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Long-range correlations and nonstationarity in the Brazilian stock market

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  1. de Oliveira Santos, Maíra & Stosic, Tatijana & Stosic, Borko D., 2012. "Long-term correlations in hourly wind speed records in Pernambuco, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1546-1552.
  2. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
  3. Gomes, Luís M. P. & Soares, Vasco J. S. & Gama, Sílvio M. A. & Matos, José A. O., 2018. "Long-term memory in Euronext stock indexes returns: an econophysics approach," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(4), pages 862-881, August.
  4. Araneda, Axel A. & Bertschinger, Nils, 2021. "The sub-fractional CEV model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
  5. Figueiredo, Thiago C. & Vivas, Jamile & Peña, Norberto & Miranda, José G.V., 2016. "Fractal measures of video-recorded trajectories can classify motor subtypes in Parkinson’s Disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 12-20.
  6. M. Bartolozzi & C. Mellen, 2009. "Local Risk Decomposition for High-frequency Trading Systems," Papers 0904.4099, arXiv.org, revised Feb 2011.
  7. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
  8. Yang, Yujun & Li, Jianping & Yang, Yimei, 2017. "The cross-correlation analysis of multi property of stock markets based on MM-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 23-33.
  9. Jia, Zhanliang & Cui, Meilan & Li, Handong, 2012. "Research on the relationship between the multifractality and long memory of realized volatility in the SSECI," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 740-749.
  10. Fernanda Cimini & Jorge Britto & Leonardo Costa Ribeiro, 2020. "Complexity systems and middle-income trap: the long-term roots of Latin America underdevelopment [Sistemas complexos e armadilha da renda media: as raízes de longo prazo do subdesenvolvimento latino-a," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 30(spe), pages 1225-1256, December.
  11. Domino, Krzysztof, 2012. "The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 156-169.
  12. 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).
  13. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
  14. 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.
  15. Uritskaya, Olga Y. & Serletis, Apostolos, 2008. "Quantifying multiscale inefficiency in electricity markets," Energy Economics, Elsevier, vol. 30(6), pages 3109-3117, November.
  16. Lim, Kian-Ping & Brooks, Robert D. & Kim, Jae H., 2008. "Financial crisis and stock market efficiency: Empirical evidence from Asian countries," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 571-591, June.
  17. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
  18. Sosa-Correa, William O. & Ramos, Antônio M.T. & Vasconcelos, Giovani L., 2018. "Investigation of non-Gaussian effects in the Brazilian option market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 525-539.
  19. 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.
  20. Luis A. Gil-Alana & Yun Cao, 2011. "Stock market prices in China. Efficiency, mean reversion, long memory volatility and other implicit dynamics," Faculty Working Papers 12/11, School of Economics and Business Administration, University of Navarra.
  21. Domino, Krzysztof & Błachowicz, Tomasz, 2015. "The use of copula functions for modeling the risk of investment in shares traded on world stock exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 142-151.
  22. Zhu, Huijian & Zhang, Weiguo, 2018. "Multifractal property of Chinese stock market in the CSI 800 index based on MF-DFA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 497-503.
  23. Domino, Krzysztof, 2011. "The use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 98-109.
  24. Lin, Aijing & Ma, Hui & Shang, Pengjian, 2015. "The scaling properties of stock markets based on modified multiscale multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 525-537.
  25. Hull, Matthew & McGroarty, Frank, 2014. "Do emerging markets become more efficient as they develop? Long memory persistence in equity indices," Emerging Markets Review, Elsevier, vol. 18(C), pages 45-61.
  26. Gu, Rongbao & Xiong, Wei & Li, Xinjie, 2015. "Does the singular value decomposition entropy have predictive power for stock market? — Evidence from the Shenzhen stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 103-113.
  27. Abounoori, Esmaiel & Shahrazi, Mahdi & Rasekhi, Saeed, 2012. "An investigation of Forex market efficiency based on detrended fluctuation analysis: A case study for Iran," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3170-3179.
  28. Paulo Ferreira, 2017. "Portuguese and Brazilian stock market integration: a non-linear and detrended approach," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(1), pages 49-63, April.
  29. Santos, E.C.O. & Guedes, E.F. & Zebende, G.F. & da Silva Filho, A.M., 2022. "Autocorrelation of wind speed: A sliding window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
  30. Lin, Aijing & Shang, Pengjian, 2016. "Multifractality of stock markets based on cumulative distribution function and multiscale multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 527-534.
  31. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.
  32. Setty, V.A. & Sharma, A.S., 2015. "Characterizing Detrended Fluctuation Analysis of multifractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 698-706.
  33. Mensi, Walid & Lee, Yun-Jung & Vinh Vo, Xuan & Yoon, Seong-Min, 2021. "Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  34. Fan, Feng-Hua & Deng, Yanbin & Huang, Yong-Chang, 2017. "Investigation on financial crises with the negative-information-propagation-induced model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 94-104.
  35. Domino, Krzysztof & Błachowicz, Tomasz, 2014. "The use of copula functions for modeling the risk of investment in shares traded on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 77-85.
  36. Mahata, Ajit & Bal, Debi Prasad & Nurujjaman, Md, 2020. "Identification of short-term and long-term time scales in stock markets and effect of structural break," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
  37. Du, Guoxiong & Ning, Xuanxi, 2008. "Multifractal properties of Chinese stock market in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 261-269.
  38. Santos, J.V.C. & Moreira, D.M. & Moret, M.A. & Nascimento, E.G.S., 2019. "Analysis of long-range correlations of wind speed in different regions of Bahia and the Abrolhos Archipelago, Brazil," Energy, Elsevier, vol. 167(C), pages 680-687.
  39. Emmanuel Numapau Gyamfi & Kwabena Kyei & Kwabena Kyei, 2016. "Long - Memory Persistence in African Stock Markets," EuroEconomica, Danubius University of Galati, issue 1(35), pages 83-91, may.
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