A Forecasting Model for the Likelihood of Delinquency, Default or Prepayment: The Case of Taiwan

10 Pages Posted: 9 Jan 2004

See all articles by Chin-Tsai Lin

Chin-Tsai Lin

Yuan Pei Institute of Science and Technology - Department of Information Management

Shih-Yu Yang

Chihlee Institute of Technology

Abstract

In a competitive and dynamic market, financial institutions must forecast the proportion of mortgages that will become delinquent, default or prepay. This paper develops a novel forecasting model with nonstationary Markov chain and Grey forecasting, capable of predicting the likelihood of delinquency, default and prepayment. Home mortgage data, obtained by a major Taiwan financial institution from January 1, 1996 to June 30, 1998, are adopted to examine the forecasting effectiveness of the novel forecasting model and the ARIMA model. Empirical results indicate that the novel forecasting model with a low error is better than ARIMA. Thus, the novel forecasting model provides a promising means of accurately predicting the probabilities of delinquency, default and prepayment.

Keywords: Forecasting, Mortgage, Loan, Delinquency, Default, Prepayment

JEL Classification: C60, G2, G21, O53

Suggested Citation

Lin, Chin-Tsai and Yang, Shih-Yu, A Forecasting Model for the Likelihood of Delinquency, Default or Prepayment: The Case of Taiwan. Available at SSRN: https://ssrn.com/abstract=420263

Chin-Tsai Lin (Contact Author)

Yuan Pei Institute of Science and Technology - Department of Information Management ( email )

Hsinchu
Taiwan

Shih-Yu Yang

Chihlee Institute of Technology ( email )

Taipei, 200
Taiwan