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GLM-methods for volatility models

Servei d'Estadística de la UAB Universitat Autonoma de Barcelona, Spain

Youngjo Lee

Department of Statistics, Seoul National University, South Korea

We propose a multivariate volatility model for the behaviour of eight international equity indices. We show that many volatility models with heavy tails in financial work can be viewed as the GLM class of models with random effects in the dispersion. Hence, the h-likelihood approach, which provides efficient and simpler algorithms for GLM class, can be used as an estimation method for models used in finance. A comparison of the h-likelihood estimators with the ML estimators is made and its relative merits are discussed.

Key Words: Generalized linear models • Lévy processes • normal inverse Gaussian distribution • likelihood for random-effect • models • portfolio selection

Statistical Modelling, Vol. 8, No. 3, 263-283 (2008)
DOI: 10.1177/1471082X0800800303


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