Performance of the Indian Stock Market and Sentiment Among Investors on Twitter

This study examines the association between investor sentiment on Twitter and the performance of the Indian stock market. Utilizing daily time series data spanning eight years, from January 1, 2015, to December 31, 2022, the research employs Descriptive Statistics, Correlation Matrix, VAR models, Granger-causality tests, and Quantile Regression Analysis to explore these relationships. The analysis reveals that while Twitter sentiment correlates with certain stock market variables, there is no significant autoregressive or causal relationship between sentiment and market performance. Specifically, the VAR models indicate that Twitter sentiment does not influence stock returns or trading volumes dynamically. Furthermore, Granger-causality tests show no causal link between Twitter sentiment and stock returns or volumes. However, the Quantile Regression Analysis uncovers significant relationships between Twitter sentiment and stock returns at various quantiles, suggesting that sentiment provides valuable insights into stock returns. These findings hold practical implications for researchers, investors, and market participants, highlighting the role of social media sentiment in understanding market dynamics. The study contributes to financial literature by demonstrating that while there is a correlation between Twitter sentiment and market performance, there is no dynamic or causal relationship, thereby providing a nuanced understanding of investor sentiment's impact on the Indian stock market.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-20
DOI
https://doi.org/10.52783/jisem.v10i3.5768
Primary Topic
Stock Market Forecasting Methods
Type
article
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article

Performance of the Indian Stock Market and Sentiment Among Investors on Twitter

Vadivel Thanikachalam
Journal of Information Systems Engineering & Management
Stock Market Forecasting Methods
article

Performance of the Indian Stock Market and Sentiment Among Investors on Twitter

Vadivel Thanikachalam
article en

Abstract

This study examines the association between investor sentiment on Twitter and the performance of the Indian stock market. Utilizing daily time series data spanning eight years, from January 1, 2015, to December 31, 2022, the research employs Descriptive Statistics, Correlation Matrix, VAR models, Granger-causality tests, and Quantile Regression Analysis to explore these relationships. The analysis reveals that while Twitter sentiment correlates with certain stock market variables, there is no significant autoregressive or causal relationship between sentiment and market performance. Specifically, the VAR models indicate that Twitter sentiment does not influence stock returns or trading volumes dynamically. Furthermore, Granger-causality tests show no causal link between Twitter sentiment and stock returns or volumes. However, the Quantile Regression Analysis uncovers significant relationships between Twitter sentiment and stock returns at various quantiles, suggesting that sentiment provides valuable insights into stock returns. These findings hold practical implications for researchers, investors, and market participants, highlighting the role of social media sentiment in understanding market dynamics. The study contributes to financial literature by demonstrating that while there is a correlation between Twitter sentiment and market performance, there is no dynamic or causal relationship, thereby providing a nuanced understanding of investor sentiment's impact on the Indian stock market.

Journal of Information Systems Engineering & ManagementVol. 10(3)
Openalex Percentile: Top 92%
Stock Market Forecasting Methods
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