Abstracts

In this study we model the dynamics of sovereign credit spreads. Specifically, we interpret credit spreads as the noisy observations of some state process which represents the financial strength of the sovereigns under consideration. This naturally gives rise to a partial-information setting in which, the default history of the sovereigns constitutes an additional piece of information. In order to incorporate that information in the analysis, we extend the estimation methodology given in Elliot (1993) and obtain an EM algorithm for the setting where the state variable follows a Markov chain observed via diffusive and point processes information. We test the speed, efficiency and accuracy of the algorithm by running a simulation analysis.