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Beneish M-Score: Detekce manipulace se ziskem×Logistická regrese×
OborFinanceStatistika ve výzkumu
RodinaRegression modelProcess / pipeline
Rok vzniku19991958
TvůrceMessod BeneishDavid Roxbee Cox
TypProbabilistic forensic accounting modelMethod
Původní zdrojBeneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24–36. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Další názvyBeneish Model, M-Score Model, Earnings Manipulation Score, Beneish M-Skorulogit model, binomial logistic regression, LR
Příbuzné33
ShrnutíThe Beneish M-Score is a statistical model developed by Messod Beneish in 1999 to identify whether a company has manipulated its reported earnings. The model combines eight financial-statement ratios into a single composite score using coefficients estimated from a probit regression on a sample of detected earnings manipulators. A score above −2.22 indicates a heightened probability of manipulation, making the M-Score a widely used tool in forensic accounting and investment due-diligence.Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.
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ScholarGatePorovnat metody: Beneish M-Score · Logistic Regression. Získáno 2026-06-18 z https://scholargate.app/cs/compare