This paper investigates the economic importance of nonparametrically/semiparametrically modelling the shape and the change in the unknown distribution of returns in portfolio allocation problems from a Bayesian perspective. Besides parametric multivariate GARCH (MGARCH) benchmark models for...

This paper introduces a novel Bayesian time series model that combines the nonparametric features of an infinite hidden Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short-term interest rates. When applied to US 3-month Treasury...

This paper proposes a new parsimonious multivariate GARCH-jump (MGARCH-jump) mixture model with multivariate jumps that allows both jump sizes and jump arrivals to be correlated among assets. Dependent jumps impact the conditional moments of returns as well as beta dynamics of a stock. Applied...

This paper proposes a new Bayesian semiparametric model that combines a multivariate GARCH (MGARCH) component and an infinite hidden Markov model. The new model nonparametrically approximates both the shape of unknown returns distributions and their short-term evolution. It also captures the...

This paper extends the Bayesian semiparametric stochastic volatility (SV-DPM) model of Jensen and Maheu (2010). Instead of using a Dirichlet process mixture (DPM) to model return innovations, we use an infinite hidden Markov model (IHMM). This allows for time variation in the return density...

The stochastic volatility (SV) model has been one of the most popular models for latent stock return volatility. Extensions of the SV model focus on either improving volatility inference or modeling higher moments of the return distribution. This study investigates which extension can better...

This paper investigates the economic importance of nonparametrically/semiparametrically modelling the shape and the change in the unknown distribution of returns in portfolio allocation problems from a Bayesian perspective. Besides parametric multivariate GARCH (MGARCH) benchmark models for...