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Persistent link: https://www.econbiz.de/10005238555
In this paper, we introduce a novel class of skewed multivariate distributions and, more generally, a method of building such a class on the basis of univariate skewed distributions. The method is based on a general linear transformation of a multidimensional random variable with independent...
Persistent link: https://www.econbiz.de/10005556332
We introduce a general perspective on the introduction of skewness into symmetric distributions. Making use of inverse probability integral transformations we provide a constructive representation of skewed distributions, where the skewing mechanism and the original symmetric distributions are...
Persistent link: https://www.econbiz.de/10005556401
We consider classes of multivariate distributions which can model skewness and are closed under orthogonal transformations. We review two classes of such distributions proposed in the literature and focus our attention on a particular, yet quite flexible, subclass of one of these classes....
Persistent link: https://www.econbiz.de/10005407985
Continuous-time stochastic volatility models are becoming an increasingly popular way to describe moderate and high-frequency financial data. Barndorff-Nielsen and Shephard (2001a) proposed a class of models where the volatility behaves according to an Ornstein–Uhlenbeck (OU) process, driven...
Persistent link: https://www.econbiz.de/10009455776
We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior...
Persistent link: https://www.econbiz.de/10005012896
This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty...
Persistent link: https://www.econbiz.de/10005062558
This paper develops Bayesian approaches to deal with linear elliptical regression models that differ in the covariance structure. A pretest method based on posterior model probabilities is compared with a pooling approach, and the data density is defined as a mixture of elliptical densities with...
Persistent link: https://www.econbiz.de/10005066254
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