IDEAS home Printed from https://ideas.repec.org/a/rfa/aefjnl/v7y2020i6p101-107.html
   My bibliography  Save this article

Volatility Distribution of the DJSTOXXE50 Index

Author

Listed:
  • Yasemin Ulu

Abstract

In this paper using data from 1995-2005 on 5-minute intraday returns, we construct a model free estimate of the daily realized volatility for the DJSTOXXE50 index. We compute the unconditional volatility distribution of the DJSTOXXE50 index by a nonparametric kernel estimation method. Our results indicate that the unconditional volatility distribution of the DJSTOXXE50 returns are leptokurtic and highly skewed to the right. The logarithmic standard deviations seem to be approximately Gaussian. Our results are inline with previous research for individual DJIA equity return volatility and for Japanese index, Nikkei 225

Suggested Citation

  • Yasemin Ulu, 2020. "Volatility Distribution of the DJSTOXXE50 Index," Applied Economics and Finance, Redfame publishing, vol. 7(6), pages 101-107, December.
  • Handle: RePEc:rfa:aefjnl:v:7:y:2020:i:6:p:101-107
    as

    Download full text from publisher

    File URL: http://redfame.com/journal/index.php/aef/article/download/5065/5259
    Download Restriction: no

    File URL: http://redfame.com/journal/index.php/aef/article/view/5065
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 159-179, September.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    4. Ole E. Barndorff‐Nielsen & Neil Shephard, 2001. "Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 167-241.
    Full references (including those not matched with items on IDEAS)

    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. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    3. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    5. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2008. "Quantile forecasts of daily exchange rate returns from forecasts of realized volatility," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 729-750, September.
    6. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    7. Vladimir Tsenkov, 2009. "Financial Markets Modelling," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 87-96.
    8. Torben G. ANDERSEN & Tim BOLLERSLEV & Nour MEDDAHI, 2002. "Correcting The Errors : A Note On Volatility Forecast Evaluation Based On High-Frequency Data And Realized Volatilities," Cahiers de recherche 21-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    10. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0504009, University Library of Munich, Germany, revised 17 Jan 2006.
    11. David McMillan & Isabel Ruiz & Alan Speight, 2010. "Correlations and spillovers among three euro rates: evidence using realised variance," The European Journal of Finance, Taylor & Francis Journals, vol. 16(8), pages 753-767.
    12. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    13. Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized volatility or price range: Evidence from a discrete simulation of the continuous time diffusion process," Economic Modelling, Elsevier, vol. 30(C), pages 212-216.
    14. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    15. Robert Brooks & Robert Faff & Sirimon Treepongkaruna & Eliza Wu, 2015. "Do Sovereign Re-Ratings Destabilize Equity Markets during Financial Crises? New Evidence from Higher Return Moments," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 42(5-6), pages 777-799, June.
    16. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
    17. Virbickaitė, Audronė & Frey, Christoph & Macedo, Demian N., 2020. "Bayesian sequential stock return prediction through copulas," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    18. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
    19. Aurea Grané & Helena Veiga, 2012. "Asymmetry, realised volatility and stock return risk estimates," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(2), pages 147-164, August.
    20. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:rfa:aefjnl:v:7:y:2020:i:6:p:101-107. 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: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.