Bootstrap prediction for returns and volatilities in GARCH models

Authors:
Lorenzo Pascual;Juan Romo;Esther Ruiz
Affiliations:
Hidro-Cantábrico, Serrano Galvache 56, Centro Empresarial Parque Nort, 28033 Madrid, Spain;Departamento de Estadística, Universidad Carlos III de Madrid, C/Madrid 126, 28903 Getafe, Spain;Departamento de Estadística, Universidad Carlos III de Madrid, C/Madrid 126, 28903 Getafe, Spain
Venue:
Computational Statistics & Data Analysis
Year:
2006

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Abstract

A new bootstrap procedure to obtain prediction densities of returns and volatilities of GARCH processes is proposed. Financial market participants have shown an increasing interest in prediction intervals as measures of uncertainty. Furthermore, accurate predictions of volatilities are critical for many financial models. The advantages of the proposed method are that it allows incorporation of parameter uncertainty and does not rely on distributional assumptions. The finite sample properties are analyzed by an extensive Monte Carlo simulation. Finally, the technique is applied to the Madrid Stock Market index, IBEX-35.