Forecasting forward defaults: a simple hazard model with competing risks |
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Authors: | Ruey-Ching Hwang Chih-Kang Chu |
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Institution: | 1. Department of Finance, National Dong Hwa University, Hualien 97401, Taiwan.rchwang@mail.ndhu.edu.tw;3. Department of Applied Mathematics, National Dong Hwa University, Hualien, Taiwan. |
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Abstract: | A forward default prediction method based on the discrete-time competing risk hazard model (DCRHM) is proposed. The proposed model is developed from the discrete-time hazard model (DHM) by replacing the binary response data in DHM with the multinomial response data, and thus allowing the firms exiting public markets for different causes to have different effects on forward default prediction. We show that DCRHM is a reliable and efficient model for forward default prediction through maximum likelihood analysis. We use actual panel data-sets to illustrate the proposed methodology. Using an expanding rolling window approach, our empirical results statistically confirm that DCRHM has better and more robust out-of-sample performance than DHM, in the sense of yielding more accurate predicted number of forward defaults. Thus, DCRHM is a useful alternative for studying forward default losses on portfolios. |
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Keywords: | Competing risks Discrete-time hazard model Expanding rolling window approach Forward default prediction Multinomial logit model Predicted number of forward defaults |
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