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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: "Ryanair" STOCK: 24/09/2018 DATE: 13.04 | 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 @Ryanair. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.0337423312883436 2_DAY_RETURN: 0.0337423312883436 3_DAY_RETURN: 0.0368098159509202 7_DAY_RETURN: 1224039.0 | 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: 24/09/2018 LAST_PRICE: 0.0337423312883436 PX_VOLUME: 29.139 VOLATILITY_10D: 29.116 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Ryanair | Predicted 1_DAY_RETURN: 0.0337423312883436
Predicted 2_DAY_RETURN: 0.0337423312883436
Predicted 7_DAY_RETURN: 1224039.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Me_Clay: @Hyundai @WardsAuto I would recommend avoiding all Hyundai models. Our engine failed associated with a recall and they have be…" 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: "Hyundai" STOCK: 24/09/2018 DATE: 129000.0 | 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 @Hyundai. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.003875968992248 7_DAY_RETURN: 765535.0 | 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: 24/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 21.051 VOLATILITY_10D: 22.827 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Hyundai | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 765535.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@ChrisWragge @Starbucks I destroyed my Starbucks Rewards card. @McCafe (Yum!)" 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: 24/09/2018 DATE: 56.69 | 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: 24/09/2018 1_DAY_RETURN: 0.013406244487564 2_DAY_RETURN: 0.013406244487564 3_DAY_RETURN: -0.037396366202152 7_DAY_RETURN: 10616004.0 | 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: 24/09/2018 LAST_PRICE: 0.013406244487564 PX_VOLUME: 16.939 VOLATILITY_10D: 13.355 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks | Predicted 1_DAY_RETURN: 0.013406244487564
Predicted 2_DAY_RETURN: 0.013406244487564
Predicted 7_DAY_RETURN: 10616004.0 |
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 HANA is helping @ElephantsRhinos & People (ERP) preserve the world's ecosystem for future generations. https://t.co/H8kclZW3lr…" 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: 24/09/2018 DATE: 103.6 | 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: 24/09/2018 1_DAY_RETURN: 0.0011583011583012 2_DAY_RETURN: 0.0011583011583012 3_DAY_RETURN: -0.0111969111969111 7_DAY_RETURN: 2084168.0 | 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: 24/09/2018 LAST_PRICE: 0.0011583011583012 PX_VOLUME: 17.276 VOLATILITY_10D: 17.368 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: 0.0011583011583012
Predicted 2_DAY_RETURN: 0.0011583011583012
Predicted 7_DAY_RETURN: 2084168.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @EmilyReviewsCom: With Expedia Add-On Advantage from @Expedia you can relax! You don't have to worry about planning and paying for your…" 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: "Expedia" STOCK: 24/09/2018 DATE: 132.21 | 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 @Expedia. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.011496861054383 2_DAY_RETURN: 0.011496861054383 3_DAY_RETURN: -0.0244308297405643 7_DAY_RETURN: 1935200.0 | 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: 24/09/2018 LAST_PRICE: 0.011496861054383 PX_VOLUME: 17.345 VOLATILITY_10D: 21.355 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Expedia | Predicted 1_DAY_RETURN: 0.011496861054383
Predicted 2_DAY_RETURN: 0.011496861054383
Predicted 7_DAY_RETURN: 1935200.0 |
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: 24/09/2018 DATE: 103.6 | 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: 24/09/2018 1_DAY_RETURN: 0.0011583011583012 2_DAY_RETURN: 0.0011583011583012 3_DAY_RETURN: -0.0111969111969111 7_DAY_RETURN: 2084168.0 | 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: 24/09/2018 LAST_PRICE: 0.0011583011583012 PX_VOLUME: 17.276 VOLATILITY_10D: 17.368 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP | Predicted 1_DAY_RETURN: 0.0011583011583012
Predicted 2_DAY_RETURN: 0.0011583011583012
Predicted 7_DAY_RETURN: 2084168.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@ASOS_HeretoHelp @ASOS Hey 👋🏻 So with the closure of ASOS A-List, does this mean I will no longer get my £5 birthda… https://t.co/dNRqwf1peE
" STOCK: ASOS DATE: 24/09/2018 | 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 -0.3125. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: ASOS 1_DAY_RETURN: 0.0298455056179775 2_DAY_RETURN: 0.0298455056179775 3_DAY_RETURN: 0.0298455056179775 7_DAY_RETURN: 0.0614466292134831 | 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: ASOS LAST_PRICE: 5696.0 PX_VOLUME: 280105.0 VOLATILITY_10D: 37.711 VOLATILITY_30D: 32.087 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: -0.3125 | Predicted 1_DAY_RETURN: 0.0298455056179775
Predicted 2_DAY_RETURN: 0.0298455056179775
Predicted 7_DAY_RETURN: 0.0614466292134831 |
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 Nike Therma Fit Blue Hoodie Youth Size XL https://t.co/IqRrSocpei @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: "Nike" STOCK: 24/09/2018 DATE: 84.27 | 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 0.2 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: 24/09/2018 1_DAY_RETURN: 0.015189272576243 2_DAY_RETURN: 0.015189272576243 3_DAY_RETURN: -0.0119852853921916 7_DAY_RETURN: 8770355.0 | 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: 24/09/2018 LAST_PRICE: 0.015189272576243 PX_VOLUME: 18.296 VOLATILITY_10D: 19.621 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.2 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.015189272576243
Predicted 2_DAY_RETURN: 0.015189272576243
Predicted 7_DAY_RETURN: 8770355.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Just saw this on Amazon: PUMA Adult Suede Classic Shoe by PUMA https://t.co/2NYadsUtY8 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: 24/09/2018 DATE: 1934.36 | 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 0.13333333333333333 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: 24/09/2018 1_DAY_RETURN: -0.0100033085878533 2_DAY_RETURN: -0.0100033085878533 3_DAY_RETURN: -0.0136117372154097 7_DAY_RETURN: 4213728.0 | 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: 24/09/2018 LAST_PRICE: -0.0100033085878533 PX_VOLUME: 24.298 VOLATILITY_10D: 22.63300000000001 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.13333333333333333 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0100033085878533
Predicted 2_DAY_RETURN: -0.0100033085878533
Predicted 7_DAY_RETURN: 4213728.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "IBM talks about the importance of #OpenSource and how it is changing the world around us... @IBM #IBM #technology
https://t.co/tN4np4kvjF
" STOCK: IBM DATE: 24/09/2018 | 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: IBM 1_DAY_RETURN: 0.0087982403519295 2_DAY_RETURN: 0.0087982403519295 3_DAY_RETURN: 0.0087982403519295 7_DAY_RETURN: -0.0139305472238885 | 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: IBM LAST_PRICE: 150.03 PX_VOLUME: 4264984.0 VOLATILITY_10D: 13.023 VOLATILITY_30D: 10.004 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0087982403519295
Predicted 2_DAY_RETURN: 0.0087982403519295
Predicted 7_DAY_RETURN: -0.0139305472238885 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Homegate with Lipton® Iced Tea from Walmart this NFL season. @Walmart #LiptonHomegating #Sponsored… https://t.co/bWz2qEK3q6" 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: "Walmart" STOCK: 24/09/2018 DATE: 94.92 | 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 @Walmart. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.0103244837758112 2_DAY_RETURN: 0.0103244837758112 3_DAY_RETURN: -0.0010535187526338 7_DAY_RETURN: 5336981.0 | 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: 24/09/2018 LAST_PRICE: 0.0103244837758112 PX_VOLUME: 10.044 VOLATILITY_10D: 29.862 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Walmart | Predicted 1_DAY_RETURN: 0.0103244837758112
Predicted 2_DAY_RETURN: 0.0103244837758112
Predicted 7_DAY_RETURN: 5336981.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Just saw this on Amazon: '47 NFL Chicago Bears MVP Adjustable Hat, O... by '47 for $19.99 https://t.co/zeQTUKIRc0 via @amazon
" STOCK: Amazon DATE: 24/09/2018 | 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: Amazon 1_DAY_RETURN: -0.0100033085878533 2_DAY_RETURN: -0.0100033085878533 3_DAY_RETURN: -0.0100033085878533 7_DAY_RETURN: -0.0136117372154097 | 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: Amazon LAST_PRICE: 1934.36 PX_VOLUME: 4213728.0 VOLATILITY_10D: 24.298 VOLATILITY_30D: 22.63300000000001 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0100033085878533
Predicted 2_DAY_RETURN: -0.0100033085878533
Predicted 7_DAY_RETURN: -0.0136117372154097 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @EasypickingsD: Check out Disney Junior Vampirina Bootiful Dress Headband And Wings Childs Size 4-6x https://t.co/h8qdP8ug3g @eBay #Disn…" 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: "Disney" STOCK: 24/09/2018 DATE: 112.77 | 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: 24/09/2018 1_DAY_RETURN: -0.0210162277201382 2_DAY_RETURN: -0.0210162277201382 3_DAY_RETURN: -0.0302385386184268 7_DAY_RETURN: 9232253.0 | 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: 24/09/2018 LAST_PRICE: -0.0210162277201382 PX_VOLUME: 18.479 VOLATILITY_10D: 12.262 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0210162277201382
Predicted 2_DAY_RETURN: -0.0210162277201382
Predicted 7_DAY_RETURN: 9232253.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@tim_cook @salesforce Now problem is this, since Apple introduced $1000 iPhone. Markets without per month deals, it… https://t.co/14Hm14WVbn
" STOCK: Apple DATE: 24/09/2018 | 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: -0.0141763666832736 2_DAY_RETURN: -0.0141763666832736 3_DAY_RETURN: -0.0141763666832736 7_DAY_RETURN: -0.0131799447438742 | 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: 220.79 PX_VOLUME: 27693358.0 VOLATILITY_10D: 25.142 VOLATILITY_30D: 20.148 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0141763666832736
Predicted 2_DAY_RETURN: -0.0141763666832736
Predicted 7_DAY_RETURN: -0.0131799447438742 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @VirginiaKettle1: Check out Disney Store Bing Bong Plush Inside Out Stuffed Animal Pixar Movie Soft Doll https://t.co/sCjDiZxGov @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: "Disney" STOCK: 24/09/2018 DATE: 112.77 | 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 0.1 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: 24/09/2018 1_DAY_RETURN: -0.0210162277201382 2_DAY_RETURN: -0.0210162277201382 3_DAY_RETURN: -0.0302385386184268 7_DAY_RETURN: 9232253.0 | 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: 24/09/2018 LAST_PRICE: -0.0210162277201382 PX_VOLUME: 18.479 VOLATILITY_10D: 12.262 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.1 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0210162277201382
Predicted 2_DAY_RETURN: -0.0210162277201382
Predicted 7_DAY_RETURN: 9232253.0 |
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 01 02 Hyundai Santa FE 5 Speed M/T 39121-38170 Engine Computer ECM ECU #Hyundai https://t.co/alJZTIJ7q7 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: "Hyundai" STOCK: 24/09/2018 DATE: 129000.0 | 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: 24/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.003875968992248 7_DAY_RETURN: 765535.0 | 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: 24/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 21.051 VOLATILITY_10D: 22.827 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 765535.0 |
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 2004-2009 Nissan 350z Convertible Top Lift Motor Left and Right #NissanOEM https://t.co/NG8A8N0LhQ 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: "Nissan" STOCK: 24/09/2018 DATE: 1105.5 | 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 0.2619047619047619 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: 24/09/2018 1_DAY_RETURN: 0.0 2_DAY_RETURN: 0.0 3_DAY_RETURN: -0.0411578471279963 7_DAY_RETURN: 20449900.0 | 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: 24/09/2018 LAST_PRICE: 0.0 PX_VOLUME: 12.567 VOLATILITY_10D: 14.915 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.2619047619047619 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0
Predicted 7_DAY_RETURN: 20449900.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Nike I was trying to buy some Nike dri-fit shirts on @nikestore and nothing was adding to my cart. I signed up for… https://t.co/F9aFUXKV5L" 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: "Nike" STOCK: 24/09/2018 DATE: 84.27 | 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 @Nike. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 24/09/2018 1_DAY_RETURN: 0.015189272576243 2_DAY_RETURN: 0.015189272576243 3_DAY_RETURN: -0.0119852853921916 7_DAY_RETURN: 8770355.0 | 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: 24/09/2018 LAST_PRICE: 0.015189272576243 PX_VOLUME: 18.296 VOLATILITY_10D: 19.621 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Nike | Predicted 1_DAY_RETURN: 0.015189272576243
Predicted 2_DAY_RETURN: 0.015189272576243
Predicted 7_DAY_RETURN: 8770355.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Just saw this on Amazon: Dressystar Women Vintage 1950s Retro Rockabilly ... by Dressystar https://t.co/dDHTvjiB05 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: 24/09/2018 DATE: 1934.36 | 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 @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: 24/09/2018 1_DAY_RETURN: -0.0100033085878533 2_DAY_RETURN: -0.0100033085878533 3_DAY_RETURN: -0.0136117372154097 7_DAY_RETURN: 4213728.0 | 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: 24/09/2018 LAST_PRICE: -0.0100033085878533 PX_VOLUME: 24.298 VOLATILITY_10D: 22.63300000000001 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0100033085878533
Predicted 2_DAY_RETURN: -0.0100033085878533
Predicted 7_DAY_RETURN: 4213728.0 |
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