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 Analysis (DFA) and the Detrended Cross-Correlation Analysis (๐๐ท๐ถ๐ถ๐ด) in the Eastern European stock markets?. The daily returns do not have normal distributions, they have negative asymmetries, leptocubtic, and also exhibit conditional heteroscedasticity. The exponents Detrended Fluctuation Analysis (DFA), during the Covid-19 period, range from 0.64 to 0.75, showing significant long memories in all markets, except for the SLOVAKIA market (0.45). When we compared the 2 subperiods, we found that 41 pairs of markets have cross-correlation coefficients without trend ( ฮปDCCA) strong (out of 45 possible), and 4 pairs of markets decreased the ๐โ๐๐ท๐ถ๐ถ๐ด in particular the markets ESTONIA-SLOVAKIA, LITHUANIA-SLOVAKIA, HUNGARY-SLOVAKIA, POLAND-SLOVAKIA. These findings show that the assumption of the market efficiency hypothesis may be in question, since the prediction of market movement can be improved if we consider the out-of-lag movements of the other markets, enabling the occurrence of arbitrage operations and some difficulties in portfolio diversification.
This paper aims to test the efficient market hypothesis, in its weak form, in the stock markets of BOTSWANA, EGYPT, KENYA, MOROCCO, NIGERIA and SOUTH AFRICA, in the period from September 2, 2019 to September 2, 2020. In order to achieve this analysis, we intend to find out if: the global pandemic (Covid-19) has decreased the efficiency, in its weak form, of African stock markets? The results therefore support the evidence that the random walk hypothesis is not supported by the financial markets analyzed in this period of global pandemic. The values of variance ratios are lower than the unit, which implies that the yields are autocorrelated in time and, there is reversal to the mean, and no differences were identified between the stock markets analyzed. The authors consider that the results achieved are of interest to investors looking for opportunities for portfolio diversification in these regional stock markets.
This chapter aims to analyze the impact of the global 2020 pandemic on the banking sectors of the Czech Republic, Hungary, Poland, Romania, Russia, and Slovakia countries in the period from January 2, 2017 to August 10, 2020. The results of the Gregory-Hansen test, in the covid subperiod, show 27 integrations (in 30 possible). When comparing the pre-covid and covid subperiods, the level of integration has increased 386% between markets, which could call into question portfolio diversification, validating the first research question. In corroboration, the authors have verified that the results of Granger's causality tests, in the COVID-19 subperiod, increased significantly. In view of these results and bearing in mind the results of integration, they can show that the crisis caused by the global pandemic of 2020 has increased the synchronization between these regional banking sectors, significantly decreasing the hypothesis of implementing efficient portfolio diversification, thus validating the second research question.
This paper aims to analyze the predictability of the stocks of Apple, Microsoft Amazon.com, Tesla, Facebook, Samsung, Electronics, Johnson & Johnson, Walmart, in the period from October 1, 2019 to January 11, 2021. To carry out such an analysis, it is intended to answer two research questions, namely: (i) is there predictability in the stock prices of the companies under analysis? (ii) Can investors diversify risk by incorporating these companiesโ shares into their portfolios? The results of the Exponents Detrended Fluctuation Analysis (DFA) show that Apple (0.51) Microsoft (0.49), Amazon.com (0.53), Samsung Electronics (0.53), Johnson & Johnson (0.53) do not have long memories in their time series, that is, investors cannot obtain abnormal profitability without incurring additional risk. Walmart (0.41) has anti-persistence, while Tesla (0.60), Facebook (0.55) indicate some predictability, meaning investors adjusting their trading strategies to the necessary missteps may have some above-average profitability, which partly rejects the first question of the research. To answer the second research question, we estimated the Detrended cross-correlation coefficient (pDCCA) model, which indicates 17 mean correlation coefficients (โ 0.333 โ โ 0.666), 7 strong cross-trend correlation coefficients (0.666 โ โ 1,000), 4 weak correlation coefficients (โ 0.000 โ โ 0.333). These results show that investors should be careful to incorporate the shares of these companies into a single portfolio; the suggestion would be to group only the shares of companies that do not present predictability and have low rhoDCCA. The authors consider that this evidence will be important for institutional investors when carrying out trading strategies based on maximizing profitability, but also mitigating risk when diversifying.
This chapter aims to analyze the efficiency, in its weak form, in the exchange rates of Brazil vs. USA, Australia, Canada, Europe (Euro Zone), Switzerland, United Kingdom, and Japan from July 1, 2019 to September 20, 2020. The results suggest that exchange rates show signs of (in)efficiency, in their weak form (i.e., the values of the variance ratios are lower than the unit), which implies that returns are autocorrelated over time, and there is reversal to the average. In corroboration, the results of detrended fluctuation analysis (DFA) show persistence in yields (i.e., the existence of long memories), thus validating the results of the Lo and Mackinlay model that show autocorrelation between the series of yields. As a conclusion, the authors show that the assumption of market efficiency may be questioned, since the forecast of market movement may be improved if the lagged movements of the other markets are taken into account, allowing the occurrence of arbitrage operations in these foreign exchange markets.
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