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Outlier Detection in GARCH Models. (2005). Ooms, Marius ; Doornik, Jurgen.
In: Tinbergen Institute Discussion Papers.
RePEc:tin:wpaper:20050092.

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  1. Correcting outliers in GARCH models: a weighted forward approach. (2019). Grossi, Luigi ; Crosato, Lisa.
    In: Statistical Papers.
    RePEc:spr:stpapr:v:60:y:2019:i:6:d:10.1007_s00362-017-0903-y.

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  2. Leverage effect in energy futures revisited. (2019). Carnero, M. Angeles ; Perez, Ana.
    In: Energy Economics.
    RePEc:eee:eneeco:v:82:y:2019:i:c:p:237-252.

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  3. The financial economics of white precious metals — A survey. (2017). Vigne, Samuel A ; Yarovaya, Larisa ; Oconnor, Fergal A ; Lucey, Brian M.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:52:y:2017:i:c:p:292-308.

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  4. Modelling Conditional Volatility and Downside Risk for Istanbul Stock Exchange. (2016). Ahmed, Doaa.
    In: Working Papers.
    RePEc:erg:wpaper:1028.

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  5. The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices. (2015). Manera, Matteo ; Behmiri, Niaz Bashiri .
    In: Working Papers.
    RePEc:fem:femwpa:2015.77.

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  6. The role of outliers and oil price shocks on volatility of metal prices. (2015). Manera, Matteo ; Behmiri, Niaz Bashiri .
    In: Resources Policy.
    RePEc:eee:jrpoli:v:46:y:2015:i:p2:p:139-150.

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  7. Understanding volatility dynamics in the EU-ETS market. (2015). Violante, Francesco ; Mansanet-Bataller, Maria ; Sanin, Maria Eugenia .
    In: Energy Policy.
    RePEc:eee:enepol:v:82:y:2015:i:c:p:321-331.

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  8. Understanding volatility dynamics in the EU-ETS market. (2015). Violante, Francesco ; Sanin Vázquez, María Eugenia ; Mansanet-Bataller, Maria .
    In: CREATES Research Papers.
    RePEc:aah:create:2015-04.

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  9. Verbesserung des Lernverhaltens durch Online-Tests: Ein Jahr später. (2014). Mangold, Benedikt ; Pleier, Thomas ; Stubinger, Johannes ; Nolzen, Jan ; Brug, Christoph .
    In: Discussion Papers.
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  10. Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013. (2014). Darné, Olivier ; Charles, Amelie.
    In: Post-Print.
    RePEc:hal:journl:hal-01122507.

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  11. Volatility persistence in crude oil markets. (2014). Darné, Olivier ; CHARLES, Amelie ; Darne, Olivier.
    In: Post-Print.
    RePEc:hal:journl:hal-00940312.

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  12. Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013. (2014). Darné, Olivier ; CHARLES, Amelie.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:43:y:2014:i:c:p:188-199.

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  13. Volatility persistence in crude oil markets. (2014). Darné, Olivier ; CHARLES, Amelie ; Darne, Olivier.
    In: Energy Policy.
    RePEc:eee:enepol:v:65:y:2014:i:c:p:729-742.

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  14. The role of regulatory uncertainty in certificate markets: A case study of the Swedish/Norwegian market. (2014). Fagiani, Riccardo ; Hakvoort, Rudi.
    In: Energy Policy.
    RePEc:eee:enepol:v:65:y:2014:i:c:p:608-618.

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  15. Modelling Correlation in Carbon and Energy Markets. (2011). Koenig, P..
    In: Cambridge Working Papers in Economics.
    RePEc:cam:camdae:1123.

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  16. Wavelet-based detection of outliers in financial time series. (2010). Veiga, Helena ; Grane, Aurea .
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:54:y:2010:i:11:p:2580-2593.

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  17. Outliers in Garch models and the estimation of risk measures. (2010). Veiga, Helena ; Grane, Aurea .
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws100502.

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  18. Extreme Value Theory Filtering Techniques for Outlier Detection. (2009). Olmo, Jose.
    In: Working Papers.
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  19. Wavelet-based detection of outliers in volatility models. (2009). Veiga, Helena ; Grane, Aurea .
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws090403.

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  20. Volatility Switching in Shanghai Stock Exchange: Does regulation help reduce volatility?. (2008). Zhang, Dayong ; Barassi, Marco ; Dickinson, David.
    In: MPRA Paper.
    RePEc:pra:mprapa:70352.

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  21. Multimodality in GARCH regression models. (2008). Ooms, Marius ; Doornik, Jurgen.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:24:y:2008:i:3:p:432-448.

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  22. Clustering techniques applied to outlier detection of financial market series using a moving window filtering algorithm. (2008). Gregori, Josep Fortiana ; Puigvert, Josep Maria .
    In: Working Paper Series.
    RePEc:ecb:ecbwps:2008948.

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  23. Exchange rate volatility and regime change: A Visegrad comparison. (2006). Valachy, Juraj ; Kočenda, Evžen.
    In: Journal of Comparative Economics.
    RePEc:eee:jcecon:v:34:y:2006:i:4:p:727-753.

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References

References cited by this document

  1. Abraham, B. and N. Yatawara (1988). A score test for detection of time series outliers. Journal of Time Series Analysis 9(2), 109–119.

  2. Bollerslev, T. (1986). Generalised autoregressive conditional heteroskedasticity. Journal of Econometrics 51, 307–327.

  3. Bollerslev, T. (1987). A conditional heteroskedastic time series model for speculative prices and rates of return. Review of Economics and Statistics 69, 542–47.

  4. Bollerslev, T., R. F. Engle, and D. B. Nelson (1994). ARCH models. In R. F. Engle and D. L. McFadden (Eds.), Handbook of Econometrics, Volume 4, Chapter 49, pp. 2959–3038. Amsterdam: North-Holland.
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  5. Chen, C. and L. M. Liu (1993). Joint estimation of model parameters and outlier effects in time series. Journal of the American Statistical Association 88, 284–297.
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  6. Doornik, J. A. (2001). Object-Oriented Matrix Programming using Ox (4th ed.). London: Timberlake Consultants Press.
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  7. Doornik, J. A. and M. Ooms (2000). Multimodality in the GARCH regression model. mimeo, Nuffield College.
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  8. Engle, R. F. (1982). Autoregressive conditional heteroscedasticity, with estimates of the variance of United Kingdom inflation. Econometrica 50, 987–1007.

  9. Franses, P. H. and D. van Dijk (2000). Outlier detection in GARCH models. Econometric Institute Report EI-9926/RV, Erasmus University Rotterdam.
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  10. Gourieroux, C. (1997). ARCH Models and Financial Applications. New York: Springer Verlag.
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  11. Hotta, L. K. and R. S. Tsay (1998). Outliers in GARCH processes. mimeo, IMECC, Brazil and University of Chicago.
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  12. Leadbetter, M. R., G. Lindgren, and H. Rootz en (1983). Extremes and Related Properties of Random Sequences and Processes. Springer Series in Statistics. Springer-Verlag, New York, Heidelberg, Berlin.
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  13. Mood, A. M., F. A. Graybill, and D. C. Boes (1974). Introduction to the Theory of Statistics, Third Edition. McGraw-Hill.
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  14. Sakata, S. and H. White (1998). High breakdown point conditional dispersion estimation with application to s&p 500 daily returns volatility. Econometrica 66, 529–567.

  15. Shephard, N. (1996). Statistical aspects of ARCH and stochastic volatility. In D. R. Cox, D. V. Hinkley, and O. E. Barndorff-Nielsen (Eds.), Time Series Models in Econometrics, Finance and Other Fields, pp. 1–67. London: Chapman & Hall.
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  16. such that for large x and large T , MT has a Type I extreme value limiting distribution. Our approximations are based on this distribution type. Leadbetter, Lindgren, and Rootz en (1983, Chapters 1,3) show that Type I extreme value (or Gumbel-) limiting distributions apply much more generally. The Xs need not be exponential and independent, although these are the cases where the asymptotic theory works well, also in moderately sized samples.
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