The full Bayesian treatment of error component models typically relies on data augmentation to produce the required inference. Never stricly necessary a direct approach is always possible though not necessarily practical. The mechanics of direct sampling are outlined and a template for including...

In this paper we derive tests for parameter constancy when the data generating process is non-stationary against the hypothesis that the parameters of the model change smoothly over time. To obtain the asymptotic distributions of the tests we generalize many theoretical results, as well as new...

Bernardo and Ledoit (2000) develop a very appealing framework to compute pricing bounds based on the so-called gain-loss ratio. Their method has many advantages and very interesting properties and so far one important drawback: the complexity of the numerical computation of the pricing bounds....

We use Bayesian techniques to select factors in a general multifactor asset pricing model. From a given set of 15 factors we evaluate all possible pricing models by the extent to which they describe the data as given by the posterior model probabilities. Interest rates, premiums, returns on...