A varying-coefficient default model

doi:10.1016/j.ijforecast.2011.11.006

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A varying-coefficient default model

2012-07-01

PRE

Ruey‐Ching Hwang *

DOI：10.1016/j.ijforecast.2011.11.006

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Abstract

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In this paper, a default prediction method based on the discrete-time varying-coefficient hazard model (DVHM) is proposed. The new model is constructed by replacing the constant coefficients of firm-specific predictors in the discrete-time hazard model (DHM; see Shumway, 2001; and Chava & Jarrow, 2004) with the smooth functions of macroeconomic variables. Thus, it allows the effects of those firm-specific predictors on the default prediction to change with the macroeconomic dynamics (Pesaran, Schuermann, Treutler, & Weiner, 2006). The coefficient functions in the new model are estimated by a local likelihood approach. One real panel dataset is used to illustrate the proposed methodology. Using an expanding rolling window approach, the empirical results confirm that DVHM has a better and more robust performance than the usual DHM, in the sense that it yields more accurate predicted numbers of defaults and predictive intervals through out-of-sample analysis. Thus, the proposed model is a useful alternative for studying default losses on portfolios. (c) 2012 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Keywords:

Discrete-time hazard model

Local likelihood

Expanding rolling window approach

Predicted number of defaults

Predictive interval

Varying-coefficient model

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