2021
DOI: 10.1051/shsconf/20219101029
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Long memory in stock returns: Evidence from the Eastern European markets

Abstract: This essay aims to analyze the impact of the 2020 global pandemic on the memory properties of the Eastern Europe stock markets, from the period between 1 January 2016 to 2 September 2020, the sample was divided in two subperiods: 1 January 2016 to 30 August 2019 (before Covid 19) and 2 September 2019 to 2 September 2020 (after Covid 19). To perform this analysis, different approaches were undertaken to analyze whether if: (i) the global pandemic (Covid-19) accentuated the exponents Detrended Fluctuation Analys… Show more

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Cited by 15 publications
(12 citation statements)
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“…The results are in line with the findings of the authors G.Sudha and V. Sornaganesh (2020), Lahmiri and Bekiros (2020), which indicate sharp declines in the international financial markets, resulting from the global pandemic . These findings are corroborated by authors Heliodoro, Dias, and Alexandre (2020), Dias, Heliodoro, Alexandre, and Vasco (2020), Dias, Heliodoro, Alexandre, Santos, and Farinha (2021, Dias and Pereira (2021) who evidence stock market crashes in the first quarter of 2020 due to the 2020 global pandemic. Source: Own elaboration.…”
Section: Resultssupporting
confidence: 58%
“…The results are in line with the findings of the authors G.Sudha and V. Sornaganesh (2020), Lahmiri and Bekiros (2020), which indicate sharp declines in the international financial markets, resulting from the global pandemic . These findings are corroborated by authors Heliodoro, Dias, and Alexandre (2020), Dias, Heliodoro, Alexandre, and Vasco (2020), Dias, Heliodoro, Alexandre, Santos, and Farinha (2021, Dias and Pereira (2021) who evidence stock market crashes in the first quarter of 2020 due to the 2020 global pandemic. Source: Own elaboration.…”
Section: Resultssupporting
confidence: 58%
“…The lack of consensus among economists and financial analysts regarding market efficiency requires the study of the efficient market hypothesis (EMH). Another significant reason to study market efficiency is the role of stock markets to act as financial intermediaries between the saver and the borrower in the distribution of scarce resources via the price mechanism (Dias, da Silva, and Dionísio, 2019;Dias et al, 2021;Dias, Heliodoro, Teixeira, et al, 2020;Dias, Teixeira, Machova, et al, 2020;Jain, 2020;Karasiński, 2020) The authors Obayagbona and Igbinosa (2015), Kelikume (2016), Abakah, Alagidede, Mensah, and Ohene-Asare ( 2018), Hawaldar, Rohith, and Pinto (2020) analyzed market efficiency, in its weak form, in the African stock indexes. Obayagbona and Igbinosa (2015) tested the Nigerian market in the context of market efficiency, the authors show that the price series do not show randomness, that is, they present long memories.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The DFA has the following interpretation: 0 < < 0,5: anti-persistent series; = 0,5 series has a random walk; 0,5 < < 1 persistent series. The function of this technique is to examine the relationship between the and + values at different times (Guedes et al, 2018;Dionísio, 2019 Alexandre, Dias, andDias, Heliodoro, Alexandre, Santos, and Farinha, 2021;Dias, Heliodoro, and Alexandre, 2020;Dias, Heliodoro, Alexandre, and Vasco, 2020;Dias, Pardal, Teixeira, and Machová, 2020 Zebende ( 2011) non-trend cross-correlation coefficient is a method for quantifying the level of cross-correlation between two nonstationary time series. The coefficient is based on the DFA (Peng et al, 1994) and DCCA (Podobnik and Stanley, 2008) methods.…”
Section: Modelmentioning
confidence: 99%
“…If a given stock market is strongly linked to the stock market of another country, the financial stability of the former depends, in part, on the financial stability of the latter. For this reason, a close or strong link between markets increases levels of vulnerability to external shocks and, as a result, influences the economic conditions and welfare levels of the respective countries, as well as the efficiency of the market itself Heliodoro, 2020a, 2020b;Alexandre, Heliodoro, and Dias, 2019;Dias and Carvalho, 2020;Alexandre, 2020a, 2019;Dias, Heliodoro, Alexandre, Santos, and Farinha, 2021;Dias, Heliodoro, Teixeira, and Godinho, 2020;Dias, Pardal, Teixeira, and Machová, 2020;Dias, Heliodoro, Alexandre, and Vasco, 2020b;Dias and Pereira, 2021; Heliodoro, P., Dias, R., Alexandre, P., and Vasco, 2020;Pardal, P., Dias, R., Šuleř, P., Teixeira, N., and Krulický, 2020;Santos and Dias, 2020).…”
Section: Introductionmentioning
confidence: 99%