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Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data

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Abstract

In this paper, we contribute to the literature on international stock market comovement. The novelty of our approach lies in usage of wavelet tools to high-frequency financial market data, which allows us to understand the relationship between stock market returns in a different way. Major part of economic time series analysis is done in time or frequency domain separately. Wavelet analysis can combine these two fundamental approaches, so we can work in time-frequency domain. Using wavelet power spectra and wavelet coherence, we have uncovered interesting dynamics of cross-correlations between Central European and Western European stock markets using high-frequency data. Our findings provide possibility of a new approach to financial risk modeling.

Suggested Citation

  • Jozef Barunik & Lukas Vacha & Ladislav Krištoufek, 2011. "Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data," Working Papers IES 2011/22, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jun 2011.
    • Handle: RePEc:fau:wpaper:wp2011_22
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    1. John Beirne & Guglielmo Maria Caporale & Marianne Schulze-Ghattas & Nicola Spagnolo, 2013. "Volatility Spillovers and Contagion from Mature to Emerging Stock Markets," Review of International Economics, Wiley Blackwell, vol. 21(5), pages 1060-1075, November.
    2. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    3. Aguiar-Conraria, Luís & Azevedo, Nuno & Soares, Maria Joana, 2008. "Using wavelets to decompose the time–frequency effects of monetary policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2863-2878.
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    Cited by:

    1. Mensi, Walid & Hkiri, Besma & Al-Yahyaee, Khamis H. & Kang, Sang Hoon, 2018. "Analyzing time–frequency co-movements across gold and oil prices with BRICS stock markets: A VaR based on wavelet approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 74-102.
    2. McNevin, Bruce D. & Nix, Joan, 2018. "The beta heuristic from a time/frequency perspective: A wavelet analysis of the market risk of sectors," Economic Modelling, Elsevier, vol. 68(C), pages 570-585.
    3. Ijaz Younis & Cheng Longsheng & Muhammad Farhan Basheer & Ahmed Shafique Joyo, 2020. "Stock market comovements among Asian emerging economies: A wavelet-based approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-23, October.
    4. Çekin, Semih Emre & Hkiri, Besma & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "The relationship between monetary policy and uncertainty in advanced economies: Evidence from time- and frequency-domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 70-87.
    5. Aloui, Chaker & Hkiri, Besma & Nguyen, Duc Khuong, 2016. "Real growth co-movements and business cycle synchronization in the GCC countries: Evidence from time-frequency analysis," Economic Modelling, Elsevier, vol. 52(PB), pages 322-331.
    6. Masih, Mansur & Majid, Hamdan Abdul, 2013. "Comovement of Selected International Stock Market Indices:A Continuous Wavelet Transformation and Cross Wavelet Transformation Analysis," MPRA Paper 58313, University Library of Munich, Germany.
    7. Taheri Bazkhaneh , Saleh & Ehsani , Mohammad Ali & Gilak Hakimabadi , Mohammad Taqi & Farzinvash , Asodollah, 2018. "Analysis of the Relationship between the Business Cycle and Inflation Gap in Time-Frequency Domain," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(3), pages 401-422, July.
    8. Jusoh, Hashim & Bacha, Obiyathulla & Masih, Abul Mansur M., 2014. "Multi-scale Lead-Lag Relationship between the Stock and Futures Markets: Malaysia as a Case Study," MPRA Paper 56954, University Library of Munich, Germany.
    9. Avishek Bhandari, 2020. "A wavelet analysis of inter-dependence, contagion and long memory among global equity markets," Papers 2003.14110, arXiv.org.
    10. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2021. "Time-varying relationship between conventional and unconventional monetary policies and risk aversion: international evidence from time- and frequency-domains," Empirical Economics, Springer, vol. 61(6), pages 2963-2983, December.
    11. Avishek BHANDARI, 2017. "Wavelets based multiscale analysis of select global equity returns," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(613), W), pages 75-88, Winter.
    12. repec:ipg:wpaper:2014-568 is not listed on IDEAS
    13. M. Kannadhasan & Debojyoti Das, 2019. "Has Co-Movement Dynamics in Brazil, Russia, India, China and South Africa (BRICS) Markets Changed After Global Financial Crisis? New Evidence from Wavelet Analysis," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(1), pages 1-26.
    14. Ben-Salha, Ousama & Hkiri, Besma & Aloui, Chaker, 2018. "Sectoral energy consumption by source and output in the U.S.: New evidence from wavelet-based approach," Energy Economics, Elsevier, vol. 72(C), pages 75-96.

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    More about this item

    Keywords

    comovement; stock market; wavelet analysis; wavelet coherence;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F30 - International Economics - - International Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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