Wavelet analysis of stock return energy decomposition and return comovement - a case of some central European and developed European stock markets

DSpace Repository

Show simple item record

dc.contributor.author Dajčman, Silvo
dc.contributor.author Kavkler, Alenka
dc.contributor.other Ekonomická fakulta cs
dc.date.accessioned 2014-03-04
dc.date.available 2014-03-04
dc.identifier.issn 12123609
dc.identifier.uri https://dspace.tul.cz/handle/15240/6764
dc.description.abstract In this article we investigate comovement of the three Central and Eastern European (CEE) stock markets (Slovenia, the Czech Republic and Hungary) with certain developed European stock markets (Austria, France, Germany and the United Kingdom) through the novel approach of maximal overlap discrete wavelet transform (MODWT). We use two features of MODWT to explore energy decomposition of stock market returns at different time scales and to apply methodology of [29] to study comovement between investigated stock markets. We show that most of the energy (variability) of stock market return series is captured by scale 1 (which correspond to 2–4 days return dynamics) and scale 2 (which correspond to 4-8 days return dynamics) MODWT coefficients. MODWT details are used to show that comovement between stock markets is scale-dependent and declines from raw (daily) return series to first- and second-scale reconstructed return series. The findings of the survey then have important implications for foreign financial investors who already hold international portfolios that exactly replicate those of non-Czech or non-Hungarian stock markets: international investing in the Czech or Hungarian stock markets with investment horizons corresponding to scale 2 (4 to 8 days) brings greater international diversification benefits than shorter (2 to 4 day horizon) international trading diversification strategies. The Slovenian stock market differs from the Czech and Hungarian markets also in this respect, as when the scale is increased the benefits of diversification are reduced. We also find that the volatility of Slovenian stock index returns is less synchronized with other observed stock return series. Interestingly, the Czech and Slovenian stock markets seem to comove with the Austrian stock market to a greater extent than with other developed stock markets. en
dc.format text
dc.format.extent 104-120 s. cs
dc.language.iso en
dc.publisher Technická Univerzita v Liberci cs
dc.publisher Technical university of Liberec, Czech Republic en
dc.relation.ispartof Ekonomie a Management cs
dc.relation.ispartof Economics and Management en
dc.relation.isbasedon BAE, K.H., KAROLYI, A.G. and STULZ, R.M. A new approach to measuring financial contagion. The Review of Financial Studies. 2003, Vol. 16, Iss. 13, pp. 717-763. ISSN 0893-9454.
dc.relation.isbasedon CANDELON, B., PIPLACK, J. and STRAETMANS, S. On measuring synchronization of bulls and bears: The case of East Asia. Journal of Banking and Finance. 2008, Vol. 32, Iss. 6, pp. 1022-1035. ISSN 0378-4266.
dc.relation.isbasedon CAPORALE, M.G. and SPAGNOLO, N. Stock market integration between three CEEC´s [online]. Brunel University Working Paper No. 10-9, 2010. [cit. 2011-02-03]. Available from: http://www.brunel.ac.uk/9379/efwps/1009.pdf.
dc.relation.isbasedon CEEG – CEE Stock Exchange Group. Fact sheet January 2011 [online]. Wien, 2011 [cit. 2011-20-05]. Available from: http://www.ceeseg.com.
dc.relation.isbasedon CHO J.H. and PARHIZGARI, A.M. East Asian financial contagion under DCC-GARCH. International Journal of Banking and Finance. 2008, Vol. 6, Iss. 1, pp. 16-30. ISSN 1675-7227.
dc.relation.isbasedon CORNISH, R.C., BRETHERTON, C.S. and PERCIVAL, D.B. Maximal Overlap Discrete Wavelet Statistical Analysis with Application to Atmospheric Turbulence. Boundary-Layer Meteorology. 2006, Vol. 119, Iss. 2, pp. 339-374. ISSN 0006-8314.
dc.relation.isbasedon CRAIGMILE, P.F. and PERCIVAL, D.B. Asymptotic Decorrelation of Between-Scale Wavelet Coefficients. IEEE Transactions on Information Theory. 2005, Vol. 51, Iss. 3, pp. 1039-1048. ISSN 0018-9448.
dc.relation.isbasedon CROWLEY, M.P. An intuitive guide to wavelets for economists [online]. Bank of Finland Research Discussion Paper No. 1/2005, 2005. [cit. 2011-10-05]. 71 p. (PDF). Available from: http://www.suomenpankki.fi/en/julkaisut/tutkimukset/keskustelualoitteet/Documents/0501netti.pdf. ISBN 952-462-189-4.
dc.relation.isbasedon DIDIER T., LOVE, I. and MARTÍNEZ PERÍA, M.S. What explains comovement in stock market returns during the 2007-2008 crisis? International Journal of Finance and Economic [online]. 2011, Vol. 17, Iss. 2 [cit. 2011-05-05], pp. 182-202. ISSN 1099-1158.
dc.relation.isbasedon ÉGERT, B., KOČENDA, E. Time-varying synchronization of European stock markets. Empirical Economics. 2010, Vol. 40, Iss. 2, pp. 393-407. ISSN 0377-7332.
dc.relation.isbasedon EMBRECHTS, P., MCNEIL, A.J. and STRAUMANN, D. Correlation and Dependence in Risk Management: Properties and Pitfalls. In M.A.H. DEMPSTER (ed.). Risk Management: Value at Risk and Beyond. Cambridge: Cambridge University Press, 1999. pp. 176-223. ISBN 0-521-78180-9.
dc.relation.isbasedon FERNANDEZ, V. Time scale decomposition of price transmission in international markets. Emerging Markets Finance and Trade. 2005, Vol. 41, Iss. 4, pp. 57-90. ISSN 1540-496X. [13] GARCIA, R. and TSAFACK, G. Dependence structure and extreme comovements in international equity and bond markets [online]. CIRANO Scientific Series. 2009. [cit. 2011-05-05]. 54 p. (PDF). Available from: http://www.cirano.qc.ca/pdf/publication/2009s-21.pdf. ISSN 1198-8177.
dc.relation.isbasedon GENÇAY, R., SELCUK, F. and WHITCHER, B. Scaling properties of foreign exchange volatility. Physica A: Statistical Mechanics and its Applications. 2001, Vol. 289, Iss. 1-2, pp. 249-266. ISSN 0378-4371.
dc.relation.isbasedon GENÇAY, R., SELÇUK, F. and WHITCHER, B. Differentiating intraday seasonalities through wavelet multi-scaling. Physica A. 2001, Vol. 289, Iss. 3-4, pp. 543-556. ISSN 0378-4371.
dc.relation.isbasedon GENÇAY, R., SELÇUK, F. and WHITCHER, B. An Introduction to Wavelets and Other Filtering Methods in Finance and Economics. San Diego (CA): Academic Press, 2002. ISBN 0-12-27-9670-5.
dc.relation.isbasedon GENÇAY, R., SELCUK, F. and WHITCHER, B. Systematic risk and timescales. Quantitative Finance. 2003, Vol. 3, Iss. 2, pp. 108-116. ISSN 1469-7688.
dc.relation.isbasedon GENÇAY, R., SELÇUK, F. and WHITCHER, B. Multiscale systematic risk. Journal of International Money and Finance. 2005, Vol. 24, Iss. 1, pp. 55-70. ISSN 0261-5606.
dc.relation.isbasedon GERRITS, R.J. and YUCE, A. Short- and long-term links among European and US stock markets. Applied Financial Economics. 1999, Vol. 9, Iss. 1, pp. 1-9. ISSN 0960-3107.
dc.relation.isbasedon GILMORE, G.C. and MCMANUS, G.M. International portfolio diversification: US and Central European equity markets. Emerging Markets Review. 2002, Vol. 3, Iss. 1, pp. 69-83. ISSN 1566-0141.
dc.relation.isbasedon HARRISON, B. and MOORE, W. Stock market comovement in the European Union and transition countries. Financial Studies [online]. 2009, Vol. 13, Iss. 3 [cit. 2011-05-05], pp.124-151. ISSN 2582-8654.
dc.relation.isbasedon HOROBET, A. and LUPU, R. Are Capital Markets Integrated? A Test of Information Transmission within the European Union. Romanian Journal of Economic Forecasting. 2009, Vol. 10, Iss. 2, pp. 64-80. ISSN 1582-6163.
dc.relation.isbasedon IN, F. and KIM, S. The hedge ratio and the empirical relationship between the stock and futures markets: A new approach using wavelet analysis. Journal of Business. 2006, Vol. 79, Iss. 2, pp. 799-820. ISSN 002-9398.
dc.relation.isbasedon IN, F., KIM, S., MARISETTY, V. and FAFF, R. Analyzing the performance of managed funds using the wavelet multiscaling method. Review of Quantitative Finance and Accounting. 2008, Vol. 31, Iss. 1, pp. 55-70. ISSN 1573-7179.
dc.relation.isbasedon KIM, S. and IN, F. The relationship between stock returns and inflation: new evidence from wavelet analysis. Journal of Empirical Finance. 2005, Vol. 12, Iss. 3, pp. 435-444. ISSN 0927-5398.
dc.relation.isbasedon KIM, S. and IN, F. A note on the relationship between industry returns and inflation through a multiscaling approach. Finance Research Letters. 2006, Vol. 3, Iss. 1, 73-78. ISSN 1544-6123.
dc.relation.isbasedon KIM, S. and IN, F. On the relationship between changes in stock prices and bond yields in the G7 countries: Wavelet analysis. Journal of International Financial Markets, Institutions and Money. 2007, Vol. 17, Iss. 2, pp. 167-179. ISSN 1042-4431.
dc.relation.isbasedon KOEDIJK, K., CAMPBELL, A.J.R. and KOFMAN, P. Increased correlation in bear markets. Financial Analysts Journal. 2002, Vol. 58, Iss. 1, pp. 87-94. ISSN 0015-198X.
dc.relation.isbasedon LEE, H.S. Price and volatility spillovers in stock markets: A wavelet analysis. Applied Economics Letters. 2004, Vol. 11, Iss. 3, pp.197-201. ISSN 1466-4291.
dc.relation.isbasedon LING, X. and DHESI, G. Volatility spillover and time-varying conditional correlation between the European and US stock markets. Global Economy and Finance Journal. 2010, Vol. 3, Iss. 2, pp. 148-164. ISSN 0972-9496.
dc.relation.isbasedon LONGIN, F. and SOLNIK, B. Is the correlation in international equity returns constant:1960-1990? Journal of International Money and Finance. 1995, Vol. 14, Iss. 1, pp. 3-26. ISSN 0261-5606.
dc.relation.isbasedon MALLAT, S.G. and ZHANG, Z. Matching pursuits with time-frequency dictionaries. IEEE Transactions of Signal Processing. 1993, Vol. 41, Iss. 12, pp. 3397-3415. ISSN 1053-587X.
dc.relation.isbasedon MALLIARIS, A.G. and URRUTIA, J.L. The international crash of October 1987: Causality tests. Journal of Financial and Quantitative Analysis. 1992, Vol. 27, Iss. 3, pp. 353-364. ISSN 0022-1090.
dc.relation.isbasedon NECULA, C. Modeling the dependency structure of stock index returns using a copula function. Romanian Journal of Economic Forecasting. 2010, Vol. 13, Iss. 3, pp. 93-106. ISSN 1582-6163.
dc.relation.isbasedon PAKKO, M.R. A spectral analysis of the cross-country consumption correlation puzzle. Economics Letters. 2004, Vol. 84, Iss. 3, pp. 341-347. ISSN 0165-1765.
dc.relation.isbasedon PATEV, P., KANARYAN, N. and LYROUDI, K. Stock market crises and portfolio diversification in Central and Eastern Europe. Managerial Finance. 2006, Vol. 32, Iss. 5, pp. 415-432. ISSN 0307-4358.
dc.relation.isbasedon PERCIVAL, D.B. On the Estimation of the Wavelet Variance. Biometrika. 1995, Vol. 82, Iss. 3, pp. 619-631. ISSN 0006-3444.
dc.relation.isbasedon PERCIVAL, D.B. Analysis of Geophysical Time Series Using Discrete Wavelet Transforms: An Overview. In DONNER, R.V. and BARBOSA, S.M. (Eds.). Nonlinear Time Series Analysis in the Geosciences. Applications in Climatology, Geodynamics and Solar-Terrestrial Physics. Berlin/Heidelberg: Springer, 2008. pp. 61-79. ISBN 3-540-78937-5.
dc.relation.isbasedon PERCIVAL, D.B. and MOJFELD, H.O. Analysis of subtidal coastal sea level fluctuations using wavelets. Journal of the American Statistical Association. 1997, Vol. 92, Iss. 439, pp. 868-880. ISSN 0162-1459.
dc.relation.isbasedon PERCIVAL, D.B. and WALDEN, A.T. Wavelet Methods for Time Series Analysis. New York: Cambridge University Press, 2000. ISBN 0-521-6406-7.
dc.relation.isbasedon PINHO, C. and MADALENO, M. Time frequency effects on market indices: world comovements [online]. Aveiro/Paris, Finance International Meeting AFFI – EUROFIDAI Paper, 2009 [cit. 2011-30-05]. 46 p. (PDF). Available from: http://www.affi.asso.fr/uploads/Externe/15/CTR_FICHIER_422_1259147300.pdf.
dc.relation.isbasedon RAMSEY, J. Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties. Economic Systems Research. 1999, Vol. 11, Iss. 2, pp.163-183. ISSN 0953-5314.
dc.relation.isbasedon RUA, A. and NUNES, L.C. International comovement of stock market returns: a wavelet analysis. Journal of Empirical Finance. 2009, Vol. 16, Iss. 4, pp. 632-639. ISSN 0927-5398.
dc.relation.isbasedon SCHEICHER, M. The comovements of stock markets in Hungary, Poland and the Czech Republic. International Journal of Finance & Economics. 2001, Vol. 6, Iss. 1, pp. 27-39. ISSN 1076-9307.
dc.relation.isbasedon SCHWENDER, A. The estimation of financial markets by means of regime-switching model [online]. St. Gallen, 2010. 147 p. Dissertation. University of St. Gallen, Graduate School of Business Administration, Economics, Law and Social Sciences, No. 3794 [cit. 2011-10-02]. Available from: http://www.iorcf.unisg.ch/de/Forschung/Publikationen/~/media/Internet/Content/Dateien/InstituteUndCenters/IORCF/Abschlussarbeiten/Schwendener%202010%20Diss%20The%20Estimation%20of%20Financial%20Markets%20by%20Means%20of%20a%20Regime%20Switching%20Model.ashx.SERROUKH, A., WALDEN, A.T. and PERCIVAL, D.B. Statistical Properties and Uses of the Wavelet Variance Estimator for the Scale Analysis of Time Series. Journal of the American Statistical Association. 2000, Vol. 95, Iss. 449, pp. 184-196. ISSN 0162-1459.
dc.relation.isbasedon SERWA, D. and BOHL, M.T. Financial Contagion Vulnerability and Resistance: A Comparison of European Stock Markets. Economic Systems. 2005, Vol. 29, Iss. 3, pp. 344-362. ISSN 0939-3625.
dc.relation.isbasedon SHARKASI, A., RUSKIN, H. and CRANE, M. Interrelationships among international stock market indices: Europe, Asia and the Americas. International Journal of Theoretical and Applied Finance. 2005, Vol. 8, Iss. 5, pp. 1-18. ISSN 0219-0249.
dc.relation.isbasedon SYLLIGNAKIS, M. and KOURETAS, G. Long And Short-Run Linkages In CEE Stock Markets: Implications For Portfolio Diversification And Stock Market Integration [online]. William Davidson Institute Working Papers Series, 2006 [cit. 2011-10-02]. 33 p. (PDF). Available from: http://wdi.umich.edu/files/publications/workingpapers/wp832.pdf.
dc.relation.isbasedon TSE, Y.K and TSUI, A.K. A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations. Journal of Business and Economic Statistics. 2002, Vol. 20, Iss. 3, pp. 351-362. ISSN 0735-0015.
dc.relation.isbasedon VUORENMAA, T.A. A wavelet analysis of scaling laws and long-memory in stock market volatility [online]. Helsinki: Bank of Finland Research Discussion Paper 27, 2005 [cit. 2011-10-05]. 44 p. (PDF). Available from: http://www.suomenpankki.fi/en/julkaisut/tutkimukset/keskustelualoitteet/Documents/0527netti.pdf. ISBN 952-462-254-8.
dc.relation.isbasedon XIAO, L. and DHESI, G. Volatility spillover and time-varying conditional correlation between the European and US stock markets. Global Economy and Finance Journal. 2010, Vol. 3, Iss. 2, pp. 148-164. ISSN 1834-5883.
dc.relation.isbasedon ZHOU, J. Multiscale analysis of international linkages of REIT returns and volatilities. Journal of Real Estate Financial Economics [online]. 2011-02-25. Online First [cit. 2011-05-20]. ISSN 0895-5638.
dc.rights CC BY-NC
dc.subject Payment cards en
dc.subject Efficiency en
dc.subject DEA models en
dc.subject.classification F21
dc.subject.classification F36
dc.subject.classification G11
dc.subject.classification G15
dc.title Wavelet analysis of stock return energy decomposition and return comovement - a case of some central European and developed European stock markets en
dc.type Article en
dc.date.defense 2014-03-04
dc.publisher.abbreviation TUL
dc.relation.isrefereed true
dc.identifier.doi 10.15240/tul/001/2014-1-009
dc.identifier.eissn 2336-5604
local.relation.volume 17
local.relation.issue 1
local.relation.abbreviation E&M en
local.relation.abbreviation E+M cs
local.faculty Faculty of Economics
local.citation.spage 104
local.citation.epage 120
local.access open
local.fulltext yes


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search

Browse

My Account