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Discriminant Analysis of Zero Recovery for China's NPL

by Yue Tang of the Chinese Academy of Sciences,
Hao Chen of the Chinese Academy of Sciences,
Bo Wang of the Chinese Academy of Sciences,
Muzi Chen of the Chinese Academy of Sciences,
Min Chen of the Chinese Academy of Sciences, and
Xiaoguang Yang of the Chinese Academy of Sciences

March 2009

Abstract: Classification of whether recovery of non-performing loans NPL is zero or positive is not only important in management of non-performing loans, but also is essential for estimating recovery rate and implementing the new Basel Capital Accord. Based on the largest database of NPL's recovering information in China, this paper tries to establish discriminant models to predict the loan with zero recovery. We first use Step-wise discrimination method to select variables; then give an in-depth analysis on why the selected variables are important factors influencing whether a loan is zero or positive recovery rate. Using the selected variables, we establish two-type discriminant models to classify the NPLs. Empirical results show that both models achieve high prediction accuracy, and the characteristics of obligors are the most important factors in determining whether a NPL is positively recovered or zero recovered.

Published in: Journal of Applied Mathematics and Decision Sciences, Vol. 2009, No. 594793, 16 pages.

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