This article develops a new portfolio selection method using Bayesian theory. The proposed method accounts for the uncertainties in estimation parameters and the model specification itself, both of which are ignored by the standard mean-variance method. The critical issue in constructing an...

A description of computationally efficient methods for the Bayesian analysis of Student-t seemingly unrelated regression (SUR) models with unknown degrees of freedom is given. The method combines a direct Monte Carlo (DMC) approach with an importance sampling procedure to calculate Bayesian...

This paper investigates the performance of the predictive distributions of Bayesian models. To overcome the difficulty of evaluating the predictive likelihood, we introduce the concept of expected log-predictive likelihoods for Bayesian models, and propose an estimator of the expected...