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Forecasting volatility with outliers in GARCH models

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  • Amélie Charles

    (Audencia Recherche - Audencia Business School)

Abstract

In this paper, we detect and correct abnormal returns in 17 French stocks returns and the French index CAC40 from additive-outlier detection method in GARCH models developed by Franses and Ghijsels (1999) and extended to innovative outliers by Charles and Darné (2005). We study the effects of outlying observations on several popular econometric tests. Moreover, we show that the parameters of the equation governing the volatility dynamics are biased when we do not take into account additive and innovative outliers. Finally, we show that the volatility forecast is better when the data are cleaned of outliers for several step-ahead forecasts (short, medium- and long-term) even if we consider a GARCH-t process

Suggested Citation

  • Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Post-Print hal-00765466, HAL.
    • Handle: RePEc:hal:journl:hal-00765466
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    Citations

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    Cited by:

    1. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    2. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    3. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    4. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    5. Manh Ha Nguyen & Olivier Darné, 2018. "Forecasting and risk management in the Vietnam Stock Exchange," Working Papers halshs-01679456, HAL.
    6. Vasiliki Chatzikonstanti & Michail Karoglou, 2022. "Can black swans be tamed with a flexible mean‐variance specification?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3202-3227, July.
    7. WenShwo Fang & Stephen M. Miller, 2014. "Output Growth and its Volatility: The Gold Standard through the Great Moderation," Southern Economic Journal, John Wiley & Sons, vol. 80(3), pages 728-751, January.
    8. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    9. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    10. Amélie Charles & Olivier Darné, 2021. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 15(2), pages 419-442, May.
    11. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    12. Grané Chávez, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    14. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The role of outliers and oil price shocks on volatility of metal prices," Resources Policy, Elsevier, vol. 46(P2), pages 139-150.
    15. Alex Huang, 2011. "Volatility Modeling by Asymmetrical Quadratic Effect with Diminishing Marginal Impact," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 301-330, March.
    16. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    17. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    18. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.

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