Volatility and VaR Forecasting in the Madrid Stock Exchange

Ñíguez, T.M. (2008) Volatility and VaR Forecasting in the Madrid Stock Exchange. Spanish Economic Review, 10 (3). pp. 169-196. ISSN 1435-5469

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Official URL: https://dx.doi.org/10.1007/s10108-007-9030-6


This paper provides an empirical study to assess the forecasting performance of a wide range of models for predicting volatility and VaR in the Madrid Stock Exchange. The models performance was measured by using different loss functions and criteria. The results show that FIAPARCH processes capture and forecast more accurately the dynamics of IBEX-35 returns volatility. It is also observed that assuming a heavy-tailed distribution does not improve models ability for predicting volatility. However, when the aim is forecasting VaR, we find evidence of that the Student’s t FIAPARCH outperforms the models it nests the lower the target quantile.

Item Type: Article
Uncontrolled Keywords: FIAPARCH, Heavy-tailed distributions, Leverage effect, Long memory, VaR;
Subjects: University of Westminster > Westminster Business School
SWORD Depositor: repository@westminster.ac.uk
Depositing User: repository@westminster.ac.uk
Date Deposited: 09 Mar 2016 16:21
Last Modified: 13 Sep 2016 13:04
URI: http://westminsterresearch.wmin.ac.uk/id/eprint/16662

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