{"title":"推文分析用于股市走势的方向性预测:短窗口事件研究","authors":"Tanuj Nandan, Manas Agrawal, Rajat Kumar Soni","doi":"10.1504/ijie.2023.133830","DOIUrl":null,"url":null,"abstract":"This study examines the influence of tweets on the prediction of the Nifty 50 index movement in association with the COVID-19 vaccination news break event in India. A 15-day short window analysis has conducted using 27,175 tweets with 14 hashtags from the first date of the COVID-19 vaccination news break in India on December 2020. The investigation explores the impact of sentiment, mood and volume of tweets on Nifty 50 index movement through regression analysis. We find positive sentiment more significantly influences the market movement than negative sentiment associated with any optimistic event, and mood is the most efficient predictor of daily market movement. However, volumes of tweets have not significantly supported our predictor model used in this study. Therefore, this study provides the behavioural impact of Twitter sentiment analysis on stock market movement only associated with an optimistic event, which can also be considered a gap for future exploration.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tweets analytics for directional prediction of stock market movement: a short window event study\",\"authors\":\"Tanuj Nandan, Manas Agrawal, Rajat Kumar Soni\",\"doi\":\"10.1504/ijie.2023.133830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examines the influence of tweets on the prediction of the Nifty 50 index movement in association with the COVID-19 vaccination news break event in India. A 15-day short window analysis has conducted using 27,175 tweets with 14 hashtags from the first date of the COVID-19 vaccination news break in India on December 2020. The investigation explores the impact of sentiment, mood and volume of tweets on Nifty 50 index movement through regression analysis. We find positive sentiment more significantly influences the market movement than negative sentiment associated with any optimistic event, and mood is the most efficient predictor of daily market movement. However, volumes of tweets have not significantly supported our predictor model used in this study. Therefore, this study provides the behavioural impact of Twitter sentiment analysis on stock market movement only associated with an optimistic event, which can also be considered a gap for future exploration.\",\"PeriodicalId\":39490,\"journal\":{\"name\":\"International Journal of Intelligent Enterprise\",\"volume\":\"83 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Intelligent Enterprise\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijie.2023.133830\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Enterprise","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijie.2023.133830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
Tweets analytics for directional prediction of stock market movement: a short window event study
This study examines the influence of tweets on the prediction of the Nifty 50 index movement in association with the COVID-19 vaccination news break event in India. A 15-day short window analysis has conducted using 27,175 tweets with 14 hashtags from the first date of the COVID-19 vaccination news break in India on December 2020. The investigation explores the impact of sentiment, mood and volume of tweets on Nifty 50 index movement through regression analysis. We find positive sentiment more significantly influences the market movement than negative sentiment associated with any optimistic event, and mood is the most efficient predictor of daily market movement. However, volumes of tweets have not significantly supported our predictor model used in this study. Therefore, this study provides the behavioural impact of Twitter sentiment analysis on stock market movement only associated with an optimistic event, which can also be considered a gap for future exploration.
期刊介绍:
Major catalysts such as deregulation, global competition, technological breakthroughs, changing customer expectations, structural changes, excess capacity, environmental concerns and less protectionism, among others, are reshaping the landscape of corporations worldwide. The assumptions about predictability, stability, and clear boundaries are becoming less valid as two factors, by no means exhaustive, have a clear impact on the nature of the competitive space and are changing the sources of competitive advantage of firms and industries in new and unpredictable ways: agents with knowledge and interactions.