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Short Patches of Outliers, ARCH and Volatility Modeling

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  • Philip Hans Franses
  • Dick van Dijk

    (Erasmus University Rotterdam)

  • André Lucas

    (Vrije Universiteit Amsterdam)

Abstract

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span two samples of 5 years ranging from 1986 to 1995. Using asymptotic arguments and Monte Carlo simulations, in which we evaluate our empirical method, we show that patches of outliers can have significant effects on test outcomes. Our main empirical result is that we find spurious GARCH in about 40% of the cases, while in many other cases we find evidence of GARCH even though such sequences of extraordinary observations seem to be present.

Suggested Citation

  • Philip Hans Franses & Dick van Dijk & André Lucas, 1998. "Short Patches of Outliers, ARCH and Volatility Modeling," Tinbergen Institute Discussion Papers 98-057/4, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:19980057
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    References listed on IDEAS

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    1. Lee, John H. H., 1991. "A Lagrange multiplier test for GARCH models," Economics Letters, Elsevier, vol. 37(3), pages 265-271, November.
    2. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.
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    7. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    2. Lanne, Markku & Saikkonen, Pentti, 2007. "A Multivariate Generalized Orthogonal Factor GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 61-75, January.
    3. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2004. "Spurious And Hidden Volatility," Working Papers. Serie AD 2004-45, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    4. Miralles-Quirós, José Luis & Daza-Izquierdo, Julio, 2015. "Do DOW returns really influence the intraday Spanish stock market behavior?," Research in International Business and Finance, Elsevier, vol. 33(C), pages 99-126.
    5. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    6. Juncal Cunado Eizaguirre & Javier Gomez Biscarri & Fernando Perez de Gracia Hidalgo, 2009. "Financial liberalization, stock market volatility and outliers in emerging economies," Applied Financial Economics, Taylor & Francis Journals, vol. 19(10), pages 809-823.
    7. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    8. 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).
    9. Par Sjolander, 2009. "Are the Basel II requirements justified in the presence of structural breaks?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(12), pages 985-998.
    10. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    11. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    12. Amado Peir, 2016. "Changes in the Unconditional Variance and Autoregressive Conditional Heteroscedasticity," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1338-1343.
    13. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723.
    14. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
    15. Pavel Cizek & Wolfgang Härdle, 2006. "Robust Econometrics," SFB 649 Discussion Papers SFB649DP2006-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    17. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    18. Par Sjolander, 2010. "A stationary unbiased finite sample ARCH-LM test procedure," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 1019-1033.
    19. Jose Luis Miralles-Marcelo & Jose Luis Miralles-Quiros & Maria del Mar Miralles-Quiros, 2010. "Intraday linkages between the Spanish and the US stock markets: evidence of an overreaction effect," Applied Economics, Taylor & Francis Journals, vol. 42(2), pages 223-235.

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