IDEAS home Printed from https://ideas.repec.org/a/taf/jnlbes/v29y2011i2p282-294.html
   My bibliography  Save this article

Infinite Density at the Median and the Typical Shape of Stock Return Distributions

Author

Listed:
  • Chirok Han
  • Jin Seo Cho
  • Peter C. B. Phillips

Abstract

Statistics are developed to test for the presence of an asymptotic discontinuity (or infinite density or peakedness) in a probability density at the median. The approach makes use of work by Knight (1998) on L 1 estimation asymptotics in conjunction with nonparametric kernel density estimation methods. The size and power of the tests are assessed, and conditions under which the tests have good performance are explored in simulations. The new methods are applied to stock returns of leading companies across major U.S. industry groups. The results confirm the presence of infinite density at the median as a new significant empirical evidence for stock return distributions.

Suggested Citation

  • Chirok Han & Jin Seo Cho & Peter C. B. Phillips, 2011. "Infinite Density at the Median and the Typical Shape of Stock Return Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 282-294, April.
    • Handle: RePEc:taf:jnlbes:v:29:y:2011:i:2:p:282-294
    DOI: 10.1198/jbes.2010.07327
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1198/jbes.2010.07327
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1198/jbes.2010.07327?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    2. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Rustam Ibragimov, 2005. "On Efficiency of Linear Estimators Under Heavy-Tailedness," Harvard Institute of Economic Research Working Papers 2085, Harvard - Institute of Economic Research.
    5. Rogers, Alan J., 2001. "Least Absolute Deviations Regression Under Nonstandard Conditions," Econometric Theory, Cambridge University Press, vol. 17(4), pages 820-852, August.
    6. Rustam Ibragimov & Johan Walden, 2006. "The Limits of Diversification When Losses May Be Large," Harvard Institute of Economic Research Working Papers 2104, Harvard - Institute of Economic Research.
    7. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    8. Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(5), pages 793-813, December.
    9. Cohen, Kalman J. & Hawawini, Gabriel A. & Maier, Steven F. & Schwartz, Robert A. & Whitcomb, David K., 1983. "Friction in the trading process and the estimation of systematic risk," Journal of Financial Economics, Elsevier, vol. 12(2), pages 263-278, August.
    10. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2551-2569, August.
    11. Kalman J. Cohen & Gabriel A. Hawawini & Steven F. Maier & Robert A. Schwartz & David K. Whitcomb, 1983. "Estimating and Adjusting for the Intervalling-Effect Bias in Beta," Management Science, INFORMS, vol. 29(1), pages 135-148, January.
    12. Dimson, Elroy, 1979. "Risk measurement when shares are subject to infrequent trading," Journal of Financial Economics, Elsevier, vol. 7(2), pages 197-226, June.
    13. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2003. "A theory of power-law distributions in financial market fluctuations," Nature, Nature, vol. 423(6937), pages 267-270, May.
    14. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    15. repec:cup:etheor:v:23:y:2007:i:03:p:501-517 is not listed on IDEAS
    16. Phillips, P.C.B., 1991. "A Shortcut to LAD Estimator Asymptotics," Econometric Theory, Cambridge University Press, vol. 7(4), pages 450-463, December.
    17. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Scholarly Articles 2624460, Harvard University Department of Economics.
    18. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
    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. Cho, Jin Seo & Kim, Tae-hwan & Shin, Yongcheol, 2015. "Quantile cointegration in the autoregressive distributed-lag modeling framework," Journal of Econometrics, Elsevier, vol. 188(1), pages 281-300.
    2. Cho, Jin Seo & Han, Chirok & Phillips, Peter C.B., 2010. "Lad Asymptotics Under Conditional Heteroskedasticity With Possibly Infinite Error Densities," Econometric Theory, Cambridge University Press, vol. 26(3), pages 953-962, June.
    3. Byung-hill Jun & Hosin Song, 2019. "Tests for Detecting Probability Mass Points," Korean Economic Review, Korean Economic Association, vol. 35, pages 205-248.

    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. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    2. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    3. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    4. Koutmos, Gregory, 1998. "Asymmetries in the Conditional Mean and the Conditional Variance: Evidence From Nine Stock Markets," Journal of Economics and Business, Elsevier, vol. 50(3), pages 277-290, May.
    5. Chollete, Loran & de la Pena , Victor & Lu, Ching-Chih, 2009. "International Diversification: An Extreme Value Approach," UiS Working Papers in Economics and Finance 2009/26, University of Stavanger.
    6. Estrada, Javier, 2000. "The temporal dimension of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(2), pages 189-204.
    7. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    8. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    9. Ibragimov, Rustam & Walden, Johan, 2008. "Portfolio diversification under local and moderate deviations from power laws," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 594-599, April.
    10. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    11. Chenglu Jin & Thomas Conlon & John Cotter, 2023. "Co-Skewness across Return Horizons," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1483-1518.
    12. De Santis, Giorgio & imrohoroglu, Selahattin, 1997. "Stock returns and volatility in emerging financial markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 561-579, August.
    13. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2004. "The Use of GARCH Models in VaR Estimation," MPRA Paper 96332, University Library of Munich, Germany.
    14. Chelley-Steeley, Patricia L. & Steeley, James M., 2014. "Portfolio size, non-trading frequency and portfolio return autocorrelation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 56-77.
    15. Ankudinov, Andrei & Ibragimov, Rustam & Lebedev, Oleg, 2017. "Sanctions and the Russian stock market," Research in International Business and Finance, Elsevier, vol. 40(C), pages 150-162.
    16. S. Sanfelici & M. E. Mancino, 2008. "Covariance estimation via Fourier method in the presence of asynchronous trading and microstructure noise," Economics Department Working Papers 2008-ME01, Department of Economics, Parma University (Italy).
    17. Albert Corhay & Alireza Tourani Rad, 1993. "Return Interval, Firm Size And Systematic Risk On The Dutch Stock Market," Review of Financial Economics, John Wiley & Sons, vol. 2(2), pages 19-28, March.
    18. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    19. Rustam Ibragimov & Johan Walden, 2011. "Value at risk and efficiency under dependence and heavy-tailedness: models with common shocks," Annals of Finance, Springer, vol. 7(3), pages 285-318, August.
    20. Ibragimov, Rustam, 2008. "Heavy-tailedness and threshold sex determination," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2804-2810, November.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:taf:jnlbes:v:29:y:2011:i:2:p:282-294. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UBES20 .

    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.