Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian prior works allow this approach to provide parsimonious skew structure and...

Let ${\bf X}$ and be two $n$-dimensional elliptical random vectors, we establish an identity for $E[f({\bf Y})]-E[f({\bf X})]$, where $f: \Bbb{R}^n \rightarrow \Bbb{R}$ fulfilling some regularity conditions. Using this provide a unified derivation of sufficient necessary conditions classifying multivariate vectors according to several main integral stochastic orders. As consequence obtain new i...

Outline Introduction Semi-parametric dynamic copula Motivation Local likelihood estimation Variance of the estimator Bias of the estimator Bandwidth selection Estimation of joint likelihood Modeling of marginal distributions Simulations and applications Simulations Empirical example Conclusions Problems and Solutions Problems Modeling dependence is critical for financial time series Model volat...

The family of skew distributions introduced by Azzalini and extended by others has received widespread attention. However, it suffers from complicated inference procedures. In this paper, a new family of skew distributions that overcomes the difficulties is introduced. This new family belongs to the exponential family. Many properties of this family are studied, inference procedures developed a...

Bivariate clustered (correlated) data often encountered in epidemiological and clinical research are routinely analyzed under a linear mixed model (LMM) framework with underlying normality assumptions of the random effects and within-subject errors. However, such normality assumptions might be questionable if the data set particularly exhibits skewness and heavy tails. Using a Bayesian paradigm...

Web Appendix A. Multivariate Skew Distributions Different versions of the multivariate skew–normal(SN) and skew-t (ST) distributions have been considered and used in the literature (Arellano-Valle and Genton, 2005; Arellano-Valle et al, 2007; Azzalini and Capitanio, 2003; Sahu et al, 2003 and among others). A new class of distributions by introducing skewness in multivariate elliptically distri...

The classical bivariate F distribution arises from ratios of chi-squared random variables with common denominators. A consequent disadvantage is that its univariate F marginal distributions have one degree of freedom parameter in common. In this paper, we add a further independent chisquared random variable to the denominator of one of the ratios and explore the extended bivariate F distributio...