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Does the Efficient Market Hypothesis Hold?: Evidence from Six Transition Economies

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  • TIMOTEJ JAGRIC
  • BORIS PODOBNIK
  • MARKO KOLANOVIC

Abstract

In this paper, a wavelet analysis of long-range dependence (LRD) based on the Hurst exponent is presented. An estimator is used to perform an analysis of LRD in the capital markets of six transition economies. The results suggest that we can divide the stock markets into two groups: markets with strong LRD (the Czech Republic, Hungary, Russia, and Slovenia), and markets with no or only a weak form of LRD (Poland and Slovakia). Additionally, if the Hurst exponent is estimated on a sliding time window, the results show some additional properties, which we believe are representative for the markets in transition economies.

Suggested Citation

  • Timotej Jagric & Boris Podobnik & Marko Kolanovic, 2005. "Does the Efficient Market Hypothesis Hold?: Evidence from Six Transition Economies," Eastern European Economics, Taylor & Francis Journals, vol. 43(4), pages 79-103, August.
    • Handle: RePEc:mes:eaeuec:v:43:y:2005:i:4:p:79-103
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    1. Ning, Ye & Han, Chenyu & Wang, Yiming, 2018. "The multifractal properties of Euro and Pound exchange rates and comparisons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 578-587.
    2. Carlos León, 2012. "Implied probabilities of default from Colombian money market spreads: The Merton Model under equity market informational constraints," Borradores de Economia 743, Banco de la Republica de Colombia.
    3. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Analysis and comparison of the multifractality and efficiency of Chinese stock market: Evidence from dynamics of major indexes in different boards," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C), pages 1-1.
    4. Caraiani, Petre, 2012. "Characterizing emerging European stock markets through complex networks: From local properties to self-similar characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(13), pages 3629-3637.
    5. Phooi M’ng, Jacinta Chan, 2018. "Dynamically Adjustable Moving Average (AMA’) technical analysis indicator to forecast Asian Tigers’ futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 336-345.
    6. Ruan, Qingsong & Yang, Bingchan & Ma, Guofeng, 2017. "Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 91-108.
    7. Avishek Bhandari & Bandi Kamaiah, 2021. "Long Memory and Fractality Among Global Equity Markets: a Multivariate Wavelet Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 23-37, March.
    8. Quinton Morris & Gary Van Vuuren & Paul Styger, 2009. "Further Evidence Of Long Memory In The South African Stock Market," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 81-101, March.
    9. Arshad, Shaista & Rizvi, Syed Aun R. & Ghani, Gairuzazmi Mat & Duasa, Jarita, 2016. "Investigating stock market efficiency: A look at OIC member countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 402-413.
    10. Laura Raisa Miloş & Cornel Haţiegan & Marius Cristian Miloş & Flavia Mirela Barna & Claudiu Boțoc, 2020. "Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical Evidence from Seven Central and Eastern European Markets," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    11. Faheem Aslam & Wahbeeah Mohti & Paulo Ferreira, 2020. "Evidence of Intraday Multifractality in European Stock Markets during the Recent Coronavirus (COVID-19) Outbreak," IJFS, MDPI, vol. 8(2), pages 1-13, May.
    12. Jagric, Timotej & Markovic-Hribernik, Tanja & Strasek, Sebastjan & Jagric, Vita, 2010. "The power of market mood -- Evidence from an emerging market," Economic Modelling, Elsevier, vol. 27(5), pages 959-967, September.
    13. Petre Caraiani, 2012. "Evidence of Multifractality from Emerging European Stock Markets," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    14. Mejra Festic & Alenka Kavkler & Silvo Dajcman, 2012. "Long memory in the Croatian and Hungarian stock market returns," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 30(1), pages 115-139.
    15. Chaker Aloui & Duc Khuong Nguyen, 2014. "On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach," Applied Economics, Taylor & Francis Journals, vol. 46(22), pages 2611-2622, August.
    16. Ferreira, Paulo, 2018. "Efficiency or speculation? A time-varying analysis of European sovereign debt," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1295-1308.
    17. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.

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