Article ID: | iaor201526520 |
Volume: | 34 |
Issue: | 4 |
Start Page Number: | 261 |
End Page Number: | 274 |
Publication Date: | Jul 2015 |
Journal: | Journal of Forecasting |
Authors: | Guo Min, Liu Chang, Nassar Raja |
Keywords: | finance & banking, markov processes, statistics: regression |
In this study, a non‐stationary Markov chain model and a vector autoregressive moving average with exogenous variables coupled with a logistic function (VARMAX‐L) are used to analyze and predict the stability of a retail mortgage portfolio, based on the stress test framework. The method introduced in this paper can be used to forecast the transition probabilities in a retail mortgage over pre‐specified states, given a shock with a certain magnitude. Hence this method provides a dynamic picture of the portfolio transition process through which one can assess its behavior over time. While the paper concentrates on retail mortgages, the methodology of this study can be adapted also to analyze other credit products in banks.