IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v86y2005i3p427-433.html
   My bibliography  Save this article

Functional Central Limit Theorem approximations and the distribution of the Dickey-Fuller test with strongly heteroskedastic data

Author

Listed:
  • Valkanov, Rossen

Abstract

No abstract is available for this item.

Suggested Citation

  • Valkanov, Rossen, 2005. "Functional Central Limit Theorem approximations and the distribution of the Dickey-Fuller test with strongly heteroskedastic data," Economics Letters, Elsevier, vol. 86(3), pages 427-433, March.
  • Handle: RePEc:eee:ecolet:v:86:y:2005:i:3:p:427-433
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165-1765(04)00316-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Markku Lanne, 2002. "Testing The Predictability Of Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 407-415, August.
    2. Richardson, Matthew & Stock, James H., 1989. "Drawing inferences from statistics based on multiyear asset returns," Journal of Financial Economics, Elsevier, vol. 25(2), pages 323-348, December.
    3. Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
    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. Su, Jen-Je & Cheung, Adrian (Wai-Kong) & Roca, Eduardo, 2014. "Does Purchasing Power Parity hold? New evidence from wild-bootstrapped nonlinear unit root tests in the presence of heteroskedasticity," Economic Modelling, Elsevier, vol. 36(C), pages 161-171.
    2. Nikolay Gospodinov & Ye Tao, 2011. "Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 379-405, August.
    3. Jürgen Wolters & Uwe Hassler, 2006. "Unit Root Testing," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 4, pages 41-56, Springer.

    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. Maynard, Alex & Shimotsu, Katsumi, 2009. "Covariance-Based Orthogonality Tests For Regressors With Unknown Persistence," Econometric Theory, Cambridge University Press, vol. 25(1), pages 63-116, February.
    2. Ventosa-Santaulària, Daniel & Noriega, Antonio E., 2015. "Long-run monetary neutrality under stochastic and deterministic trends," Economic Modelling, Elsevier, vol. 47(C), pages 372-382.
    3. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    4. Hjalmarsson, Erik, 2008. "Interpreting long-horizon estimates in predictive regressions," Finance Research Letters, Elsevier, vol. 5(2), pages 104-117, June.
    5. Erik Hjalmarsson, 2006. "Inference in Long-Horizon Regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.).
    6. Hjalmarsson, Erik, 2005. "On the Predictability of Global Stock Returns," Working Papers in Economics 161, University of Gothenburg, Department of Economics.
    7. Nelson C. Mark & Donggyu Sul, 2004. "The Use of Predictive Regressions at Alternative Horizons in Finance and Economics," Finance 0409032, University Library of Munich, Germany.
    8. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    9. Chiquoine, Benjamin & Hjalmarsson, Erik, 2009. "Jackknifing stock return predictions," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 793-803, December.
    10. Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2008. "The Myth of Long-Horizon Predictability," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1577-1605, July.
    11. David McMillan & Alan Speight, 2006. "Non-linear long horizon returns predictability: evidence from six south-east Asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(2), pages 95-111, June.
    12. Henkel, Sam James & Martin, J. Spencer & Nardari, Federico, 2011. "Time-varying short-horizon predictability," Journal of Financial Economics, Elsevier, vol. 99(3), pages 560-580, March.
    13. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
    14. Ke-Li Xu & Junjie Guo, 2021. "A New Test for Multiple Predictive Regression," CAEPR Working Papers 2022-001 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    15. Ferson, Wayne E. & Sarkissian, Sergei & Simin, Timothy, 2008. "Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 331-353, June.
    16. J. Annaert & W. Van Hyfte, 2006. "Long-Horizon Mean Reversion for the Brussels Stock Exchange: Evidence for the 19th Century," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/376, Ghent University, Faculty of Economics and Business Administration.
    17. Nikolaos Mitianoudis & Theologos Dergiades, 2016. "Stock Prices Predictability at Long-horizons: Two Tales from the Time-Frequency Domain," Discussion Paper Series 2016_04, Department of Economics, University of Macedonia, revised Dec 2016.
    18. John Hatgioannides & Spiros Mesomeris, 2005. "Mean Reversion in Equity Prices: the G-7 Evidence," Money Macro and Finance (MMF) Research Group Conference 2005 64, Money Macro and Finance Research Group.
    19. Park, Cheolbeom, 2010. "When does the dividend-price ratio predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 81-101, January.
    20. Mototsugu Shintani & Tomoyoshi Yabu & Daisuke Nagakura, 2008. "Spurious Regressions in Technical Trading: Momentum or Contrarian?," IMES Discussion Paper Series 08-E-09, Institute for Monetary and Economic Studies, Bank of Japan.

    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:eee:ecolet:v:86:y:2005:i:3:p:427-433. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.