Advanced Search
MyIDEAS: Login to save this article or follow this journal

Interdependence Between Some Major European Stock Markets - A Wavelet Lead/Lag Analysis

Contents:

Author Info

  • Silvo Dajčman

Abstract

This paper investigates multiscale interdependence between the stock markets of Germany, Austria, France, and the United Kingdom. Wavelet energy additive decomposition was analyzed to investigate which scales capture the most energy (volatility), whereas a wavelet cross-correlation estimator was used to analyze comovement and lead/lag relationship between stock markets´ return dynamics on a scale-by-scale basis. The main findings of the paper are as follows. First, major financial market crises had a significant impact on return volatility of investigated stock markets. Among them, the global financial crisis of 2007-2008 had the greatest and the most durable impact. Second, the lowest scale (associated with stock markets´ return dynamics over a 2-4 days horizon) and the second lowest scale (associated with stock markets´ return dynamics over 4-8 days horizon) MODWT (maximal overlap discrete wavelet transform) decompositions of stock markets´ returns captured the greatest share (together about 70-80%) of indices´ returns volatility. Third, comovement between stock market returns is a scale-dependent phenomenon. Fourth, a strong comovement between stock market returns of Germany, France, and the United Kingdom exists at all scales, while the Austrian stock market is less correlated with the three biggest stock markets in Europe. Fifth, the dynamics of stock market returns seems to be well time-synchronized at daily (raw returns) and the lowest scale (scale ) return decomposition as most of the return innovations are transmitted between stock markets intraday. Sixth, at the highest investigated scale (associated with stock markets´ return dynamics over a 64-128 days horizon), significant leads and lags between dynamics of stock markets´ returns were detected. The time-synchronization of the stock markets´ return dynamics for investments of 64 to 128 days horizon is less perfect than for investments of shorter investment horizons.

Download Info

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.vse.cz/polek/download.php?jnl=pep&pdf=439.pdf
Download Restriction: Restriction: free of charge

File URL: http://www.vse.cz/pep/abstrakt.php?IDcl=439
Download Restriction: Restriction: free of charge

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.

Bibliographic Info

Article provided by University of Economics, Prague in its journal Prague Economic Papers.

Volume (Year): 2013 (2013)
Issue (Month): 1 ()
Pages: 28-49

as in new window
Handle: RePEc:prg:jnlpep:v:2013:y:2013:i:1:id:439:p:28-49

Contact details of provider:
Postal: nam. W. Churchilla 4, 130 67 Praha 3
Phone: (02) 24 09 51 11
Fax: (02) 24 22 06 57
Web page: http://www.vse.cz/
More information through EDIRC

Order Information:
Postal: Editorial office Prague Economic Papers, University of Economics, nám. W. Churchilla 4, 130 67 Praha 3, Czech Republic
Email:
Web: http://www.vse.cz/pep/

Related research

Keywords: wavelet cross-correlation; wavelet analysis; stock markets; return spillovers;

Find related papers by JEL classification:

References

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. Alessandro Cardinali, 2009. "A Generalized Multiscale Analysis Of The Predictive Content Of Eurodollar Implied Volatilities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 1-18.
  2. Francis In & Sangbae Kim, 2006. "The Hedge Ratio and the Empirical Relationship between the Stock and Futures Markets: A New Approach Using Wavelet Analysis," The Journal of Business, University of Chicago Press, vol. 79(2), pages 799-820, March.
  3. Kee-Hong Bae & G. Andrew Karolyi & Rene M. Stulz, 2000. "A New Approach to Measuring Financial Contagion," NBER Working Papers 7913, National Bureau of Economic Research, Inc.
  4. Vuorenmaa , Tommi, 2005. "A wavelet analysis of scaling laws and long-memory in stock market volatility," Research Discussion Papers 27/2005, Bank of Finland.
  5. Francis In & Sangbae Kim & Vijaya Marisetty & Robert Faff, 2008. "Analysing the performance of managed funds using the wavelet multiscaling method," Review of Quantitative Finance and Accounting, Springer, vol. 31(1), pages 55-70, July.
  6. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
  7. Ramazan Genay & Faruk Seļuk & Brandon Whitcher, 2003. "Systematic risk and timescales," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 108-116.
  8. Richard D. F. Harris & Anirut Pisedtasalasai, 2006. "Return and Volatility Spillovers Between Large and Small Stocks in the UK," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9-10), pages 1556-1571.
  9. Turbelin, Grégory & Ngae, Pierre & Grignon, Michel, 2009. "Wavelet cross-correlation analysis of wind speed series generated by ANN based models," Renewable Energy, Elsevier, vol. 34(4), pages 1024-1032.
  10. Mazin A. M. Al Janabi & Abdulnasser Hatemi-J & Manuchehr Irandoust, 2010. "Modeling Time-Varying Volatility and Expected Returns: Evidence from the GCC and MENA Regions," Emerging Markets Finance and Trade, M.E. Sharpe, Inc., vol. 46(5), pages 39-47, September.
  11. Viviana Fernandez, 2004. "Time-Scale Decomposition of Price Transmission in International Markets," Documentos de Trabajo 189, Centro de Economía Aplicada, Universidad de Chile.
  12. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
  13. Aslanidis, Nektarios & Savva, Christos S., 2008. "Stock market integration between new EU member states and the Euro-zone," Working Papers 2072/13263, Universitat Rovira i Virgili, Department of Economics.
  14. Gencay, Ramazan & Selcuk, Faruk & Whitcher, Brandon, 2005. "Multiscale systematic risk," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 55-70, February.
  15. Robert-Jan Gerrits & Ayse Yuce, 1999. "Short- and long-term links among European and US stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 9(1), pages 1-9.
  16. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-62, July.
  17. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Scaling properties of foreign exchange volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 249-266.
  18. Campbell, Rachel & Koedijk, Kees & Kofman, Paul, 2002. "Increased Correlation in Bear markets: A Downside Risk Perspective," CEPR Discussion Papers 3172, C.E.P.R. Discussion Papers.
  19. 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.
  20. Marco Gallegati, 2005. "A Wavelet Analysis of MENA Stock Markets," Finance 0512027, EconWPA.
  21. Olan Henry, 2002. "Long memory in stock returns: some international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 725-729.
  22. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
  23. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Differentiating intraday seasonalities through wavelet multi-scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 543-556.
Full references (including those not matched with items on IDEAS)

Citations

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:prg:jnlpep:v:2013:y:2013:i:1:id:439:p:28-49. 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: (Vaclav Subrta).

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.