방법 비교

	DuPont 분석	Altman Z-Score: 기업 파산 예측	Beneish M-Score: 부정 회계 탐지
분야	재무학	재무학	재무학
계열	Regression model	Regression model	Regression model
기원 연도	2008	1968	1999
창시자	DuPont Corporation; Soliman	Edward Altman	Messod Beneish
유형	Profitability decomposition framework	Multiple discriminant analysis scoring model	Probabilistic forensic accounting model
원전	Soliman, M. T. (2008). The use of DuPont analysis by market participants. The Accounting Review, 83(3), 823–853.	Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609.	Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24–36.
별칭	DuPont Decomposition, DuPont Identity, Return on Equity Decomposition, DuPont Analizi	Altman's Z-Score Model, Multiple Discriminant Analysis Bankruptcy Model, Z-Score Financial Distress Model, Altman Z-Skoru	Beneish Model, M-Score Model, Earnings Manipulation Score, Beneish M-Skoru
관련	2	3	3
요약	DuPont Analysis is a financial performance framework that decomposes Return on Equity (ROE) into three multiplicative components: net profit margin, asset turnover, and the equity multiplier. Originally developed by engineers at DuPont Corporation in the early 1920s, the method gained renewed academic prominence through Soliman (2008), who demonstrated that market participants exploit DuPont decompositions to forecast future earnings and to distinguish sustainable from transient profitability.	The Altman Z-Score is a linear discriminant model developed by Edward I. Altman in 1968 to predict corporate bankruptcy using five accounting-based financial ratios. Derived through multiple discriminant analysis on a matched sample of 66 US manufacturing firms, the model combines liquidity, profitability, leverage, solvency, and activity ratios into a single composite score that classifies firms as financially sound, distressed, or in a grey zone.	The 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.