Analysis of Default Data Using Hidden Markov Models

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Crowder, Martin, Mark Davis, and Giacomo Giampieri, "Analysis of Default Data Using Hidden Markov Models", Quantitative Finance, Vol. 5, No. 1, (February 2005), pp. 27-34.

Abstract: Current risk assessment methodologies separate the analysis of market and credit risk and thus misestimate security and portfolio risk levels. We propose a new approach that relates financial market volatility to firm specific credit risk and integrates interest rate, interest rate spread, and foreign exchange rate risk into one overall fixed income portfolio risk assessment. Accounting for the correlation between these significant risk factors as well as portfolio diversification results in improved risk measurement and management. The methodology is shown to produce reasonable credit transition probabilities, prices for bonds with credit risk, and portfolio value-at-risk measures.

Previously titled: A Hidden Markov Model of Default Interaction

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