Reference : A robust statistical approach to select adequate error distributions for financial r...
Scientific journals : Article
Business & economic sciences : Quantitative methods in economics & management
http://hdl.handle.net/2268/194534
A robust statistical approach to select adequate error distributions for financial returns
English
Hambuckers, julien mailto [Université de Liège > HEC-Ecole de gestion : UER > Statistique appliquée à la gestion et à l'économie >]
Heuchenne, Cédric mailto [Université de Liège > HEC-Ecole de gestion : UER > Statistique appliquée à la gestion et à l'économie >]
2017
Journal of Applied Statistics
Routledge
44
1
137-161
Yes (verified by ORBi)
International
0266-4763
1360-0532
[en] error distribution ; nonparametric volatility ; model misspecification ; goodness-of-fit ; skewed-t distribution ; NIG distribution ; hyperbolic distribution
[en] In this article, we propose a robust statistical approach to select an appropriate error distribution, in a classical multiplicative heteroscedastic model. In a first step, unlike to the traditional approach, we don't use any GARCH-type estimation of the conditional variance. Instead, we propose to use a recently developed nonparametric procedure (Mercurio and Spokoiny, 2004): the Local Adaptive Volatility Estimation (LAVE). The motivation for using this method is to avoid a possible model misspecification for the conditional variance. In a second step, we suggest a set of estimation and model selection procedures (Berk-Jones tests, kernel density-based selection, censored likelihood score, coverage probability) based on the so-obtained residuals. These methods enable to assess the global fit of a set of distributions as well as to focus on their behavior in the tails, giving us the capacity to map the strengths and weaknesses of the candidate distributions. A bootstrap procedure is provided to compute the rejection regions in this semiparametric context. Finally, we illustrate our methodology throughout a small simulation study and an application on three time series of daily returns (UBS stock returns, BOVESPA returns and EUR/USD exchange rates)
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
Researchers
http://hdl.handle.net/2268/194534
10.1080/02664763.2016.1165803

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