.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: 0.0100548678046279 2_DAY_RETURN: 0.0086083068130485 3_DAY_RETURN: -0.0091970825148844 7_DAY_RETURN: 3642030.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: 0.0099888843208014 PX_VOLUME: 23.601 VOLATILITY_10D: 19.372 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.13636363636363635 TEXTBLOB_POLARITY: @amazon
Predicted 1_DAY_RETURN: 0.0100548678046279 Predicted 2_DAY_RETURN: 0.0086083068130485 Predicted 7_DAY_RETURN: 3642030.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @BDSmovement: HSBC is a major shareholder in companies selling weapons & military technology to Israel. Tell @HSBC to divest from Elbit…" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "HSBC" STOCK: 14/09/2018 DATE: 658.4
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.018750000000000003 and the TextBlob polarity score is @HSBC.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0094167679222356 2_DAY_RETURN: -0.011543134872418 3_DAY_RETURN: -0.0050121506682866 7_DAY_RETURN: 18315618.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.0033414337788577 PX_VOLUME: 11.587 VOLATILITY_10D: 12.026 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.018750000000000003 TEXTBLOB_POLARITY: @HSBC
Predicted 1_DAY_RETURN: -0.0094167679222356 Predicted 2_DAY_RETURN: -0.011543134872418 Predicted 7_DAY_RETURN: 18315618.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@easyJet Suck my ass easyJet. You inconvenience passengers by forcing people to check their laggage -we get on the… https://t.co/amQdmHN0Fx" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "easyJet" STOCK: 14/09/2018 DATE: 1421.0
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @easyJet.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.004222378606615 2_DAY_RETURN: -0.0190007037297677 3_DAY_RETURN: 0.0133708655876143 7_DAY_RETURN: 1126082.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.0010555946516537 PX_VOLUME: 20.339 VOLATILITY_10D: 20.481 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @easyJet
Predicted 1_DAY_RETURN: -0.004222378606615 Predicted 2_DAY_RETURN: -0.0190007037297677 Predicted 7_DAY_RETURN: 1126082.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: Chegaram os novos iPhone XS, iPhone XS Max, iPhone XR e Apple Watch Series 4. #AppleEvent " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @SAP: SAP’s @AdaireFoxMartin shares how SAP is bringing our purpose of improving people’s lives to life with a specific target in mind #…" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "SAP" STOCK: 14/09/2018 DATE: 104.26
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @SAP.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0032610780740456 2_DAY_RETURN: -0.0151544216382121 3_DAY_RETURN: -0.0352963744484942 7_DAY_RETURN: 1514318.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.006713984270094 PX_VOLUME: 22.385 VOLATILITY_10D: 16.511 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP
Predicted 1_DAY_RETURN: -0.0032610780740456 Predicted 2_DAY_RETURN: -0.0151544216382121 Predicted 7_DAY_RETURN: 1514318.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@Apple How often is this incredibly annoying? Just about every single day. Did Apple remove the functionality of th… https://t.co/HomZAKHZG6" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Apple" STOCK: 14/09/2018 DATE: 223.84
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.8 and the TextBlob polarity score is @Apple.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0123749106504646 2_DAY_RETURN: 4.4674767691167376e-05 3_DAY_RETURN: -0.0113473909935667 7_DAY_RETURN: 31999289.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: 0.0114814152966404 PX_VOLUME: 25.688 VOLATILITY_10D: 17.88 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.8 TEXTBLOB_POLARITY: @Apple
Predicted 1_DAY_RETURN: -0.0123749106504646 Predicted 2_DAY_RETURN: 4.4674767691167376e-05 Predicted 7_DAY_RETURN: 31999289.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Check out New Alpatronix Black Folio Case KX101 with Stand for Apple iPad Mini 1,2,3,4 #Alpatronix https://t.co/DujDliff1k via @eBay " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is -0.015151515151515154.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -0.015151515151515154
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@Nissan hi you all fans of Nissan cars do you all want to laugh more today this is a 2014 versa please view this tr… https://t.co/lxN3S67wPV" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Nissan" STOCK: 14/09/2018 DATE: 1060.0
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.4 and the TextBlob polarity score is @Nissan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.030188679245283 2_DAY_RETURN: -0.0221698113207547 3_DAY_RETURN: -0.0367924528301886 7_DAY_RETURN: 15909200.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.0136792452830188 PX_VOLUME: 16.015 VOLATILITY_10D: 14.02 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.4 TEXTBLOB_POLARITY: @Nissan
Predicted 1_DAY_RETURN: -0.030188679245283 Predicted 2_DAY_RETURN: -0.0221698113207547 Predicted 7_DAY_RETURN: 15909200.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Check out Car Phone Holder 360 For iPhone X XS 8 7 6 Plus Samsung S9 S8 Note 9 8 https://t.co/sLccbDzK4F via @eBay" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Samsung" STOCK: 14/09/2018 DATE: 45850.0
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0283533260632497 2_DAY_RETURN: -0.0174482006543075 3_DAY_RETURN: -0.0207197382769901 7_DAY_RETURN: 12446344.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: -0.0392584514721919 PX_VOLUME: 32.88 VOLATILITY_10D: 26.92 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0283533260632497 Predicted 2_DAY_RETURN: -0.0174482006543075 Predicted 7_DAY_RETURN: 12446344.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Disgusting #everydaysexism from Amazon. Portraying a man incapable of looking after his kids. @amazon https://t.co/GuSGozt4Q9" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Amazon" STOCK: 14/09/2018 DATE: 1970.19
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1.0 and the TextBlob polarity score is @amazon.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: 0.0100548678046279 2_DAY_RETURN: 0.0086083068130485 3_DAY_RETURN: -0.0091970825148844 7_DAY_RETURN: 3642030.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: 0.0099888843208014 PX_VOLUME: 23.601 VOLATILITY_10D: 19.372 VOLATILITY_30D: -1.0 LSTM_POLARITY: -1.0 TEXTBLOB_POLARITY: @amazon
Predicted 1_DAY_RETURN: 0.0100548678046279 Predicted 2_DAY_RETURN: 0.0086083068130485 Predicted 7_DAY_RETURN: 3642030.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Reuters: ICYMI: Starbucks opens a branch run entirely by a staff aged over 55 to promote labor inclusion https://t.co/7JIhRQhnl5" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Starbucks" STOCK: 14/09/2018 DATE: 54.75
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.05 and the TextBlob polarity score is @Reuters.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: 0.0040182648401826 2_DAY_RETURN: 0.0067579908675798 3_DAY_RETURN: 0.0020091324200913 7_DAY_RETURN: 6827670.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: 0.0025570776255707 PX_VOLUME: 7.891 VOLATILITY_10D: 11.511 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.05 TEXTBLOB_POLARITY: @Reuters
Predicted 1_DAY_RETURN: 0.0040182648401826 Predicted 2_DAY_RETURN: 0.0067579908675798 Predicted 7_DAY_RETURN: 6827670.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@Google it looks like Google is a liberally slanted." STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Google" STOCK: 14/09/2018 DATE: 1177.98
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Google.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0054160512063024 2_DAY_RETURN: 0.0101954192770675 3_DAY_RETURN: -0.0003310752304793 7_DAY_RETURN: 1208767.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: 0.0035314691251125 PX_VOLUME: 16.637 VOLATILITY_10D: 16.840999999999998 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google
Predicted 1_DAY_RETURN: -0.0054160512063024 Predicted 2_DAY_RETURN: 0.0101954192770675 Predicted 7_DAY_RETURN: 1208767.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: The all-new iPhone XS, iPhone XS Max, iPhone XR and Apple Watch Series 4 are here. #AppleEvent " STOCK: Apple DATE: 14/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Apple 1_DAY_RETURN: 0.0114814152966404 2_DAY_RETURN: -0.0123749106504646 3_DAY_RETURN: 4.4674767691167376e-05 7_DAY_RETURN: -0.0113473909935667
The stock shows a consistent negative return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: Apple LAST_PRICE: 223.84 PX_VOLUME: 31999289.0 VOLATILITY_10D: 25.688 VOLATILITY_30D: 17.88 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0114814152966404 Predicted 2_DAY_RETURN: -0.0123749106504646 Predicted 7_DAY_RETURN: -0.0113473909935667
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Check out Imagine John Lennon 1977 Vinyl LP Apple Records Japan EAS-80705 + POSTER https://t.co/m9yweMj581 via @eBay" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
The stock shows a neutral return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
Predicted 1_DAY_RETURN: nan Predicted 2_DAY_RETURN: nan Predicted 7_DAY_RETURN: nan
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Apple" STOCK: 14/09/2018 DATE: 223.84
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 14/09/2018 1_DAY_RETURN: -0.0123749106504646 2_DAY_RETURN: 4.4674767691167376e-05 3_DAY_RETURN: -0.0113473909935667 7_DAY_RETURN: 31999289.0
The stock shows a consistent positive return trend over the specified periods.
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 14/09/2018 LAST_PRICE: 0.0114814152966404 PX_VOLUME: 25.688 VOLATILITY_10D: 17.88 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0123749106504646 Predicted 2_DAY_RETURN: 4.4674767691167376e-05 Predicted 7_DAY_RETURN: 31999289.0