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Volatility And Var Forecasting For The Ibex-35 Stock-Return Index Using Figarch-Type Processes And Different Evaluation Criteria

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Author Info
Trino-Manuel Ñíguez (Universidad de Alicante)
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.

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Publisher Info
Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2003-33.

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Length: 35 pages
Date of creation: Sep 2003
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Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2003-33

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Related research
Keywords: APARCH Fractional Integration Leverage Effect Long Memory Value-at-risk

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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