Economic Analysis: Theory and Practice

Increasing the efficiency of exposure to bankruptcy analysis under econometric methods

Vol. 17, Iss. 6, JUNE 2018

Received: 28 March 2018

Received in revised form: 2 April 2018

Accepted: 16 April 2018

Available online: 30 June 2018


JEL Classification: C01, C13, G33, G34

Pages: 1178–1196

Bukharin S.V. Voronezh State University of Engineering Technologies, Voronezh, Russian Federation

Paraskevich V.V. Voronezh State University of Engineering Technologies, Voronezh, Russian Federation

Importance The article analyzes the methodology for comparing the results of various methods to assess bankruptcy exposure.
Objectives The purpose of the study is to develop a single approach to comparing the results of various methods through the introduction of a composite index of financial standing on the basis of modern econometric methods.
Methods We employ methods of the theory of expert systems, fuzzy sets, the analytic hierarchy process by Thomas Saaty, rank statistician, correlation analysis.
Results Using the theory of expert systems, we offer a single composite index of enterprise financial condition; based on the modern method of analytic hierarchy process for the W. Beaver method, which traditionally estimates only separate attributes, we introduce an integrated rating number; for the R.S. Saifullin and G.G. Kadykov method, we introduce the vector of priorities to account for various importance of attributes in the rating. The findings show that the results of these three methods comply with the introduced composite index and can be compared from a unified position.
Conclusions The introduced composite index of financial condition enabled to compare the results of three widespread methods of exposure to bankruptcy analysis on a uniform methodological basis. The paper shows that the said three methods provide a qualitatively identical picture of separating the enterprises into 'normal' and 'unsatisfactory'.

Keywords: bankruptcy, rating, scoring, correlation


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Vol. 17, Iss. 6
June 2018