Identification Model of Logistic Regression Analysis on Listed Firms' Frauds in China
Xiaoxin Chen, Ye Rong · 2009
The identification of corporation accounting frauds is a major difficulty in financial study. This article establishes an identifying model of financial frauds of Chinese listed firms by adopting Logistic regression analysis. Then it defines public companies whose accounting statements are rejected or denied by register accountant in Shanghai & Shenzhen security market as " corporation with financial frauds" and selects 88 corporations which contain 44 companies with financial frauds and 44 companies without financial frauds as samples of study to build the Logistic regression identifying model for financial frauds of listed firms. Appling the model to test samples which contain 30 firms which 15 companies with financial frauds and 15 companies without financial frauds, it possesses good identification ability, because accurate rate of its identification is 93.33%.