In this paper, we propose a new multivariate mean-reverting model incorporating state-of-the art 4/2 stochastic volatility and a convenient principal component stochastic volatility (PCSV) decomposition for the stochastic covariance. We find a quasi closed-form characteristic function and...

It is divided into four substantive parts, as follows: Part 1, Stochastic Models and their Forecasting, is an introduction to linear stationary models with finite numbers of parameters, in particular ARMA (mixed autoregressive-moving average) processes, their probabilistic and forecasting...