An exploratory study that uses textual analysis to examine the financial reporting sentiments during the COVID-19 pandemic

Normawati Non and Norazlin Ab Aziz

Journal of Financial Reporting and Accounting, 2023, vol. 21, issue 4, 895-915

Abstract: Purpose - This paper aims to examine if Malaysian public listed companies have expressed any specific sentiment(s) when publishing their financial performance during the COVID-19 pandemic. Design/methodology/approach - The disclosed sentiments contained in the management discussion and analysis section of the companies’ annual reports were extracted by means of computer-automated textual analysis through the linguistic inquiry and word counts and the Loughran–McDonald Financial Sentiment Dictionary. Next, a correlation analysis was conducted. Finally, a qualitative content analysis (QCA) was conducted to confirm these sentiments. Findings - The analysis shows that companies adopted various tones of sentiments when communicating with their stakeholders. Most companies used negative sentiments to voice their concerns about how the COVID-19 pandemic has impacted upon their business operations. Only a few companies reflected positive sentiments, whilst those that experienced operating losses also expressed uncertainty. Research limitations/implications - This study may assist either the regulators or accounting bodies to introduce a reporting framework that public companies can adopt during natural hazards. It also provides useful insights to (potential) investors to enable them to better understand the business landscape. For future research, the same study could be conducted on more countries so that their experiences can be used to better understand the business phenomenon from a global perspective. Originality/value - This study is one of few studies to adopt automated textual analysis and QCA to examine the exhibited sentiments when public companies reported their financial performance during the COVID-19 pandemic.

Keywords: Content analysis; Narrative disclosure; Financial performance; Textual analysis; COVID-19 pandemic (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jfrapp:jfra-10-2022-0364

DOI: 10.1108/JFRA-10-2022-0364

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