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Are European equity markets efficient? New evidence from fractal analysis

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Cited by:

  1. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
  2. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2022. "Persistence in ESG and conventional stock market indices," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(4), pages 678-703, October.
  3. Jin, Xiaoye, 2016. "The impact of 2008 financial crisis on the efficiency and contagion of Asian stock markets: A Hurst exponent approach," Finance Research Letters, Elsevier, vol. 17(C), pages 167-175.
  4. Taro Ikeda, 2017. "Fractal analysis revisited: The case of the US industrial sector stocks," Economics Bulletin, AccessEcon, vol. 37(2), pages 666-674.
  5. Oussama Tilfani & My Youssef El Boukfaoui, 2020. "Multifractal Analysis of African Stock Markets During the 2007–2008 US Crisis," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-31, January.
  6. Mishelle Doorasamy & Prince Kwasi Sarpong, 2018. "Fractal Market Hypothesis and Markov Regime Switching Model: A Possible Synthesis and Integration," International Journal of Economics and Financial Issues, Econjournals, vol. 8(1), pages 93-100.
  7. Mynhardt, H. R. & Plastun, Alex & Makarenko, Inna, 2014. "Behavior of Financial Markets Efficiency During the Financial Market Crisis: 2007-2009," MPRA Paper 58942, University Library of Munich, Germany.
  8. Bachar Fakhry & Christian Richter, 2018. "Does the Federal Constitutional Court Ruling Mean the German Financial Market is Efficient?," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 4(2), pages 111-125.
  9. Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
  10. Wahbeeah Mohti & Andreia Dionísio & Paulo Ferreira & Isabel Vieira, 2019. "Frontier markets’ efficiency: mutual information and detrended fluctuation analyses," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 551-572, September.
  11. Adelina Gschwandtner & Michael Hauser, 2016. "Profit persistence and stock returns," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3538-3549, August.
  12. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun, 2017. "Long Memory and Data Frequency in Financial Markets," Discussion Papers of DIW Berlin 1647, DIW Berlin, German Institute for Economic Research.
  13. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
  14. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
  15. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
  16. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
  17. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.
  18. Horta, Paulo & Lagoa, Sérgio & Martins, Luís, 2014. "The impact of the 2008 and 2010 financial crises on the Hurst exponents of international stock markets: Implications for efficiency and contagion," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 140-153.
  19. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
  20. Kedong YIN & Hengda ZHANG & Wenbo ZHANG & Qian WEI, 2013. "Fractal Analysis of the Gold Market in China," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 144-163, October.
  21. Fan, Xinghua & Lv, Xiangxiang & Yin, Jiuli & Tian, Lixin & Liang, Jiaochen, 2019. "Multifractality and market efficiency of carbon emission trading market: Analysis using the multifractal detrended fluctuation technique," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  22. Sobolev, Daphne, 2017. "The effect of price volatility on judgmental forecasts: The correlated response model," International Journal of Forecasting, Elsevier, vol. 33(3), pages 605-617.
  23. Rupel Nargunam & Ananya Lahiri, 2022. "Persistence in daily returns of stocks with highest market capitalization in the Indian market," Digital Finance, Springer, vol. 4(4), pages 341-374, December.
  24. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis And The Global Financial Crisis: Scaling, Investment Horizons And Liquidity," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-13.
  25. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.
  26. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
  27. Gurdgiev, Constantin & Harte, Gerard, 2016. "Tsallis entropy: Do the market size and liquidity matter?," Finance Research Letters, Elsevier, vol. 17(C), pages 151-157.
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