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Beneish M-score

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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):

  • Days Sales in Receivables Index

(DSRI) DSRI = (Net Receivablest / Salest) / (Net Receivablest-1 / Salest-1)

  • Gross Margin Index (GMI)

GMI = /

  • Asset Quality Index (AQI)

AQI = /

  • Sales Growth Index (SGI)

SGI = Salest / Salest-1

  • Depreciation Index (DEPI)

DEPI = (Depreciationt-1/ (PP&Et-1 + Depreciationt-1)) / (Depreciationt / (PP&Et + Depreciationt))

  • Sales General and Administrative Expenses Index (SGAI)

SGAI = (SG&A Expenset / Salest) / (SG&A Expenset-1 / Salest-1)

  • Leverage Index (LVGI)

LVGI = /

  • Total Accruals to Total Assets (TATA)

TATA = (Income from Continuing Operationst - Cash Flows from Operationst) / Total Assetst

The formula to calculate the M-score is:

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

Cite error: A <ref> tag is missing the closing </ref> (see the help page).</ref>== 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.

Note from M.D. Beneish: The cut-off described in Investopedia (-2.22) is incorrect for the model reported above. It was a valid cut-off for an early version of the weighted probit estimation (WESML). I don't know how to change it References: M. D. Beneish, "The Detection of Earnings Manipulation." Financial Analysts’ Journal, 1999, 55(5):24-36. M. D. Beneish, C.M.C. Lee and D.C. Nichols, “Earning Manipulation and Expected Returns”, Financial Analysts Journal-March/April 2013:57-82. M. D. Beneish, and P. J. Vorst “The Cost of Fraud Prediction Errors” Kelley School of Business Research Paper No. 2020-55, available at SSRN: https://ssrn.com/abstract=3529662 or http://dx.doi.org/10.2139/ssrn.3529662

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. It means that the M-score for fraud detection cannot be applied among financial firms (banks, insurance).

Example of successful application

Enron Corporation was correctly identified 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.

Further reading on financial statement manipulation

  • A sequence of articles on Alpha Architect blog.
  • An article on Investopedia about different types of financial statement manipulation ("smoke and mirrors", "elder abuse", "fleeing town", and others).

See also

References

  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. "Attention Value Investors: How to Predict Accounting Trickery". Alpha Architect. 2015-04-20. Retrieved 2017-01-28.
  4. "The Accrual Anomaly For Dummies". Alpha Architect. 2011-09-07. Retrieved 2017-01-28.
  5. "Managing the Risks of Permanent Capital Impairment (Part 1 of 4)". Alpha Architect. 2012-06-25. Retrieved 2017-01-28.
  6. Beattie, Andrew (2006-11-26). "Common Clues Of Financial Statement Manipulation". Investopedia. Retrieved 2017-01-28.
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