predictors, where robust stands for the use of mixtures of proper conjugate priors. Concerning dynamic analysis, volatility …

density of logreturns. Our proposed approach originates from the Bayesian approach to parameter estimation and time series … forecasting, however it is robust in the sense that it provides a more accurate estimation of the predictive density in the region …. This quasi-Bayesian approach yields more precise parameter estimation than a fully censored posterior for all parameters …

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized …’s seminal work in terms of the estimation of highly non-linear model specifications ("Causality tests and observationally …. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions …

Many recent modelling advances in finance topics ranging from the pricing of volatility-based derivative products to … number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in … forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …