Il giorno giovedì 16 febbraio alle ore 16 presso il Dipartimento di Economia dell'Università di Perugia, la Dott.ssa Zehra Eksi, Assistant Professor presso la WU-Vienna University of Economics and Business, e ospite del Dipartimento di Economia in qualità di professore visitatore nell'ambito del progetto YITP (Young Investigation Training Program), terrà un seminario dal titolo

"EM Algorithm for Markov Chains observed via Gaussian Noise and Point Processes Information"

*Abstract*:

In this paper we obtain an Expectation-Maximization (EM) algorithm for a setting in which the state variable follows a finite-state Markov chain observed via diffusive and point process information. Such a setting may arise, for example, in the modelling of sovereign credit risk where information stems from default history (jump component) and CDS spreads (diffusive component). Obtaining the EM algorithm amounts to the derivation of finite-dimensional filters for quantities such as number of jumps and sojourn times associated to the Markov chain. In this context, we obtain both exact and unnormalized filters for the related quantities. Moreover, we compute discretized robust versions of the unnormalized filters. Next, we introduce a novel goodness of fit test to check how well the estimated model explains a given data set. Finally, we run a simulation study to test speed and accuracy of the algorithm. In particular, we provide a comparison for the estimates resulting from the robust and naive discretization and the value of point process information (This is a Joint work with Camilla Damian and Ruediger Frey)

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Dott.ssa Katia Colaneri Department of Economics, University of Perugia Via A. Pascoli 20, Perugia 06123- Italy e-mail: katia.colaneri@unipg katia.colaneri@gmail.com.it