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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 25.688 VOLATILITY_10D: 17.88 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0114814152966404
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: "RT @Jessiedoth: @Shell That makes your contributions to a mass extinction of life on the planet all worth it. Thank you Shell." 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: "Shell" STOCK: 16/09/2018 DATE: 2469.5 | 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 0.3 and the TextBlob polarity score is @Shell. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: -0.0034419923061348 3_DAY_RETURN: -0.0105284470540595 7_DAY_RETURN: 3351052.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 16.342 VOLATILITY_10D: 17.352999999999998 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.3 TEXTBLOB_POLARITY: @Shell | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: -0.0034419923061348
Predicted 7_DAY_RETURN: 3351052.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Apple I have everything Apple so do my family, but the time has come. I am going to go from IPhone X to Samsung no… https://t.co/lpRm5bYkDk
" STOCK: Apple DATE: 16/09/2018 | 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: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0114814152966404 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: 0.0
Predicted 2_DAY_RETURN: 0.0
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: "@temodent @nicholasibekwe @HSBC You can use Google without having education.
Common sense?
" STOCK: Google DATE: 16/09/2018 | 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: Google 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0035314691251125 7_DAY_RETURN: -0.0003310752304793 | 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: Google LAST_PRICE: 1177.98 PX_VOLUME: 1208767.0 VOLATILITY_10D: 16.637 VOLATILITY_30D: 16.840999999999998 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0003310752304793 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Starbucks @Starbucks at the Hay Building is throwing a bday party for one of their regulars and I. LOVE. IT." 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: 16/09/2018 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 0.0 and the TextBlob polarity score is @Starbucks. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0025570776255707 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 7.891 VOLATILITY_10D: 11.511 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0025570776255707
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: "@McDonalds Is this why America is so obese. Next it will be the 1 2 3 cent menu. With and extra chance of heat attack." 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: "Next" STOCK: 16/09/2018 DATE: 5350.0 | 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 @McDonalds. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0082242990654205 3_DAY_RETURN: 0.0183177570093457 7_DAY_RETURN: 268593.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 14.282 VOLATILITY_10D: 15.157 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @McDonalds | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0082242990654205
Predicted 7_DAY_RETURN: 268593.0 |
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 HP Pavilion w185e 18.5" LCD Monitor With Built-In Speakers!!! #HP https://t.co/7nI6HBrLwP via @eBay
" STOCK: HP DATE: 16/09/2018 | 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: HP 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0011980830670925 7_DAY_RETURN: -0.0131789137380191 | 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: HP LAST_PRICE: 25.04 PX_VOLUME: 5509826.0 VOLATILITY_10D: 10.452 VOLATILITY_30D: 15.356 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0131789137380191 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Techmeme @asymco Google Pixel Fraud might happen again with the launch of Pixel 3 on 9 October 2018
@Google is Ki… https://t.co/c9n4yzRAP4
" STOCK: Google DATE: 16/09/2018 | 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: Google 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0035314691251125 7_DAY_RETURN: -0.0003310752304793 | 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: Google LAST_PRICE: 1177.98 PX_VOLUME: 1208767.0 VOLATILITY_10D: 16.637 VOLATILITY_30D: 16.840999999999998 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0003310752304793 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @mdubowitz: Boeing cargo plane loaded with weapons. Yet more evidence of how Islamic Republic of Iran would use @Boeing @Airbus @Bombard…" 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: "Boeing" STOCK: 16/09/2018 DATE: 359.8 | 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 @Boeing. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: -0.0120622568093386 3_DAY_RETURN: -0.0292384658143414 7_DAY_RETURN: 2835757.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 20.806 VOLATILITY_10D: 22.042 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Boeing | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: -0.0120622568093386
Predicted 7_DAY_RETURN: 2835757.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @i4unews: The Best iPhone Xs Deals For Sunday: Walmart, Sam's Club, T-Mobile #iPhoneXs #iPhoneXsMax #Save$100 @Walmart @Samsclub https:/…
" STOCK: Walmart DATE: 16/09/2018 | 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 1.0. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Walmart 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0056031292948514 7_DAY_RETURN: 0.0131092081615392 | 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: Walmart LAST_PRICE: 94.59 PX_VOLUME: 6319383.0 VOLATILITY_10D: 12.923 VOLATILITY_30D: 30.137 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 1.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 0.0131092081615392 |
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: TODAY: At 9am NY/ 2pm UK/ 4pm Palestine, tweet @HSBC & @HSBC_UK to #StopArmingIsrael. HSBC must divest from Elbit Systems,…
" STOCK: HSBC DATE: 16/09/2018 | 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: HSBC 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0033414337788577 7_DAY_RETURN: -0.0050121506682866 | 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: HSBC LAST_PRICE: 658.4 PX_VOLUME: 18315618.0 VOLATILITY_10D: 11.587 VOLATILITY_30D: 12.026 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0050121506682866 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @mdubowitz: Boeing cargo plane loaded with weapons. Yet more evidence of how Islamic Republic of Iran would use @Boeing @Airbus @Bombard…" 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: "Boeing" STOCK: 16/09/2018 DATE: 359.8 | 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 @Boeing. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: -0.0120622568093386 3_DAY_RETURN: -0.0292384658143414 7_DAY_RETURN: 2835757.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 20.806 VOLATILITY_10D: 22.042 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Boeing | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: -0.0120622568093386
Predicted 7_DAY_RETURN: 2835757.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @SAP: SAP technology allows @elephantsrhinos (ERP) to monitor elephants and rhinos with drones and sensors to reduce poaching. https://t…" 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: 16/09/2018 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: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: -0.006713984270094 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 22.385 VOLATILITY_10D: 16.511 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: -0.006713984270094
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: "RT @intel: Intel and Smithsonian @AmericanArt Museum partnered with VR specialists to create an exhibit free from the constraints of time a…" 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: "Intel" STOCK: 16/09/2018 DATE: 45.54 | 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 @intel. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0006587615283267 3_DAY_RETURN: 0.0199824330259113 7_DAY_RETURN: 22998666.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 19.793 VOLATILITY_10D: 19.265 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.4 TEXTBLOB_POLARITY: @intel | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0006587615283267
Predicted 7_DAY_RETURN: 22998666.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@TMobile @TMobileHelp hello, what is the process for transferring my TMO data plan from old to new Apple Watch?
P… https://t.co/dL1TPfSk63
" STOCK: Apple DATE: 16/09/2018 | 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 0.11818181818181818. |
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: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0114814152966404 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: 0.11818181818181818 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
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 @blackrock: On 9/25, tune in as BlackRock bond experts discuss what the changing fixed income landscape could mean for your practice. ht…
" STOCK: BlackRock DATE: 16/09/2018 | 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 -0.10625. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: BlackRock 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0148720749485358 7_DAY_RETURN: -0.0097046590765869 | 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: BlackRock LAST_PRICE: 476.06 PX_VOLUME: 416701.0 VOLATILITY_10D: 13.186 VOLATILITY_30D: 14.525 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -0.10625 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0097046590765869 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @blackrock: On 9/25, tune in as BlackRock bond experts discuss what the changing fixed income landscape could mean for your practice. ht…
" STOCK: BlackRock DATE: 16/09/2018 | 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 -0.10625. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: BlackRock 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0148720749485358 7_DAY_RETURN: -0.0097046590765869 | 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: BlackRock LAST_PRICE: 476.06 PX_VOLUME: 416701.0 VOLATILITY_10D: 13.186 VOLATILITY_30D: 14.525 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -0.10625 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0097046590765869 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @IanS_devotee: Win a chance to visit Ian Somerhalder on the set of his upcoming Netflix series V Wars. @iansomerhalder @netflix #vwars 😍…" 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: "Netflix" STOCK: 16/09/2018 DATE: 364.56 | 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 @netflix. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0098474873820495 3_DAY_RETURN: -0.0435593592275619 7_DAY_RETURN: 4756426.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 46.007 VOLATILITY_10D: 37.876 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.8 TEXTBLOB_POLARITY: @netflix | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0098474873820495
Predicted 7_DAY_RETURN: 4756426.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @babypeashop: The countdown is on! Find out more @ASOS #OutletFlashSale – http://t.co/3ZEBOUW - RT to win £250 ASOS vouchers" 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: "ASOS" STOCK: 16/09/2018 DATE: 5986.0 | 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 @ASOS. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: -0.0113598396257935 3_DAY_RETURN: -0.0223855663214166 7_DAY_RETURN: 159724.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 28.622 VOLATILITY_10D: 26.295 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @ASOS | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: -0.0113598396257935
Predicted 7_DAY_RETURN: 159724.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @candacecbure: Netflix knows how to party! @andreabarber @johnstamos @caitlinskybound @netflix #Emmys2018 #FullerHouse https://t.co/9fij…" 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: "Netflix" STOCK: 16/09/2018 DATE: 364.56 | 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 @netflix. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0098474873820495 3_DAY_RETURN: -0.0435593592275619 7_DAY_RETURN: 4756426.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 46.007 VOLATILITY_10D: 37.876 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @netflix | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0098474873820495
Predicted 7_DAY_RETURN: 4756426.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @urfavhoodhomie: preparation... @ChampionsLeague @Heineken @Heineken_NG
Kidnapping Mr. Heineken
drink responsibly 🔞. https://t.co/H5e…
" STOCK: Heineken DATE: 16/09/2018 | 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 0.2. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Heineken 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0060591371788657 7_DAY_RETURN: 0.0101793504604944 | 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: Heineken LAST_PRICE: 82.52 PX_VOLUME: 569135.0 VOLATILITY_10D: 17.53 VOLATILITY_30D: 11.573 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.2 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 0.0101793504604944 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @ebayflipper: Check out IBM Lenovo Thinkpad 20V AC Adapter 92P1160 #Lenovo https://t.co/iwAfsDX1bY 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: "IBM" STOCK: 16/09/2018 DATE: 148.33 | 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: 16/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0041798692105438 3_DAY_RETURN: -0.0194161666554306 7_DAY_RETURN: 3452144.0 | 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: 16/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 11.606 VOLATILITY_10D: 11.390999999999998 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0041798692105438
Predicted 7_DAY_RETURN: 3452144.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@techywife @Tesco This is silly, Ruislip Manor Tesco is on the site of an old BMW garage and clearly has a car park… https://t.co/kOa3IHEdAQ
" STOCK: BMW DATE: 16/09/2018 | 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 -0.1. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: BMW 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: 0.0023038680732387 7_DAY_RETURN: -0.0195222505153389 | 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: BMW LAST_PRICE: 82.47 PX_VOLUME: 1400162.0 VOLATILITY_10D: 13.991 VOLATILITY_30D: 15.594 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -0.1 | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: -0.0195222505153389 |
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