Open Access
Issue
SHS Web Conf.
Volume 91, 2021
Innovative Economic Symposium 2020 – Stable Development in Unstable World (IES2020)
Article Number 01029
Number of page(s) 10
Section Stable Development in Unstable World
DOI https://doi.org/10.1051/shsconf/20219101029
Published online 14 January 2021
  1. M.T.S.G. Sudha, V. Sornaganesh, “IMPACT OF INDIAN STOCK MARKET DUE TO CRISIS IN MARCH 2020,” 2020. [Google Scholar]
  2. R. Dias, J.V. da Silva, and A. Dionísio, “Financial markets of the LAC region: Does the crisis influence the financial integration?,” Int. Rev. Financ. Anal., 63, (February), 160-173 (2019). [CrossRef] [Google Scholar]
  3. M. Gallegati, “Beyond econophysics (not to mention mainstream economics),” Eur. Phys. J. Spec. Top. (2016). [Google Scholar]
  4. G.F. Zebende, “DCCA cross-correlation coefficient: Quantifying level of cross-correlation,” Phys. A Stat. Mech. its Appl., 390, (4), 614-618 (2011). [CrossRef] [Google Scholar]
  5. V. Filipovski and D. Tevdovski, “Stock market efficiency in south eastern Europe: Testing return predictability and calendar effects,” in Regaining Global Stability After the Financial Crisis (2018). [Google Scholar]
  6. P. Ferreira, “Long-range dependencies of Eastern European stock markets: A dynamic detrended analysis,” Phys. A Stat. Mech. its Appl ( 2018). [Google Scholar]
  7. H. Muharam, W. Mawardi, E.D. Arfinto, and Najmudin, “Volatility spillovers under difference in the degree of market integration: Evidence from the selected asian and eastern European stock markets,” J. Int. Stud ( 2019). [Google Scholar]
  8. S. Moagar-Poladian, D. Clichici, and C.V. Stanciu, “The comovement of exchange rates and stock markets in Central and Eastern Europe,” Sustain. (2019). [Google Scholar]
  9. Lawrence H. Summers, “Does the stock market rationally reflect fundamental values,” J. Finance (1986). [Google Scholar]
  10. S. Nisar and M. Hanif, “Testing weak form of efficient market hypothesis: Empirical evidence from South-Asia,” World Appl. Sci. J. (2012). [Google Scholar]
  11. S. Mehla and S.K. Goyal, “Empirical Evidence on Weak Form of Efficiency in Indian Stock Market,” Asia-Pacific J. Manag. Res. Innov. (2013). [Google Scholar]
  12. A. El Khamlichi, K. Sarkar, M. Arouri, and F. Teulon, “Are Islamic equity indices more efficient than their conventional counterparts? Evidence from major global index families,” J. Appl. Bus. Res. (2014). [Google Scholar]
  13. D. Li, Y. Nishimura, and M. Men, “The long memory and the transaction cost in financial markets,” Phys. A Stat. Mech. its Appl. (2016). [Google Scholar]
  14. G. Ngene, K.A. Tah, and A.F. Darrat, “The random-walk hypothesis revisited: new evidence on multiple structural breaks in emerging markets,” Macroecon. Financ. Emerg. Mark. Econ. (2017). [Google Scholar]
  15. S. Ali, S.J.H. Shahzad, N. Raza, and K.H. Al-Yahyaee, “Stock market efficiency: A comparative analysis of Islamic and conventional stock markets,” Phys. A Stat. Mech. its Appl. (2018). [Google Scholar]
  16. G. Pernagallo and B. Torrisi, “An empirical analysis on the degree of Gaussianity and long memory of financial returns in emerging economies,” Phys. A Stat. Mech. its Appl. (2019). [Google Scholar]
  17. S. Lahmiri, S. Bekiros, and F. Bezzina, “Multi-fluctuation nonlinear patterns of European financial markets based on adaptive filtering with application to family business, green, Islamic, common stocks, and comparison with Bitcoin, NASDAQ, and VIX,” Phys. A Stat. Mech. its Appl. (2020). [Google Scholar]
  18. S. Lahmiri and S. Bekiros, “Nonlinear analysis of Casablanca Stock Exchange, Dow Jones and S&P500 industrial sectors with a comparison,” Phys. A Stat. Mech. its Appl. (2020). [Google Scholar]
  19. G.M. Caporale, L.A. Gil-Alana, and C. Poza, “High and low prices and the range in the European stock markets: A long-memory approach,” Res. Int. Bus. Financ. (2020). [Google Scholar]
  20. L.R. Milos, C. Hatiegan, M.C. Milos, F.M. Barna, and C. Botoc, “Multifractal detrended fluctuation analysis (MF-DFA) of stock market indexes. Empirical evidence from seven central and eastern european markets,” Sustain. (2020). [Google Scholar]
  21. C.M. Jarque and A.K. Bera, “Efficient tests for normality, homoscedasticity and serial independence of regression residuals,” Econ. Lett., 6 (3), 255-259 (1980). [CrossRef] [Google Scholar]
  22. E.F. Guedes et al., “Statistical test for ΔρDCCA: Methods and data,” Data Br. (2018). [Google Scholar]
  23. C.K. Peng, S.V. Buldyrev, S. Havlin, M. Simons, H.E. Stanley, and A.L. Goldberger, “Mosaic organization of DNA nucleotides,” Phys. Rev. E, 49 (2), 1685-1689 (1994). [NASA ADS] [CrossRef] [Google Scholar]
  24. B. Podobnik and H.E. Stanley, “Detrended cross-correlation analysis: A new method for analyzing two nonstationary time series,” Phys. Rev. Lett., 100, (8), (2008). [CrossRef] [PubMed] [Google Scholar]
  25. P. Ferreira, A. Dionísio, E.F. Guedes, and G.F. Zebende, “A sliding windows approach to analyse the evolution of bank shares in the European Union,” Phys. A Stat. Mech. its Appl., 490, 1355-1367 (2018). [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.