In univariate data, there exist standard procedures for identifying dominating features that produce the largest number of observations. However, in the multivariate setting, the situation is quite different. This paper aims to provide tools and methods for detecting dominating directional...

Sudden and uncertain events often cause cross-contagion of risk among various sectors of the macroeconomy. This paper introduces the stochastic volatility shock that follows a thick-tailed Student's t-distribution into a high-order approximate dynamic stochastic general equilibrium (DSGE) model...

A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which...

In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate...

A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which...

In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate...

This paper investigates how the downside tail risk of stock returns is differentiated cross-sectionally. Stock returns follow heavy-tailed distributions with downside tail risk determined by the tail shape and scale. If safety-first investors are concerned with sufficiently large downside...