Title :
A Method for Identifying the Industry Credit Risk Based on Markov Chain
Author :
Zhang, Mu ; Zhou, Zongfang
Author_Institution :
Sch. of Manage. & Econ., Univ. of Electron. Sci. & Technol. of China, UESTC, Chengdu, China
Abstract :
This paper proposes a new method for identifying the industry credit risk based on Markov chain. Firstly, a new credit rating model for enterprises based on Projection Pursuit and optimal partition is constructed, and then a credit state space of enterprises is established. Secondly, through calculating the non-conditional probability, the one-step transfer probability matrix of industry is obtained. Finally, through calculating the k-step transfer probability matrix of industry, the industry credit risk is identified successfully. Taking the high-tech listed companies in China as samples, it is proved that the method proposed by this paper is feasible and effective.
Keywords :
Markov processes; financial management; matrix algebra; probability; risk analysis; risk management; China; Markov chain; credit rating model; industry credit risk; k-step transfer probability matrix; nonconditional probability; one-step transfer probability matrix; projection pursuit; Banking; Biological system modeling; Finance; Markov processes; Modeling; Probability; Markov chain; credit rating; credit risk identification; credit transfer matrix; industry credit risk;
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
DOI :
10.1109/ICEE.2010.882