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The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis

Villani, Mattias; Larsson, Rolf - 2004

which allows for skewness in the form of contraction/dilation along a subset of the prinicpal axis. The paper derives some … properties for this distribution, including its moment generating function, multivariate skewness and kurtosis. Maximum … likelihood estimation is discussed and a complete Bayesian analysis of the multivariate split normal distribution is developed. …

Persistent link: https://www.econbiz.de/10010321327

Flexible Fat-tailed Vector Autoregression

Karlsson, Sune; Mazur, Stepan - 2020

We propose a general class of multivariate fat-tailed distributions which includes the normal, t and Laplace distributions as special cases as well as their mixture. Full conditional posterior distributions for the Bayesian VAR-model are derived and used to construct a MCMC-sampler for the joint...

Persistent link: https://www.econbiz.de/10012654459

Objective Bayesian meta-analysis based on generalized multivariate random effects model

Bodnar, Olha; Bodnar, Taras - 2021

Objective Bayesian inference procedures are derived for the parameters of the multivariate random effects model generalized to elliptically contoured distributions. The posterior for the overall mean vector and the between-study covariance matrix is deduced by assigning two noninformative priors...

Persistent link: https://www.econbiz.de/10012654475

Vector autoregression models with skewness and heavy tails

Karlsson, Sune; Mazur, Stepan; Nguyen, Hoang - 2021

to take into account skewness and heavy tails. Tools for Bayesian inference and model selection using a Gibbs sampler are … provided. In an empirical study, we present evidence of skewness and heavy tails for monthly macroe- conomic variables. The … analysis also gives a clear message that skewness should be taken into account for better predictions during recessions and …

Persistent link: https://www.econbiz.de/10012654478

Methods for computing marginal data densities from the gibbs output

Fuentes-Albero, Cristina; Melosi, Leonardo - 2011

We introduce two new methods for estimating the Marginal Data Density (MDD) from the Gibbs output, which are based on exploiting the analytical tractability condition. Such a condition requires that some parameter blocks can be analytically integrated out from the conditional posterior...

Persistent link: https://www.econbiz.de/10010282843

Maximum likelihood estimation of the symmetric and asymmetric exponential power distribution

Bottazzi, Giulio; Secchi, Angelo - 2008

We introduce a new 5-parameter family of distributions, the Asymmetric Exponential Power (AEP), able to cope with asymmetries and leptokurtosis and at the same time allowing for a continuous variation from non-normality to normality. We prove that the Maximum Likelihood (ML) estimates of the AEP...

Persistent link: https://www.econbiz.de/10010328554

Models for heavy-tailed asset returns

Borak, Szymon; Misiorek, Adam; Weron, Rafał - 2010

Many of the concepts in theoretical and empirical finance developed over the past decades - including the classical portfolio theory, the Black-Scholes-Merton option pricing model or the RiskMetrics variance-covariance approach to VaR - rest upon the assumption that asset returns follow a normal...

Persistent link: https://www.econbiz.de/10010281502

Parametric estimation of risk neutral density functions

Grith, Maria; Krätschmer, Volker - 2010

This chapter deals with the estimation of risk neutral distributions for pricing index options resulting from the … hypothesis of the risk neutral valuation principle. After justifying this hypothesis, we shall focus on parametric estimation ….r.t. reviewed parametric statistical families used for direct estimation. Additionally, we shall introduce the Fast Fourier …

Persistent link: https://www.econbiz.de/10010281587

Extreme value theory as a theoretical background for power law behavior

Alfarano, Simone; Lux, Thomas - 2010

therefore allows its application in many diverse fields. Moreover, this theory offers new powerful techniques for the estimation …

Persistent link: https://www.econbiz.de/10010277948

The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation

Basturk, Nalan; Hoogerheide, Lennart; Opschoor, Anne; … - 2012

This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...

Persistent link: https://www.econbiz.de/10010326521