Earticle

초록

영어

Nowadays, the accounting information distortion of listed company is generally common in the market. It has caused adverse effects to the enterprise itself and even the development of the securities market. In order to solve this problem, domestic and foreign scholars have done a series of researches from different perspectives and create a lot of detection model to identify financial reporting fraud more correctly. As far as we are concerned, these models’ index selection, calculation, prediction and application are not so satisfying and few efficient recognition models can be applied generally. In this paper, we combine the method of principal component analysis with logistic regression method. Then we select variables from the financial data that reflect the profitability, turnover, the establishment of the enterprise and some other perspectives. This accounting information distortion detection model is created by improving the method and index selection which has a higher correct recognition rate. We have chosen the 2012 financial statements from 56 firms for sample and the forecasting accuracy of the model reached 92.86%. We can get that it has obvious advantages compared to the predicted results from simple logistic regression model.

목차

Abstract
 1. Introduction
 2. The Basic Idea of Logistic Regression Method
 3. The Principle Components-logistic Regression Method
 4. The Empirical Analysis
 5. Conclusions and Recommendations
 References

키워드

저자

• Zhenjie Li [ School of Economics and Management, Yantai University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605