Public Sentiments & Performance of Industrial Indices: Evidence from Twitter Happiness Index.

AuthorJawed, Mohammad Shameem


The conventional financial theory suggests that the investor demonstrates rational behavior, leaving no room for any irrational behavior in influencing pricing of assets. With the introduction of behavioral finance, the view with regard to investor's behavior has been changing. Behavioral finance scholars defined investor sentiment as "a belief about future cash flows and investment risks that is not justified by the facts at hand" (Baker & Wurgler, 2007: 129). Li et al. (2017:497) referred sentiment as "the extent of investors' expectations diverge from the norm, either manifested as excessive optimism or pessimism". Researchers of behavioral finance have been actively exploring and substituting proxies for investor sentiments that may have an effect on pricing of assets (Baker & Wurgler, 2006; Kim & Kim, 2014; Shen, Liu & Zhang, 2018). Kim & Kim (2014) identified that scholars have used four broad sources of proxies for investor sentiments namely: a) investors survey, b) several market variables, c) news and social media, and d) popular internet message boards.

Extant literature has used social media like Twitter (Shen, Liu & Zhang, 2018; You, Guo & Peng, 2017; Zhang et al., 2018), Facebook (Siganos et al., 2014; Siikanen, 2018), etc. to operationalize investor sentiments and examine its effect on stock markets. Shen, Liu & Zhang (2018) used event study methodology to examine the impact of happiness sentiments extracted from the online social media, Twitter, on 26 international stock market returns. The study identified the skewness of stock returns to be significantly greater in the highest happiness days as compared to lowest happiness days. Examining 10 international stock markets You, Guo & Peng (2017) identified daily happiness as a powerful predicting variable for stock returns. Although analysis using the Granger noncausality test showcased the varying effect in different quantiles but the effect was found to be significant. Zhang et al. (2016) emphasized the crucial role played by the social media in stock markets. Examining 11 international stock markets Zhang et al. (2016) identified positive impact of happiness sentiments on the performance of stock markets. The happiness sentiments in this study were extracted from Twitter and were further grouped into quantiles of least to the most happiness days. Zhang et al. (2017), further extended the studies and identified linear and non-linear relationship among different international markets. Yet another study conducted by Li et al. (2017) identified bi-directional relationship between daily happiness sentiment and stocks return, excess trading volume and range-based volatility. Unlike other studies on investor sentiment analysis, the Li et al. (2017) study examined the local investor sentiment on the international stock market.

Based on the extant literature we found that very few studies looked at the emerging market context. Moreover, none have explored the causal relationship of various sectoral stock market indices with Happiness Index, as they may show a very different behavior than market in general--depending upon their nature of business and hence could give new evidences and cues for the investors who take market positions...

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