Beneish M-score

The Beneish model is a statistical model that uses financial ratios calculated with accounting data of a specific company in order to check if it is likely (high probability) that the reported earnings of the company have been manipulated.

How to calculate

The Beneish M-score is calculated using 8 variables (financial ratios):^[1]^[2]

Days Sales in Receivables Index

(DSRI) DSRI = (Net Receivables_t / Sales_t) / (Net Receivables_t-1 / Sales_t-1)

Gross Margin Index (GMI)

GMI = [(Sales_t-1 - COGS_t-1) / Sales_t-1] / [(Sales_t - COGS_t) / Sales_t]

Asset Quality Index (AQI)

AQI = [1 - (Current Assets_t + PP&E_t + Securities_t) / Total Assets_t] / [1 - ((Current Assets_t-1 + PP&E_t-1 + Securities_t-1) / Total Assets_t-1)]

Sales Growth Index (SGI)

SGI = Sales_t / Sales_t-1

Depreciation Index (DEPI)

DEPI = (Depreciation_t-1/ (PP&E_t-1 + Depreciation_t-1)) / (Depreciation_t / (PP&E_t + Depreciation_t))

Sales General and Administrative Expenses Index (SGAI)

SGAI = (SG&A Expense_t / Sales_t) / (SG&A Expense_t-1 / Sales_t-1)

Leverage Index (LVGI)

LVGI = [(Current Liabilities_t + Total Long Term Debt_t) / Total Assets_t] / [(Current Liabilities_t-1 + Total Long Term Debt_t-1) / Total Assets_t-1]

Total Accruals to Total Assets (TATA)

TATA = (Income from Continuing Operations_t - Cash Flows from Operations_t) / Total Assets_t

The formula to calculate the M-score is:^[1]

M-score = −4.84 + 0.92 × DSRI + 0.528 × GMI + 0.404 × AQI + 0.892 × SGI + 0.115 × DEPI −0.172 × SGAI + 4.679 × TATA − 0.327 × LVGI

How to interpret

The threshold value is -1.78 for the model whose coefficients are reported above. (see Beneish 1999, Beneish, Lee, and Nichols 2013, and Beneish and Vorst 2020).

If M-score is less than -1.78, the company is unlikely to be a manipulator. For example, an M-score value of -2.50 suggests a low likelihood of manipulation.
If M-score is greater than −1.78, the company is likely to be a manipulator. For example, an M-score value of -1.50 suggests a high likelihood of manipulation.

Aggregate recession predictor

A 2023 research paper will use an aggregate score of many companies to predict recessions. It finds that the score in early 2023 is the highest in some 40 years.^[3]^[4]

Important notices

Beneish M-score is a probabilistic model, so it cannot detect companies that manipulate their earnings with 100% accuracy.
Financial institutions were excluded from the sample in Beneish paper when calculating M-score since these institutions make money through different routes. Sales and receivables which are two main ingredients that go into the Beneish formula are not used when analyzing a financial institution.

Example of successful application

Enron Corporation was correctly identified 1998 as an earnings manipulator by students from Cornell University using M-score Noticeably, Wall Street financial analysts were still recommending to buy Enron shares at that point in time..^[5]^[6]

References

^ ^a ^b Messod D. Beneish. "The Detection of Earnings Manipulation". Scribd. Retrieved 2017-01-08.
^ "Beneish M Score Definition". ycharts.com. Retrieved 2017-01-08.
^ Beneish, Messod D.; Farber, David B.; Glendening, Matthew; Shaw, Kenneth W. (2023). "Aggregate Financial Misreporting and the Predictability of U.S. Recessions and GDP Growth". The Accounting Review. 98 (5): 129–159. doi:10.2308/TAR-2021-0160. SSRN 3790566.
^ Zumbrun, Josh (2023-03-24). "Accounting-Fraud Indicator Signals Coming Economic Trouble". Wall Street Journal. ISSN 0099-9660. Retrieved 2023-06-13.
^ "Business School Students Caught Enron Early". The Cornell Daily Sun. 2007-01-29. Retrieved 2021-10-31.
^ "Cornell Research Report on Enron 1998". pdfslide.net. Retrieved 2021-10-31.
^ "Attention Value Investors: How to Predict Accounting Trickery". Alpha Architect. 2015-04-20. Retrieved 2017-01-28.
^ "The Accrual Anomaly For Dummies". Alpha Architect. 2011-09-07. Retrieved 2017-01-28.
^ "Managing the Risks of Permanent Capital Impairment (Part 1 of 4)". Alpha Architect. 2012-06-25. Retrieved 2017-01-28.
^ Beattie, Andrew (2006-11-26). "Common Clues Of Financial Statement Manipulation". Investopedia. Retrieved 2017-01-28.

[:0-1] Messod D. Beneish. "The Detection of Earnings Manipulation". Scribd. Retrieved 2017-01-08.

[2] "Beneish M Score Definition". ycharts.com. Retrieved 2017-01-08.

[3] Beneish, Messod D.; Farber, David B.; Glendening, Matthew; Shaw, Kenneth W. (2023). "Aggregate Financial Misreporting and the Predictability of U.S. Recessions and GDP Growth". The Accounting Review. 98 (5): 129–159. doi:10.2308/TAR-2021-0160. SSRN 3790566.

[4] Zumbrun, Josh (2023-03-24). "Accounting-Fraud Indicator Signals Coming Economic Trouble". Wall Street Journal. ISSN 0099-9660. Retrieved 2023-06-13.

[5] "Business School Students Caught Enron Early". The Cornell Daily Sun. 2007-01-29. Retrieved 2021-10-31.

[6] "Cornell Research Report on Enron 1998". pdfslide.net. Retrieved 2021-10-31.

[7] "Attention Value Investors: How to Predict Accounting Trickery". Alpha Architect. 2015-04-20. Retrieved 2017-01-28.

[8] "The Accrual Anomaly For Dummies". Alpha Architect. 2011-09-07. Retrieved 2017-01-28.

[9] "Managing the Risks of Permanent Capital Impairment (Part 1 of 4)". Alpha Architect. 2012-06-25. Retrieved 2017-01-28.

[10] Beattie, Andrew (2006-11-26). "Common Clues Of Financial Statement Manipulation". Investopedia. Retrieved 2017-01-28.

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