Estimating Default Risk of Bank Loans in Zimbabwe Using the Mover-Stayer Model

Dingilizwe Jacob Nkomo (), Union Chiwandamira () and Peter Mazuruse ()

Asian Journal of Economic Modelling, 2018, vol. 6, issue 3, 220-234

Abstract: This paper estimates default probabilities of bank loans through the use of a mover stayer model, using the data of Zimbabwe. Management of credit risk is an element of financial engineering, which provides safeguard against institutions’ financial failure. The study aimed at estimating default probabilities of bank loans through the use of a mover stayer model. In-order to achieve this, the study compared the predictive power of duration method and cohort method in forecasting default risk of bank loans, tested for presence of time homogeneity and determined the model with an upper hand between the Mover stayer model and the Markov Chain Model in gauging default risk. It was concluded that the cohort approach has an upper hand than the duration approach and that there was time inhomogeneity. There was also significant evidence that the mover-stayer model is a superior and effective way of estimating the risk of default. The effectiveness was shown through the process of back testing. The forecasted results for 2014 were in line with the actual 2014 default results hence the model called the Mover Stayer effectively and competently predicted the risk of default of bank advances and loans.

Keywords: Markov chain; Mover-stayer model; Default probabilities; Time homogeneity. (search for similar items in EconPapers)
Date: 2018
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