To Catch a Thief: Can Forensic Accounting Help Predict Stock Returns?

Beneish, Messod Daniel; Nichols, Craig; Lee, Charles M.C.

doi:10.2139/ssrn.1903593

Cited by 4 publications

(7 citation statements)

References 15 publications

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“…Since some companies were engaged in earnings manipulation on the basis average percentage, the Null Hypothesis that no listed companies in Ghana engage in earnings manipulation, H 01, is rejected in favor of the Alternative Hypothesis that some listed companies in Ghana engage in earnings manipulation, H A1 . This finding supports the assertion that M-score could accurately identify companies that have manipulated their earning and those that have not engaged in such practice (Beneish, 1999;Beneish et al, 2011;Goel, 2014;Omar et al, 2014). This finding is also consistent with the finding of Dichev et al (2016) which indicates that some companies deliberately manipulate their earnings even when applying the GAPP.…”

Section: Discussion Of the Resultssupporting

confidence: 86%

“…On the average, 26.2% of the companies assessed manipulated their earnings between 2011 and 2016. The rejection of the Null Hypothesis, H 01 , supports the general views of Beneish et al (2011), Beneish (1999), Goel (2014) and Omar et al (2014) that confirm the effectiveness of M-score in detecting earnings manipulation. The finding also suggests that there are a number of companies who have not been detected to have manipulated their earnings by the various stakeholders such as regulatory bodies and auditors and yet have engaged or are engaging in such practice.…”

Section: Resultssupporting

confidence: 57%

“…Research on the application of Beneish M-score in detention of earnings manipulation has been widely conducted in different geographical areas around the globe (Beneish et al, 2013;Beneish, Lee, & Nichols, 2011;Nwoye et al, 2013;Repousis, 2016). These researchers have either tested the effectiveness of the Beneish M-score model in detecting earnings manipulation or used the model to determine an existence and a degree of earnings manipulation (Beneish et al, 2013;Beneish, Lee, & Nichols, 2011;Nwoye et al, 2013). Beneish et al (2011) found new evidence on the ability of forensic accounting to effectively detect corporate fraud and predict stock returns.…”

Section: Degeorge Et Al (As Cited Inmentioning

confidence: 99%

“…These researchers have either tested the effectiveness of the Beneish M-score model in detecting earnings manipulation or used the model to determine an existence and a degree of earnings manipulation (Beneish et al, 2013;Beneish, Lee, & Nichols, 2011;Nwoye et al, 2013). Beneish et al (2011) found new evidence on the ability of forensic accounting to effectively detect corporate fraud and predict stock returns. Using Beneish M-score model, Beneish et al (2011) found that 12 out of 17 non-manipulators between 1998 and 2002 were detected by the model, indicating 71% success rate.…”

Section: Degeorge Et Al (As Cited Inmentioning

confidence: 99%

“…Beneish et al (2011) found new evidence on the ability of forensic accounting to effectively detect corporate fraud and predict stock returns. Using Beneish M-score model, Beneish et al (2011) found that 12 out of 17 non-manipulators between 1998 and 2002 were detected by the model, indicating 71% success rate. They further found that the Beneish M-score model has a strong ability in predicting stock return out-of-sample.…”

Section: Degeorge Et Al (As Cited Inmentioning

confidence: 99%

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Investigating Financial Statement Fraud in Ghana Using Beneish M-Score: A Case of Listed Companies on the Ghana Stock Exchange

Adu-Gyamfi¹

2020

IFB

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This quantitative research was conducted to detect the possibility of earnings manipulation by listed companies on the Ghana Stock Exchange, determine the relationship between company size and earnings manipulation and find out the existence of a correlation between share price and earnings manipulation. Using 22 companies out of a total of 41 listed companies, financial data gathered from published financial statements on the companies’ websites, Ghana Stock Exchange website and Annual Report Ghana website were examined from 2011 to 2016. Applying Beneish M-score model for the period 2011-2016, it was found that 26.2% of the sample size on the average were involved in creative accounting. The study also found that 28.4% of the small companies on the average were involved in earnings manipulation during the period 2011-2016 as compared to 25.4% of the big companies. However, the Mann-Whitney U test conducted revealed that there is no statistically significant difference between the level of earnings manipulation and company size. Spearman’s correlation analysis was conducted, firstly, on the entire sample and separately on the small and big companies. The results of the analysis showed that earnings manipulation and share price, statistically, were not significantly correlated. The quantitative research provides an insight into the level of earnings management amongst listed companies in Ghana and the appropriateness of the M-score model in detecting earnings manipulation. The evidence of incidence of creative accounting amongst the sampled companies is an indication of the need for more stringent measures to curb such practice to ensure the stability of the Ghanaian stock market and protect investor interest.

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Section: Discussion Of the Resultssupporting

confidence: 86%

Section: Resultssupporting

confidence: 57%

Section: Degeorge Et Al (As Cited Inmentioning

confidence: 99%

Section: Degeorge Et Al (As Cited Inmentioning

confidence: 99%

Section: Degeorge Et Al (As Cited Inmentioning

confidence: 99%

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Investigating Financial Statement Fraud in Ghana Using Beneish M-Score: A Case of Listed Companies on the Ghana Stock Exchange

Adu-Gyamfi¹

2020

IFB

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Using Beneish model to detect corporate financial statement fraud in Greece

Repousis

2016

JFC

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Purpose This paper aims to investigate empirically the eight-variables Beneish M-model to identify occurrence of financial statement fraud or tendency to engage in earning manipulation. Design/methodology/approach A data set of 25,468 companies (Société Anonyme and Limited Liability Companies) in Greece was analyzed during two-year period of 2011-2012. Financial statements of banks are excluded. Findings The results showed that 8,486 companies or 33 per cent of the whole sample has a greater than −2.2 score, which is a signal that companies are likely to be manipulators. Also, for manipulators, results using F-distribution showed that days sales in receivable index (DSRI), asset quality index (AQI), depreciation index, selling, general and administrative expenses index (SGAI), total accruals to total assets index and leverage index (LVGI) are significant at 99 per cent confidence level in its effect on Beneish M-score. Also, there is a significant relationship between earning management, as expressed by Beneish M-score and each one of variables, DSRI, AQI, gross margin index, sales growth index, SGAI and LVGI. Most of all, DSRI explains 95.92 per cent of the variation in Beneish M-score in statistical terms. Practical implications Results are important for banking system, because financial statements information influence credit decisions of banks. Debt agreements include terms based upon accounting numbers. Also, using Beneish Model, it is a cheap and easy way for examiners of possible fraudulent activity. Originality/value To the best of the author’s knowledge, there is a great lack of research in Greece, using Beneish model. There is only one more study using the Beneish model, examining only a few companies listed in Athens Stock Exchange during 1999-2000. Findings have also important implications not only for banks but also for users of Greek financial statement accounts, especially to investors, auditors, regulators, to taxation and other state authorities.

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Запобігання Фальсифікації Інформації Для Аналітичного Забезпечення Управління Підприємством

Проскура,

Лизанець,

Гонак

2024

Економіка та суспільство

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У статті визначено необхідність та важливість створення на підприємстві системи превентивного захисту і перевірки достовірності аналітичної інформації яка застосовується для його роботи. Звернуто увагу на те, що джерела інформаційного забезпечення управління підприємством можуть бути не тільки внутрішні, але і зовнішні. Наголошено на тому, що існують три групи факторів, які визначають можливість і мотивацію фальсифікації фінансової звітності, а саме: можливості, мотив, та раціоналізація - так званий «трикутник шахрайства». Наведено перелік превентивних заходів щодо запобігання фальсифікації, зокрема: комплаєнс контроль, внутрішній аудит та дотримання корпоративних етичних норм, а також відмінності між ними. Підкреслено важливість оцінки достовірності фінансової звітності як для внутрішніх, так і зовнішніх стейкхолдерів. Наведено перелік моделей, що застосовуються для визначення рівня ризику транспарентності та фальсифікації фінансової звітності, встановлено та обґрунтовано, шо найбільш вдалою серед перерахованих моделей є модель М.Д. Беніша. Розкрито суть моделі М.Д. Беніша, наведено перелік показників, що застосовуються у моделі для розрахунку інтегрального показника М-Score. Наголошено, що попри ефективність моделі М.Д. Беніша, за її допомогою можна виявити факти шахрайства лише у 76 % випадків, тому наведено показники, аналіз яких дасть додаткову інформацію про наявність маніпуляцій зі звітністю.

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To Catch a Thief: Can Forensic Accounting Help Predict Stock Returns?

Cited by 4 publications

References 15 publications

Investigating Financial Statement Fraud in Ghana Using Beneish M-Score: A Case of Listed Companies on the Ghana Stock Exchange

Investigating Financial Statement Fraud in Ghana Using Beneish M-Score: A Case of Listed Companies on the Ghana Stock Exchange

Using Beneish model to detect corporate financial statement fraud in Greece

Запобігання Фальсифікації Інформації Для Аналітичного Забезпечення Управління Підприємством

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