This paper proposes a method for estimating the VaR of a portfolio based on copula and extreme value theory. Each return is modeled by ARMA-GARCH models with the joint distribution of innovations modeled by copula. The marginal distributions are modeled by the generalized Pareto distribution in...

In this article, we propose a multivariate Pascal mixture regression model as an alternative to understand the association between multivariate count response variables and their covariates. When compared to the copula approach, this proposed class of regression models is not only less complex...

A new multivariate distribution possessing arbitrarily parametrized univariate Pareto margins is introduced. Unlike the probability law of Asimit et al. (2010) [Asimit, V., Furman, E. and Vernic, R. (2010). “On a multivariate Pareto distribution,” Insurance: Mathematics and Economics 46(2),...

We check the empirical importance of some generalisations of the conditional distribution in M-GARCH case. A copula M-GARCH model with coordinate free conditional distribution is considered, as a continuation of research concerning specification of the conditional distribution in multivariate...

In the present paper we study the dynamics of penalization parameter λ of the least absolute shrinkage and selection operator (Lasso) method proposed by Tibshirani (1996) and extended into quantile regression context by Li and Zhu (2008). The dynamic behaviour of the parameter λ can be...

There is a paramount importance of Job Satisfaction of the employees of an organization for the smooth functioning of its work. It has substantial impact on workers' performance. RMG workers of Bangladesh are enormous in number and instrumental to the economic growth of Bangladesh. But the...

This paper proposes a multivariate least squares Mallows averaging approach to the issue of forecast combination by vector autoregressive (VAR) model fitting. Our approach extends the current literature on frequentist least squares model/forecast averaging methods, in particular Hansen (2008),...

Pair-copula constructions are flexible models for the dependence in a random vector that have attracted a lot of interest in recent years. In this paper, we use generalized additive models to extend pair-copula constructions to allow for effects of covariates on the dependence parameters. We let...

Previously we introduced Singular Spectrum Analysis SSA and its multivariate extension MSSA as a powerful tool for cleaning data. Here we compare MSSA with the data filling algorithm M-REM (Multivariate Regularized Expectation Maximization). We compare theoretical methodology, numerical...

We propose sparse versions of multivariate GARCH models that allow for volatility and correlation spillover effects across assets. The proposed models are generalizations of existing diagonal DCC and BEKK models, yet they remain estimable for high-dimensional systems of asset returns. To cope...