In this paper, the S&P 500 stock index is studied for its time varying volatility and stylized facts. The ARMA mean equation with asymmetric power ARCH errors is used to model the series correlations and the conditional heteroscadesticity in the asset returns. The conditional distributions of the standardized residuals are assumed to be the normal distribution, the t distribution or the skew-t ...

In this paper, likelihood-based inference and bias correction based on Firth’s approach are developed in the modified skew-t-normal (MStN) distribution. The latter model exhibits a greater flexibility than skew-normal (MSN) distribution since it is able to heavily skewed data thick tails. addition, tails controlled by shape parameter degrees of freedom. We provide density new present some its m...

In this paper we study the multivariate skew-normal distribution and its scale mixtures, as extensions of the similar non-skewed distributions. Different parameterizations and some properties are investigated. ∗ Subject Classification: 60E05.

In this paper, multivariate skew-normal distribution is em- ployed for analyzing an outcome based dropout model for repeated mea- surements with non-random dropout in skew regression data sets. A probit regression is considered as the conditional probability of an ob- servation to be missing given outcomes. A simulation study of using the proposed methodology and comparing it with a semi-parame...

Approximating a binomial distribution by a suitable normal distribution is a well known practice, and widely discussed in introductory level statistics books. Recently it has been shown (in Chang et al. (2008)) that the skew-normal distributions can provide a far better approximation than the normal ones. This article revisits the approximation issue and other related inferential aspects. Thoug...