Cookies?
Library Header Image
LSE Research Online LSE Library Services

Estimation and testing of dynamic models with generalised hyperbolic innovations

Mencia, Javier F. and Sentana, Enrique (2004) Estimation and testing of dynamic models with generalised hyperbolic innovations. Financial Markets Group Discussion Papers (502). Financial Markets Group, The London School of Economics and Political Science, London, UK.

[img]
Preview
PDF - Published Version
Download (1MB) | Preview

Abstract

We analyse the Generalised Hyperbolic distribution as a model for fat tails and asymmetries in multivariate conditionally heteroskedastic dynamic regression models. We provide a standardised version of this distribution, obtain analytical expressions for the log-likelihood score, and explain how to evaluate the information matrix. In addition, we derive tests for the null hypotheses of multivariate normal and Student t innovations, and decompose them into skewness and kurtosis components, from which we obtain more powerful one-sided versions. Finally, we present an empirical illustration with UK sectorial stock returns, which suggests that their conditional distribution is asymmetric and leptokurtic.

Item Type: Monograph (Discussion Paper)
Official URL: http://fmg.lse.ac.uk
Additional Information: © 2004 The Authors
Divisions: Financial Markets Group
Subjects: H Social Sciences > HG Finance
H Social Sciences > HB Economic Theory
JEL classification: C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection
C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
Date Deposited: 06 Aug 2009 09:19
Last Modified: 15 Sep 2023 22:58
URI: http://eprints.lse.ac.uk/id/eprint/24742

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics