Do changes in MD&amp;A section tone predict investment behavior?

Berns, John; Bick, Patty; Flugum, Ryan; Houston, Reza

doi:10.1111/fire.12280

Cited by 23 publications

(8 citation statements)

References 95 publications

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“…Similarly, Berns et al (2022) find that an incremental positive tone, expressed from management discussion and analysis, that captures managerial sentiment is associated with subsequent corporate investments. Furtherly, a piece of Yuan et al's (2022) studies show that companies with more positive word usage in the annual report are prone to display higher research and development (R&D) expenditures in the subsequent year.…”

Section: Managerial Sentiment and Corporate Risk-takingmentioning

confidence: 86%

“…Whereas textual-based managerial sentiment is likely to overcome this limitation. As suggested by prior studies, positive and negative semantic words used in corporate disclosure reflect managerial positive bias, such as overconfidence (Liu and Nguyen, 2020), narcissistic trait (Bassyouny et al , 2020) and optimism (Jiang et al , 2019; Berns et al , 2022). Moreover, sentiment as a belief (Hsiao et al , 2014; Hribar et al , 2017) varies with time and events.…”

Section: Introductionmentioning

confidence: 93%

“…Managerial sentiment is a belief that manifests managers’ optimism or pessimism (Hsiao et al , 2014; Jiang et al , 2019; Berns et al , 2022). To some extent, optimism is synonymous with the term overconfidence used by Malmendier and Tate (2005) [see Hsiao et al (2014)].…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

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Managerial sentiment and corporate risk-taking: evidence from Chinese listed companies’ annual reports

Qin,

Cui,

Yan

et al. 2023

MRR

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Purpose This paper aims to examine whether managerial sentiment, extracted from annual reports, is associated with corporate risk-taking in the context of Chinese companies. This study expands the vein of literature on overconfidence theory. Design/methodology/approach By leveraging textual analysis on Chinese listed companies’ annual reports, the authors construct firm-level managerial sentiment during 2007 and 2021 to examine how managerial sentiment influences corporate risk-taking after control for firm characteristics. Corporate risk-taking is denoted by corporate investment engagements: capital expenditures and net fixed asset investment. Findings Results show that incentives for corporate risk-taking are likely to increase with the positive managerial sentiment and decrease with the negative sentiment in companies’ annual reports. Positive managerial sentiment is associated with over-/under-investment and low/high investment efficiency. Further additional tests show that the managerial sentiment effect only holds during low economic uncertain years and samples of private-owned firms. Furthermore, the robust tests indicate that there is no endogenous issue between managerial sentiment and corporate risk-taking. Research limitations/implications Annual report textual-based managerial sentiment may not perfectly reflect managers’ lower frequency sentiment (e.g. weekly, monthly and quarterly sentiment). Future studies could attempt to capture managers’ on-time sentiment by using media sources and corporate disclosures. Practical implications To the best of the authors’ knowledge, this paper is the first research to provide insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach of measuring managerial sentiment might be a solution to monitoring managerial class. Originality/value This paper contributes to the literature on accounting and finance studies, adding another piece of empirical evidence on content analysis by examining a unique language and institutional context (i.e. China). Besides, the paper notes that in line with the English version disclosure, based on Chinese semantic words, managerial sentiment in the Chinese-speaking world has magnitude on corporate decisions. The research provides insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach to measuring managerial sentiment may be a practical solution to monitoring managerial class.

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Section: Managerial Sentiment and Corporate Risk-takingmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 93%

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Managerial sentiment and corporate risk-taking: evidence from Chinese listed companies’ annual reports

Qin,

Cui,

Yan

et al. 2023

MRR

View full text Add to dashboard Cite

show abstract

“…While not addressing the role of information directly, this strand of research centres on the role of the information flows. Similarly, the role of insider trading (Davis et al, 2021) and the tone of information release (Berns et al, 2022) have been given significant attention by researchers. Information flows have remained one of the important aspects of M&A research, and exploration should continue in this direction in the future.…”

Section: Frontier #1: Corporate Culture and Mergersmentioning

confidence: 99%

Mergers and acquisitions research in finance and accounting: Past, present, and future

Kanungo

Jindal

Kumar

et al. 2023

Euro Fin Management

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This study presents an analysis of publication patterns and major themes in research on mergers and acquisitions in finance and accounting. We find that takeovers as mechanisms of governance, drivers of mergers, mechanisms of mergers, bank mergers, cross‐border mergers, shareholder wealth effects of mergers and related events, and the role of financial experts and ownership structure form major themes of research in the finance area, while in accounting area major themes are corporate governance and accounting outcomes, predicting takeovers and their outcomes, valuation, financial reporting and takeover decisions, and financial reporting and performance.

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“…This section includes further explanations of important events in the earning calendar and descriptions of business plans, possible challenges and difficulties in the next year. Existing literature has suggested that when listed companies are trapped in financial trouble in the current year, the appearance of negative words in the MD&A section will increase, along with the level of uncertainty [33,34]. By analyzing the tone of earning calendars some researchers predicted the financial crisis of listed companies and verified the availability of non-standardized financial information in financial crisis recognition [35][36][37][38].…”

Section: The Emotional Tone Of Text and Financial Crisis Early Warningmentioning

confidence: 99%

Textual Emotional Tone and Financial Crisis Identification in Chinese Companies: A Multi-Source Data Analysis Based on Machine Learning

Zhang

Luo

et al. 2022

Applied Sciences

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Nowadays, China is faced with increasing downward pressure on its economy, along with an expanding business risk on listed companies in China. Listed companies, as the solid foundation of the national economy, once they face a financial crisis, will experience hazards from multiple perspectives. Therefore, the construction of an effective financial crisis early warning model can help listed companies predict, control and resolve their risks. Based on textual data, this paper proposes a web crawler and textual analysis, to assess the sentiment and tone of financial news texts and that of the management discussion and analysis (MD&A) section in annual financial reports of listed companies. The emotional tones of the two texts are used as external and internal information sources for listed companies, respectively, to measure whether they can improve the prediction accuracy of a financial crisis early warning model based on traditional financial indicators. By comparing the early warning effects of thirteen machine learning models, this paper finds that financial news, as external texts, can provide more incremental information for prediction models. In contrast, the emotional tone of MD&A, which can be easily modified by the management, will distort predictions. Comparing the early warning effect of machine learning models with different input feature variables, this paper also finds that DBGT, AdaBoost, random forest and Bagging models maintain stable and accurate sample recognition ability. This paper quantifies financial news texts, unraveling implied information hiding behind the surface, to further improve the accuracy of the financial crisis early warning model. Thus, it provides a new research perspective for related research in the field of financial crisis warnings for listed companies.

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Do changes in MD&A section tone predict investment behavior?

Cited by 23 publications

References 95 publications

Managerial sentiment and corporate risk-taking: evidence from Chinese listed companies’ annual reports

Managerial sentiment and corporate risk-taking: evidence from Chinese listed companies’ annual reports

Mergers and acquisitions research in finance and accounting: Past, present, and future

Textual Emotional Tone and Financial Crisis Identification in Chinese Companies: A Multi-Source Data Analysis Based on Machine Learning

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