IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v8y2004i2n3.html
   My bibliography  Save this article

Analyzing Financial Time Series through Robust Estimators

Author

Listed:
  • Grossi Luigi

    (University of Parma)

Abstract

In this paper we suggest an extension of the forward search methodology to GARCH models which are often used for forecasting stock market volatility. It is frequently found that estimated residuals from GARCH models have excess kurtosis, even when one allows for conditional t-distributed errors. Some papers have appeared on outlier detection in GARCH models but the proposed methods are iterative and may suffer from masking effects. The forward search is a method for determining the effect of outliers on fitted parameters and for detecting also masked outliers. In the case of GARCH models outliers are strictly related to extreme observations which are responsible for the well-known volatility clustering of financial returns. It is possible, through the forward search, to visualize the effect on estimated parameters of patches of extremal observations.

Suggested Citation

  • Grossi Luigi, 2004. "Analyzing Financial Time Series through Robust Estimators," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-15, May.
    • Handle: RePEc:bpj:sndecm:v:8:y:2004:i:2:n:3
    DOI: 10.2202/1558-3708.1224
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1558-3708.1224
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1558-3708.1224?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    2. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    3. Franses, Philip Hans & Ghijsels, Hendrik, 1999. "Additive outliers, GARCH and forecasting volatility," International Journal of Forecasting, Elsevier, vol. 15(1), pages 1-9, February.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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).
    3. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2008. "Estimating and Forecasting GARCH Volatility in the Presence of Outiers," Working Papers. Serie AD 2008-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    2. Akhtaruzzaman, Md & Shamsuddin, Abul & Easton, Steve, 2014. "Dynamic correlation analysis of spill-over effects of interest rate risk and return on Australian and US financial firms," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 378-396.
    3. Yilmaz, Tolgahan, 2010. "Improving Portfolio Optimization by DCC And DECO GARCH: Evidence from Istanbul Stock Exchange," MPRA Paper 27314, University Library of Munich, Germany.
    4. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    5. Harris, Richard D.F. & Mazibas, Murat, 2013. "Dynamic hedge fund portfolio construction: A semi-parametric approach," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 139-149.
    6. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    7. Bodnar, Taras & Hautsch, Nikolaus, 2012. "Copula-based dynamic conditional correlation multiplicative error processes," SFB 649 Discussion Papers 2012-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Kuper, Gerard H. & Lestano, 2007. "Dynamic conditional correlation analysis of financial market interdependence: An application to Thailand and Indonesia," Journal of Asian Economics, Elsevier, vol. 18(4), pages 670-684, August.
    9. Zagaglia, Paolo, 2014. "International portfolio allocation with European fixed-income funds: What scope for Italian funds?," MPRA Paper 57878, University Library of Munich, Germany.
    10. Marshall, Andrew & Maulana, Tubagus & Tang, Leilei, 2009. "The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 250-259, December.
    11. Emerson Fernandes Marcal & Pedro Valls Pereira & Diogenes Manoel Leiva Martin & Wilson Toshiro Nakamura, 2011. "Evaluation of contagion or interdependence in the financial crises of Asia and Latin America, considering the macroeconomic fundamentals," Applied Economics, Taylor & Francis Journals, vol. 43(19), pages 2365-2379.
    12. Yaya, OlaOluwa S. & Lukman, Adewale F. & Vo, Xuan Vinh, 2022. "Persistence and volatility spillovers of bitcoin price to gold and silver prices," Resources Policy, Elsevier, vol. 79(C).
    13. Dr. Martin Indergand & Eric Jondeau & Dr. Andreas Fuster, 2022. "Measuring and stress-testing market-implied bank capital," Working Papers 2022-02, Swiss National Bank.
    14. Alhaj-Yaseen, Yaseen S. & Lam, Eddery & Barkoulas, John T., 2014. "Price discovery for cross-listed firms with foreign IPOs," International Review of Financial Analysis, Elsevier, vol. 31(C), pages 80-87.
    15. Bathia, Deven & Demirer, Riza & Gupta, Rangan & Kotzé, Kevin, 2021. "Unemployment fluctuations and currency returns in the United Kingdom: Evidence from over one and a half century of data," Journal of Multinational Financial Management, Elsevier, vol. 61(C).
    16. Marçal, Emerson Fernandes & Pereira, Pedro L. Valls, 2008. "Testing the Hypothesis of Contagion Using Multivariate Volatility Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 28(2), November.
    17. Mirzosaid Sultonov, 2020. "The Impacts of International Political and Economic Events on Japanese Financial Markets," IJFS, MDPI, vol. 8(3), pages 1-10, July.
    18. Mark, Joy, 2011. "Gold and the US dollar: Hedge or haven?," Finance Research Letters, Elsevier, vol. 8(3), pages 120-131, September.
    19. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    20. Afees Adebare Salisu & Raymond Swaray & Tirimisiyu Oloko, 2017. "US stocks in the presence of oil price risk: Large cap vs. Small cap," Economics and Business Letters, Oviedo University Press, vol. 6(4), pages 116-124.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sndecm:v:8:y:2004:i:2:n:3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.