IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Long memory properties in return and volatility: Evidence from the Korean stock market

  • Kang, Sang Hoon
  • Yoon, Seong-Min

In this paper, we study the dual long memory property of the Korean stock market. For this purpose, the ARFIMA–FIGARCH model is applied to two daily Korean stock price indices (KOSPI and KOSDAQ). Our empirical results indicate that long memory dynamics in the returns and volatility can be adequately estimated by the joint ARFIMA–FIGARCH model. We also found that the assumption of a skewed Student-t distribution is better for incorporating the tendency of asymmetric leptokurtosis in a return distribution.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/pii/S0378437107008084
Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 385 (2007)
Issue (Month): 2 ()
Pages: 591-600

as
in new window

Handle: RePEc:eee:phsmap:v:385:y:2007:i:2:p:591-600
Contact details of provider: Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
  2. Yoon, Seong-Min & Choi, J.S. & Christopher Lee, C. & Yum, Myung-Kul & Kim, Kyungsik, 2006. "Dynamical volatilities for yen–dollar exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 359(C), pages 569-575.
  3. Beine, Michel & Laurent, Sebastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 641-660, December.
  4. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  5. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
  6. Bormetti, Giacomo & Cisana, Enrica & Montagna, Guido & Nicrosini, Oreste, 2007. "A non-Gaussian approach to risk measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 532-542.
  7. Scalas, Enrico, 1998. "Scaling in the market of futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 253(1), pages 394-402.
  8. Dionisio, Andreia & Menezes, Rui & Mendes, Diana A., 2007. "On the integrated behaviour of non-stationary volatility in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 58-65.
  9. Galluccio, S. & Caldarelli, G. & Marsili, M. & Zhang, Y.-C., 1997. "Scaling in currency exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 245(3), pages 423-436.
  10. Michel Beine & Sébastien Laurent & Christelle Lecourt, 2002. "Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates," ULB Institutional Repository 2013/10443, ULB -- Universite Libre de Bruxelles.
  11. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  12. Fengzhong Wang & Kazuko Yamasaki & Shlomo Havlin & H. Eugene Stanley, 2005. "Scaling and memory of intraday volatility return intervals in stock market," Papers physics/0511101, arXiv.org.
  13. Cajueiro, Daniel O & Tabak, Benjamin M, 2004. "The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 521-537.
  14. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
  15. Xiu, Jin & Jin, Yao, 2007. "Empirical study of ARFIMA model based on fractional differencing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 138-154.
  16. Ivanov, Plamen Ch. & Podobnik, Boris & Lee, Youngki & Stanley, H.Eugene, 2001. "Truncated Lévy process with scale-invariant behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 154-160.
  17. Richard T. Baillie & Young Wook Han & Tae-Go Kwon, 2002. "Further Long Memory Properties of Inflationary Shocks," Southern Economic Journal, Southern Economic Association, vol. 68(3), pages 496-510, January.
  18. Kim, Kyungsik & Yoon, Seong-Min, 2004. "Multifractal features of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 272-278.
  19. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2005. "Institutional Investors and Stock Market Volatility," NBER Working Papers 11722, National Bureau of Economic Research, Inc.
  20. Podobnik, Boris & Ivanov, Plamen Ch. & Grosse, Ivo & Matia, Kaushik & Eugene Stanley, H., 2004. "ARCH–GARCH approaches to modeling high-frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 216-220.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:385:y:2007:i:2:p:591-600. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.