Forecasting credit portfolio components with a Markov chain model

被引：0
|
作者：
G. A. Timofeeva
N. A. Timofeev
机构：
[1] Ural Federal University,
[2] Ural State Academy of Railway Transport,undefined
来源：
Automation and Remote Control | 2012年 / 73卷
关键词：
Remote Control; Markov Chain Model; Transition Probability Matrix; Credit Portfolio; Imitational Modeling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We consider the forecasting problem for components of a bank’s credit portfolio, in particular, for the share of non-performing loans. We assume that changes in the portfolio are described by a Markov random process with discrete time and finite number of states. By the state of a loan we mean that it belongs to a certain group of loans with respect to the existence and duration of arrears. We assume that the matrix of transitional probabilities is not known exactly, and information about it is collected during the system’s operation.
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页码：637 / 651
页数：14
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