On the Asymptotic Events of a Markov Chain

Financial Risk Modeling with Markova Chain

Investors use different approaches to select optimal portfolio. so, Optimal investment choices according to return can be interpreted in different models. The traditional approach to allocate portfolio selection called a mean - variance explains. Another approach is Markov chain. Markov chain is a random process without memory. This means that the conditional probability distribution of the nex...

A Scaling Analysis of a Cat and Mouse Markov Chain

Motivated by an original on-line page-ranking algorithm, starting from an arbitrary Markov chain (Cn) on a discrete state space S, a Markov chain (Cn, Mn) on the product space S, the cat and mouse Markov chain, is constructed. The first coordinate of this Markov chain behaves like the original Markov chain and the second component changes only when both coordinates are equal. The asymptotic pro...

Markov Chain Anticipation for the Online Traveling Salesman Problem by Simulated Annealing Algorithm

The arc costs are assumed to be online parameters of the network and decisions should be made while the costs of arcs are not known. The policies determine the permitted nodes and arcs to traverse and they are generally defined according to the departure nodes of the current policy nodes. In on-line created tours arc costs are not available for decision makers. The on-line traversed nodes are f...

Asymptotic Behavior of Multivariate Reward Processes with Nonlinear Reward Functions

Relative Entropy Rate between a Markov Chain and Its Corresponding Hidden Markov Chain

 In this paper we study the relative entropy rate between a homogeneous Markov chain and a hidden Markov chain defined by observing the output of a discrete stochastic channel whose input is the finite state space homogeneous stationary Markov chain. For this purpose, we obtain the relative entropy between two finite subsequences of above mentioned chains with the help of the definition of...