VOLATILITY AND VAR FORECASTING FOR THE IBEX-35 STOCK-RETURN INDEX USING FIGARCH-TYPE PROCESSES AND DIFFERENT EVALUATION CRITERIA

Trino Ñíguez Grau

Working Papers. Serie AD from Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie)

Abstract: In this paper I analyze the relative performance of Gaussian and Student-t GARCH and FIGARCH type models for volatility and Value-at-Risk forecasting of daily stock-returns using data from the Spanish equity index IBEX-35. The in-sample analysis shows that the Student-t FIAPARCH process provides a better fit than the nested models. Regarding the out-of-sample volatility forecasting, both the Gaussian- and the t-FIAPARCH processes show the best performance, although it is not possible to discriminate between them. As for the models' capacity for VaR forecasting, different results are obtained according to the evaluation criteria considered, although if the aim is regulatory VaR it is shown that the Student-t FIAPARCH model would be clearly the most recommendable.

Keywords: APARCH; Fractional Integration; Leverage Effect; Long Memory; Value-at-risk (search for similar items in EconPapers)
JEL-codes: C32 C52 C53 G15 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2003-09
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Persistent link: https://EconPapers.repec.org/RePEc:ivi:wpasad:2003-33

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