{"title":"Twitter作为预测股市走势的工具:一项短窗口事件研究","authors":"Tahir M. Nisar, Man Yeung","doi":"10.1016/j.jfds.2017.11.002","DOIUrl":null,"url":null,"abstract":"<div><p>In order to explore the relationship between politics-related sentiment and FTSE 100 movements, we conducted a short-window event study of a UK based political event. We collected a sample of over 60,000 tweets using 3 key hashtags during the period of 6 days including before, during and after the 2016 local elections. The study involved performing a collection of correlation and regression analyses to compare daily mood with daily changes in the price of the FTSE 100 at the market level. The findings suggest that there is evidence of correlation between the general mood of the public and investment behavior in the short term; however, the relationship is not yet determined as statistically significant. There is also evidence of causation between public sentiment and the stock market movements, in terms of the relationship between MOOD and the daily closing price, and the time lag findings of MOOD and PRICE. Overall, these results show promise for using sentiment analytics on Twitter data for forecasting market movements.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2017.11.002","citationCount":"82","resultStr":"{\"title\":\"Twitter as a tool for forecasting stock market movements: A short-window event study\",\"authors\":\"Tahir M. Nisar, Man Yeung\",\"doi\":\"10.1016/j.jfds.2017.11.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In order to explore the relationship between politics-related sentiment and FTSE 100 movements, we conducted a short-window event study of a UK based political event. We collected a sample of over 60,000 tweets using 3 key hashtags during the period of 6 days including before, during and after the 2016 local elections. The study involved performing a collection of correlation and regression analyses to compare daily mood with daily changes in the price of the FTSE 100 at the market level. The findings suggest that there is evidence of correlation between the general mood of the public and investment behavior in the short term; however, the relationship is not yet determined as statistically significant. There is also evidence of causation between public sentiment and the stock market movements, in terms of the relationship between MOOD and the daily closing price, and the time lag findings of MOOD and PRICE. Overall, these results show promise for using sentiment analytics on Twitter data for forecasting market movements.</p></div>\",\"PeriodicalId\":36340,\"journal\":{\"name\":\"Journal of Finance and Data Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.jfds.2017.11.002\",\"citationCount\":\"82\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Finance and Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405918817300247\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Finance and Data Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405918817300247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
Twitter as a tool for forecasting stock market movements: A short-window event study
In order to explore the relationship between politics-related sentiment and FTSE 100 movements, we conducted a short-window event study of a UK based political event. We collected a sample of over 60,000 tweets using 3 key hashtags during the period of 6 days including before, during and after the 2016 local elections. The study involved performing a collection of correlation and regression analyses to compare daily mood with daily changes in the price of the FTSE 100 at the market level. The findings suggest that there is evidence of correlation between the general mood of the public and investment behavior in the short term; however, the relationship is not yet determined as statistically significant. There is also evidence of causation between public sentiment and the stock market movements, in terms of the relationship between MOOD and the daily closing price, and the time lag findings of MOOD and PRICE. Overall, these results show promise for using sentiment analytics on Twitter data for forecasting market movements.