Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

Using copula methods and simulation-based inference, the authors investigate the association between the performance of a stock index formed by European financial institutions and a basket of CDS contracts of the same sector. Their analysis focuses on (i) assessing the dependence structure of...

Using copula methods and simulation-based inference the authors address the association between the performance of the stocks of European banks and the CDS markets. Their analysis has three purposes: (i) analysing the dependence structure of the markets when extreme events occur; (ii) checking...

We develop the idea of using Monte Carlo sampling of random portfolios to solve portfolio investment problems. In this first paper we explore the need for more general optimization tools, and consider the means by which constrained random portfolios may be generated. A practical scheme for the...