ScholarGate
Asisten

Bandingkan metode

Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.

Analisis DuPont×Beneish M-Score: Mendeteksi Manipulasi Laba×
BidangKeuanganKeuangan
KeluargaRegression modelRegression model
Tahun asal20081999
PencetusDuPont Corporation; SolimanMessod Beneish
TipeProfitability decomposition frameworkProbabilistic forensic accounting model
Sumber perintisSoliman, M. T. (2008). The use of DuPont analysis by market participants. The Accounting Review, 83(3), 823–853. DOI ↗Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24–36. DOI ↗
AliasDuPont Decomposition, DuPont Identity, Return on Equity Decomposition, DuPont AnaliziBeneish Model, M-Score Model, Earnings Manipulation Score, Beneish M-Skoru
Terkait23
RingkasanDuPont 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 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.
ScholarGateSet data
  1. v1
  2. 1 Sumber
  3. PUBLISHED
  1. v1
  2. 1 Sumber
  3. PUBLISHED

Ke halaman pencarian Unduh salindia

ScholarGateBandingkan metode: DuPont Analysis · Beneish M-Score. Diakses 2026-06-19 dari https://scholargate.app/id/compare