Markov processes form a fundamental class of stochastic models in which the evolution of a system is delineated by the memoryless property. In such processes, the future state depends solely on the ...

Semi-Markov processes extend traditional Markov models by explicitly accounting for the time spent in each state before transitioning. This added temporal dimension is particularly valuable in credit ...

This is a preview. Log in through your library . Abstract We consider risk processes that locally behave like Brownian motion with some drift and variance, these both depending on an underlying Markov ...

In this paper we show that any separable stochastic process on a compact metric space can be derived from a temporally homogeneous Markov process on the extreme points of a compact convex set of ...