Author(s) :

Amit Kumar Singh, Priya Harjai.

Volume/Issue :

Abstract :

This case tries to analyse and uncover the sentiment expressed in a report published dated 24 January 2023 by Hindenburg Research on Adani Enterprises. The study emphasizes the significance of qualitative data (textual data) by employing the novel empirical textual sentiment analysis technique to quantify the information present in a voluminous report with the intention of studying its impact on Adani Enterprises stock prices. It introduces a novel dimension of examining a qualitative aspect of the report rather than the conventional event study approach with numerical figures. The case elucidates that the negative sentiment expressed via the research report resulted in a decrease in stock prices. It portrays the power of qualitative data to change the perceptions and beliefs of investors. However, the more pronounced effect of a decrease in the stock price over days shows that the information embedded in the report took time to be incorporated into the stock price which pertains to the inefficiency of the semi-strong form of market efficiency

No. of Downloads :

26

KEYWORDS:

Behavioral Finance, Textual Sentiment Analysis, Stock Market, Hindenburg research report, Adani Enterprises

INTRODUCTION & OBJECTIVES:

Investors vigorously seek information available in the public domain regarding the companies. Textual information which is hard to quantify is quintessential to the overall financial market condition, industries, and firms (Kearney & Liu, 2014). Researchers over the decades have intensified their efforts to examine the effect of sentiment embedded in textual information on stock price returns. One of the ways to study sentiment is through textual sentiment analysis. Textual Analysis can be perceived as a component of qualitative analysis and can be defined as an approach to measure qualitative information systematically into quantitative measures. It is used to infer the sentiment of the context. Kearney and Liu (2014) suggested three sources of sentiment analysis in finance where major work by academicians has been done: Corporation public disclosure (includes official releases done internally), Media (news stories, in -depth commentaries, or analyst reports), and Internet posting. This case emphasized somewh ere between media-based information and corporate disclosure (Kearney &Liu, 2014). The hard-to-quantify information content from a reputable and authentic source like a research firm can change the perception and behaviour of individual investors. The arrival of new information can potentially change investors' beliefs (Huberman & Regev, 2001). There are myriads of evidence that elucidates that qualitative information can shape the perception and behaviour of individual investors (Bajo & Raimondo, 2017; Tetlock, 2007; Tetlock et al., 2008). In emerging countries like India, various studies have been conducted using event study methodology to analyse the impact of particular events such as announcements of scams, fraud, earnings, etc on the stock price (Ahmad et al., 2022; Mallesha & Archana, 2023). Recently Mallesha and Archana (2023) investigated the impact of the Hindenburg report on the Adani Group’s stock prices using event study methodology. This case broadens the scope with a distinctive method, notably the textual sentiment analysis approach to analyse and interpret the text (positive sentiment or negative sentiment) of the 106-page Hindenburg report and subsequently its impact on the stock price. The event study focuses on the financial data (quantitative) while sentiment analysis deals with the textual information (qualitative data). This case tries to answer: How a report published by Hindenburg Research on January 24, 2023, impact the belief and perception of investors and hence the share price of Adani enterprises afterward? Moreover, whether the impact on share price was immediate or it took time to be incorporated into the Adani enterprise share price. The report consists of 106 pages, which is voluminous, and investors may face difficulty autonomously understanding complex information stated in the report. Hence, we have used Corporate Governance Insight, Volume: 5, Number:2, December 2023, eISSN: 2582-0834 14 Hindenburg's published report as a research object and deployed textual sentiment analysis to measure abundant information in the report using a pysentiment 2 package on Python software

DOI:

10.58426/cgi.v5.i2.2023.12-22