[en] In this article, we propose a robust methodology to select the most appropriate error distribution candidate, 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 given distribution as well as to focus on its behavior in the tails. Finally, we illustrate our methodology on three time series (UBS stock returns, BOVESPA returns and EUR/USD exchange rates).
Research Center/Unit :
Centre for Quantitative Methods and Operations Management (QuantOM)
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Hambuckers, julien ; Université de Liège - ULiège > HEC-Ecole de gestion : UER > Statistique appliquée à la gestion et à l'économie
Heuchenne, Cédric ; Université de Liège - ULiège > HEC-Ecole de gestion : UER > Statistique appliquée à la gestion et à l'économie
Language :
English
Title :
A new methodological approach for error distributions selection in Finance
Publication date :
April 2014
Number of pages :
26
Event name :
Skewness, Heavy Tails, Market Crashes, and Dynamics conference
Event organizer :
The Faculty of Economics of Cambridge University and the Institute for New Economic Thinking (INET) Society for Financial Econometrics (SoFiE)
Event place :
Cambridge, United Kingdom
Event date :
du 29 au 29 avril 2014
Audience :
International
Peer reviewed :
Peer reviewed
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office (grant P7/06 StUDyS)