The sequence ≥nd of nth degree stochastic dominances for d-dimensional distribution functions is defined. It is shown that, under some regularity conditions, ≥nd implies ≥nd−1 for the (d−1) - dimensional marginals. Also some necessary conditions for ≥nd are established. These...

We document five novel empirical findings on the well-known potential ordering drawback associated with the time-varying parameter vector autoregression with stochastic volatility developed by Cogley and Sargent (2005) and Primiceri (2005), CSP-SV. First, the ordering does not affect point...

In this paper, our proposal is to combine univariate ARMA models to produce a variant of the VARMA model that is much more easily implementable and does not involve certain complications. The original model is reduced to a series of univariate problems and a copula – like term (a...

In this paper we exploit properties of the likelihood function of the stochastic volatility model to show that it can be approximated accurately and efficiently using a response surface methodology. The approximation is across the plausible range of parameter values and all possible data and is...

We propose a new multivariate model to capture the presence of jumps in mean and conditional variance in the returns of oil prices and companies in this sector. The model is based on the presence of common factors associated with jumps in mean and variance, as it performs a decomposition of the...

Asset prices exhibit characteristics that significantly deviate from log-normality and display time-varying stochastics. There is ample evidence of jumps in one asset price or market leading to jumps in other assets' prices or markets. We propose a multivariate jump diffusion model with...