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

Non, Normawati; Aziz, Norazlin Ab

doi:10.1108/jfra-10-2022-0364

Cited by 4 publications

(1 citation statement)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, only a limited number of studies have focused on textual analysis for fraud prediction in Malaysia. Non and Azis [16] examine whether Malaysian public listed companies expressed any specific sentiments in the management discussion and analysis section of the companies' annual report during the COVID-19 pandemic. The sentiments are extracted by means of computer-automated textual analysis through the linguistic inquiry and word counts and the Loughran-McDonald financial sentiment dictionary.…”

Section: Introductionmentioning

confidence: 99%

Predicting likelihood of fraud among financial distressed firms in Malaysia using textual analysis

Marzuki,

Md Nasir,

Mat Zain

et al. 2024

IJEECS

View full text Add to dashboard Cite

This research paper aims to analyze and predict fraud patterns among failed companies in Malaysia. The approach involves utilizing textual analysis on the management discussion and analysis (MD&A) section within the annual reports. The dataset is subjected to text clustering to group companies based on similar financial characteristics. This clustering process entails several steps, including data conversion, collation, and summarization into a structured format, followed by text pre-processing to cleanse the dataset. Notably, RapidMiner Studio software was utilized to extract data for the study. Subsequently, the documents are clustered using both the K-means and latent dirichlet allocation (LDA) methods. Upon examining a sample of 22 failed companies in the year 2020, the study reveals that financially distressed companies exhibit prominent financial negativity and utilize litigious financial terms within their MD&A sections. These linguistic traits are found to be closely associated with seven distinct characteristics of fraudulent firms. This preliminary findings provide compelling evidence that financial pressure may serve as a triggering factor for fraudulent activities within companies.

show abstract

Section: Introductionmentioning

confidence: 99%

Predicting likelihood of fraud among financial distressed firms in Malaysia using textual analysis

Marzuki,

Md Nasir,

Mat Zain

et al. 2024

IJEECS

View full text Add to dashboard Cite

show abstract

Management’s tone change in MD&A and tax avoidance

Wang,

Wright

2024

JFRA

View full text Add to dashboard Cite

Purpose The purpose of this paper is to explore how variations in management’s tone within management’s discussion and analysis (MD&A) sections of 10-K reports can serve as an indicator of tax avoidance and highlight the complex relationship between such linguistic shifts and the tax avoidance decisions within firms. Design/methodology/approach The paper uses a textual analysis approach to identify linguistic cues in MD&A sections of 10-K filings related to tax avoidance, going beyond traditional quantitative measures. The study uses differences in negative word occurrences in MD&A to measure management’s tone change and examines various measures of tax avoidance. The sample covers the period from 1993 to 2017 and comprises all firms with 10-K filings available on EDGAR, totaling over 30,000 firm-year observations. Findings The findings indicate a complementary relationship between tax avoidance and other drivers of firm performance. When firms have more negative management’s tone, they are less willing to engage in tax avoidance and vice versa. The study’s approach with management’s tone change provides a different and statistically significant improvement in model fit for detecting tax avoidance. Practical implications This paper provides actionable insights for detecting tax avoidance through the analysis of management’s tone in corporate disclosures, offering a new tool for researchers, investors and tax authorities. It highlights the importance of linguistic cues as indicators of tax avoidance behavior, complementing traditional financial metrics. Originality/value The paper contributes to the literature by using management’s tone change as a time-varying factor to explain tax avoidance behavior. It uncovers a larger set of linguistic cues in MD&A that can be used to detect tax avoidance. This research provides a complementary approach to traditional quantitative tax avoidance measures and offers insights into the overall relationship between tax avoidance and firm performance, going beyond one-dimensional measures typically used in prior literature.

show abstract

Dynamic dependency between health-care sector and Islamic industry: before, during and after COVID-19 lockdown evidences

Braiek,

Ben Said

2024

JFRA

View full text Add to dashboard Cite

Purpose This study aims to empirically explore and compare the dynamic dependency between health-care sector and Islamic industries before, during and after the COVID-19 pandemic. Design/methodology/approach Time-varying student-t copula is used for before, during and after COVID-19 periods. The data used are the daily frequency price series of the selected markets from February 2017 to October 2023. Findings Empirical results found strong evidence of significant impact of the COVID-19 pandemic on the dependence structure of the studied indexes: Co-movements between various sectors are certain. The authors assist also in the birth of new dependence structure with the health-care industry in response to the COVID-19 crisis. This reflects the contagion occurrence from the health-care sector to other sectors. Originality/value By specifically examining the Islamic industry, this study sheds light on the resilience, challenges and opportunities within this sector, contributing novel perspectives to the broader discourse on pandemic-related impacts on economies and industries. Also, this paper conducts a comprehensive temporal analysis, examining the dynamics before, during and after the COVID-19 lockdown. Such approach enables an understanding of how the relationship between the health-care sector and the Islamic industry evolves over time, accounting for both short-term disruptions and long-term effects. By considering the pre-pandemic context, the paper adopts a longitudinal perspective, enabling a deeper understanding of how historical trends, structural factors and institutional frameworks shape the interplay between the health-care sector and the Islamic industry.

show abstract

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

Cited by 4 publications

References 67 publications

Predicting likelihood of fraud among financial distressed firms in Malaysia using textual analysis

Predicting likelihood of fraud among financial distressed firms in Malaysia using textual analysis

Management’s tone change in MD&A and tax avoidance

Dynamic dependency between health-care sector and Islamic industry: before, during and after COVID-19 lockdown evidences

Contact Info

Product

Resources

About