Testing Linearity in an
AR Errors-in-variables Model with
Application to Stochastic Volatility
D. Feldmann, W. Härdle, C. Hafner, M. Hoffmann, O. Lepski, A. Tsybakov
Applicationes Mathematicae 30 (2003), 389-412
MSC: 62G07, 62G10, 62M10.
DOI: 10.4064/am30-4-3
Abstract
Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given data set, a statistical test is required. In this paper, we develop such a test of a linear hypothesis versus a general composite nonparametric alternative using the state space representation of the SV model as an errors-in-variables AR(1) model. The power of the test is analyzed. We provide a simulation study and apply the test to the HFDF96 data set. Our results confirm a linear AR(1) structure in log-volatility for the analyzed stock indices S&P500, Dow Jones Industrial Average and for the exchange rate DEM/USD.
Authors
- D. FeldmannSFB 373 and
Institut für Statistik und Ökonometrie
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität zu Berlin
Spandauer Str. 1
D-10178 Berlin, Germany
- W. HärdleSFB 373 and
Institut für Statistik und Ökonometrie
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität zu Berlin
Spandauer Str. 1
D-10178 Berlin, Germany
- C. HafnerSFB 373 and
Institut für Statistik und Ökonometrie
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität zu Berlin
Spandauer Str. 1
D-10178 Berlin, Germany
- M. HoffmannLaboratoire de probabilités
et modèles aléatoires
Université Paris 7
pl. Jussieu 2
F-75252 Paris, France
e-mail
- O. LepskiCentre des Mathématiques
et d'Informatique
Université, Aix-Marseille 1
39, rue F. Joliot-Curie
F-13453 Marseille, France
e-mail
- A. TsybakovLaboratoire de probabilités
et modèles aléatoires
Université Paris 6
pl. Jussieu 4, BP 188
F-75252 Paris, France
e-mail