Modeling Portfolio Defaults Using Hidden Markov Models with Covariates
by Konrad Banachewicz of Vrije Universiteit,
October 24, 2006
Abstract: We extend the Hidden Markov Model for defaults of Crowder, Davis, and Giampieri (2005) 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.
Keywords: defaults, Markov switching, default regimes.
Published in: Econometrics Journal, Vol. 11, No. 1, (March 2008), pp.155-171.