Bayesian predictive density estimation represents a cornerstone of modern statistical inference by integrating prior knowledge with observed data to produce a predictive distribution for future ...

The Stiefel manifold Vp,d is the space of all d × p orthonormal matrices, with the d−1 hypersphere and the space of all orthogonal matrices constituting special cases. In modeling data lying on the ...

We suggest a new method for integrating volatility information for estimating the value-at-risk and conditional value-at-risk of a portfolio. This new method is developed from the perspective of ...

The covariance matrix of asset returns is the key input for many problems in finance and economics. This paper introduces a Bayesian nonparametric method to estimate the ex post covariance matrix from ...

Extended educational sessions that offer attendees the opportunity to learn research methods and techniques from prominent ...