In this paper, we consider hidden semi-Markov chain filters having possible applications in areas such as genomics, statistical studies of earthquakes, reliability, etc.

We introduce a weak hidden Markov model (WHMM) in an attempt to capture more accurately the evolution of a risky asset. The log returns of assets are modulated by a weak or higher-order Markov chain with finite-state space. In particular, the optimal estimates of the second-order Markov chain...

In this paper we propose a type of mean reverting model with jumps, where the mean reverting level changes according to a continuous time, finite state Markov chain. This model could be applied to the interest rate and energy markets. We apply filtering techniques and obtain finite dimensional...