Modelling Portfolio Defaults Using Hidden Markov Models with Covariates

Konrad Banachewicz, Andre Lucas and Aad van der Vaart

Econometrics Journal, 2008, vol. 11, issue 1, 155-171

Abstract: We extend the hidden Markov Model for defaults of Crowder et al. (2005, Quantitative Finance 5, 27--34) to include covariates. The covariates enhance the prediction of transition probabilities from high to low default regimes. To estimate the model, we extend the EM estimating equations to account for the time varying nature of the conditional likelihoods due to sample attrition and extension. Using empirical U.S. default data, we find that GDP growth, the term structure of interest rates and stock market returns impact the state transition probabilities. The impact, however, is not uniform across industries. We only find a weak correspondence between industry credit cycle dynamics and general business cycles. Copyright Royal Economic Society 2008

Date: 2008
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Working Paper: Modeling Portfolio Defaults using Hidden Markov Models with Covariates (2006)
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