This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets (Brent oil and WTI oil) for the period 2011-2021. The main objective is to make step ahead volatility predictions for the front month contracts followed by an implication discussion...

This paper is concerned with near-optimal control of manufacturing systems consisting of two unreliable machines in tandem and having the objective of minimizing the total discounted cost of inventories/shortages over an infinite horizon. Asymptotic optimal feedback controls are constructed with...

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

In this paper, we explore a dynamical version of by Aoki and Yoshikawa model (AYM) for an economy driven by demand. We show that when an appropriate Markovian dynamics is taken into account, AYM has different equilibrium distributions depending on the form of transition probabilities. In the...

For a time-continuous discrete-state Markov process as model for rating transitions, we study the time-stationarity by means of a likelihood ratio test. For multiple Markov process data from a multiplicative intensity model, maximum likelihood parameter estimates can be represented as martingale...

We show that local potential maximizer (\cite{morris+05}) with constant weights is stochastically stable in the log-linear dynamics provided that the payoff function or the associated local potential function is supermodular. We illustrate and discuss, through a series of examples, the use of...