my-server
← Wiki

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):

  • Days Sales in Receivables Index

(DSRI) DSRI = (Net Receivables<sub>t</sub> / Sales<sub>t</sub>) / (Net Receivables<sub>t-1</sub> / Sales<sub>t-1</sub>)

  • Gross Margin Index (GMI)

GMI = [(Sales<sub>t-1</sub> - COGS<sub>t-1</sub>) / Sales<sub>t-1</sub>] / [(Sales<sub>t</sub> - COGS<sub>t</sub>) / Sales<sub>t</sub>]

  • Asset Quality Index (AQI)

AQI = [1 - (Current Assets<sub>t</sub> + PP&E<sub>t</sub> + Securities<sub>t</sub>) / Total Assets<sub>t</sub>] / [1 - ((Current Assets<sub>t-1</sub> + PP&E<sub>t-1</sub> + Securities<sub>t-1</sub>) / Total Assets<sub>t-1</sub>)]

  • Sales Growth Index (SGI)

SGI = Sales<sub>t</sub> / Sales<sub>t-1</sub>

  • Depreciation Index (DEPI)

DEPI = (Depreciation<sub>t-1</sub>/ (PP&E<sub>t-1</sub> + Depreciation<sub>t-1</sub>)) / (Depreciation<sub>t</sub> / (PP&E<sub>t</sub> + Depreciation<sub>t</sub>))

  • Sales General and Administrative Expenses Index (SGAI)

SGAI = (SG&A Expense<sub>t</sub> / Sales<sub>t</sub>) / (SG&A Expense<sub>t-1</sub> / Sales<sub>t-1</sub>)

  • Leverage Index (LVGI)

LVGI = [(Current Liabilities<sub>t</sub> + Total Long Term Debt<sub>t</sub>) / Total Assets<sub>t</sub>] / [(Current Liabilities<sub>t-1</sub> + Total Long Term Debt<sub>t-1</sub>) / Total Assets<sub>t-1</sub>]

  • Total Accruals to Total Assets (TATA)

TATA = (Income from Continuing Operations<sub>t</sub> - Cash Flows from Operations<sub>t</sub>) / Total Assets<sub>t</sub>

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

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 −1.780, 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 uses an aggregate score of many companies to predict recessions. It finds that the score in early 2023 is the highest in some 40 years.

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.

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