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Contagion among Central and Eastern European stock markets during the financial crisis

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  • Jozef Barunik
  • Lukas Vacha

Abstract

This paper contributes to the literature on international stock market comovements and contagion. The novelty of our approach lies in application of wavelet tools to high-frequency financial market data, which allows us to understand the relationship between stock markets in a time-frequency domain. While major part of economic time series analysis is done in time or frequency domain separately, wavelet analysis combines these two fundamental approaches. Wavelet techniques uncover interesting dynamics of correlations between the Central and Eastern European (CEE) stock markets and the German DAX at various investment horizons. The results indicate that connection of the CEE markets to the leading market of the region is significantly lower at higher frequencies in comparison to the lower frequencies. Contrary to previous literature, we document significantly lower contagion between the CEE markets and the German DAX after the large 2008 stock market crash.

Suggested Citation

  • Jozef Barunik & Lukas Vacha, 2013. "Contagion among Central and Eastern European stock markets during the financial crisis," Papers 1309.0491, arXiv.org, revised Sep 2013.
  • Handle: RePEc:arx:papers:1309.0491
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    Cited by:

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    2. Cengiz KARATAS & Gazanfer UNAL & Adil YILMAZ, 2017. "Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-18, June.
    3. Adil Yilmaz & Gazanfer Unal, 2016. "Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-19, December.
    4. Reboredo, Juan C. & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2015. "An analysis of dependence between Central and Eastern European stock markets," Economic Systems, Elsevier, vol. 39(3), pages 474-490.
    5. Jasmina Ðuraškovic & Slavica Manic & Dejan Živkov, 2019. "Multiscale Volatility Transmission and Portfolio Construction Between the Baltic Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(2), pages 211-235, April.
    6. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
    7. Jovan Njegic & Milica Stankovic & Dejan Živkov, 2019. "What Wavelet-Based Quantiles Can Suggest about the Stocks-Bond Interaction in the Emerging East Asian Economies?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(1), pages 95-119, February.
    8. Yilmaz, Adil & Unal, Gazanfer & Karatasoglu, Cengiz, 2016. "Wavelet Based Analysis Of Major Real Estate Markets," MPRA Paper 74083, University Library of Munich, Germany.
    9. Dejan Zivkov & Marina Gajic-Glamoclija & Jelena Kovacevic & Sanja Loncar, 2020. "Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(5), pages 461-486, November.
    10. Dejan Zivkov & Suzana Balaban & Jasmina Djuraskovic, 2018. "What Multiscale Approach Can Tell About the Nexus Between Exchange Rate and Stocks in the Major Emerging Markets?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(5), pages 491-512, October.
    11. RNuket Kirci Cevik & Sel Dibooglu & Ali M. Kutan, 2016. "Real and Financial Sector Studies in Central and Eastern Europe: A Review," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(1), pages 2-31, February.
    12. Emre Kahraman & Gazanfer Unal, 2016. "Multiple Wavelet Coherency Analysis and Forecasting of Metal Prices," Papers 1602.01960, arXiv.org.
    13. Dejan Živkov & Jovan Njegiæ & Mirela Momèiloviæ, 2018. "Bidirectional spillover effect between Russian stock index and the selected commodities," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(1), pages 29-53.

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    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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