Automated model selection in finance: General-to-speci c modelling of the mean and volatility speci cations
Alvaro Escribano () and
No 2011-09, Working Papers from Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales
General-to-Specific (GETS) modelling has witnessed major advances over the last decade thanks to the automation of multi-path GETS specification search. However, several scholars have argued that the estimation complexity associated with financial models constitutes an obstacle to multi-path GETS modelling in finance. Making use of a recent result on log-GARCH Models, we provide and study simple but general and flexible methods that automate financial multi-path GETS modelling. Starting from a general model where the mean specification can contain autoregressive (AR) terms and explanatory variables, and where the exponential volatility specification can include log-ARCH terms, asymmetry terms, volatility proxies and other explanatory variables, the algorithm we propose returns parsimonious mean and volatility specifications. The finite sample properties of the methods are studied by means of extensive Monte Carlo simulations, and two empirical applications suggest the methods are very useful in practice.
Keywords: general-to-specific; specification search; model selection; finance; volatility (search for similar items in EconPapers)
JEL-codes: C32 C51 C52 E44 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ets
Note: This paper is included in the IMDEA Social Sciences Working Paper Series through the Bank of Spain Excellence Programme
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Published in Oxford Bulletin of Economics and Statistics
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Persistent link: https://EconPapers.repec.org/RePEc:imd:wpaper:wp2011-09
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