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Forecasting Cross-Sections of Frailty-Correlated Default

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Author Info
Siem Jan Koopman () (VU University Amsterdam)
André Lucas () (VU University Amsterdam)
Bernd Schwaab () (VU University Amsterdam)

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Abstract

We propose a novel econometric model for estimating and forecasting cross-sections of time-varying conditional default probabilities. The model captures the systematic variation in corporate default counts across e.g. rating and industry groups by using dynamic factors from a large panel of selected macroeconomic and financial data as well as common unobserved risk factors. All factors are statistically and economically significant and together capture a large part of the time-variation in observed default rates. In this framework we improve the out-of-sample forecasting accuracy associated with conditional default probabilities by about 10-35% in terms of Mean Absolute Error, particularly in years of default stress.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 08-029/4.

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Date of creation: 20 Mar 2008
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Handle: RePEc:dgr:uvatin:20080029

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Web page: http://www.tinbergen.nl/

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Related research
Keywords: Non-Gaussian Panel Data Common Factors Unobserved Components Forecasting Conditional Default Probabilities

Find related papers by JEL classification:
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages

References listed on IDEAS
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