Paula Heliodoro – Escola Superior de Ciências Empresarias – Instituto Politécnico de Setúbal, Portugal

Rui Dias – Escola Superior de Ciências Empresarias – Instituto Politécnico de Setúbal, Portugal & CEFAGE, Universidade de Évora, Portugal

Paulo Alexandre – Escola Superior de Ciências Empresarias – Instituto Politécnico de Setúbal, Portugal

Maria Manuel – Escola Superior de Ciências Empresarias – Instituto Politécnico de Setúbal, Portugal




4th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2020, Online/virtual, October 8, 2020, CONFERENCE PROCEEDINGS published by the Association of Economists and Managers of the Balkans, Belgrade; Printed by: SKRIPTA International, Belgrade, ISBN 978-86-80194-36-3, ISSN 2683-5991, DOI:




This essay aims to analyse the impact of the 2020 global pandemic on the stock indexes of France (CAC 40), Germany (DAX 30), USA (DOW JONES), United Kingdom (FTSE 100), Italy (FTSE MID), Japan (Nikkei 225) and Canada (TSX 300), from January 2018 to June 2020, with the sample being divided into two sub periods: first sub period from January 2018 to August 2019 (Pre-Covid); second period from September 2019 to June 2020 (Covid-19). In order to carry out this analysis, different approaches were taken in order to analyse whether: (i) the global pandemic (Covid-19) increased the persistence of the G7 financial markets? In the Pre-Covid period, we can verify the presence of long memories in the Canadian market (TSX), while the markets in France (CAC 40) and Italy (FTSE MID) show signs of balance, since the random walk hypothesis was not rejected. The German (DAX 30), USA (DJI), United Kingdom (FTSE 100) and Japan (NIKKEI 225) markets have anti-persistence (0 <α <0.5). In period II, the Covid-19-time scale is contained, and we verified the presence of significant long memories, except for the US stock index (0.49). These findings make it possible to show that the assumption of the market efficiency hypothesis may be called into question, because these markets are predictable, which validate the research question. The results of the pDCCA correlation coefficients, in the Pre-Covid period, show 14 pairs of median markets (0.333 → ≌ 0.666). We can also see 7 pairs of markets with strong correlation coefficients (0.666 → ≌ 1,000), showing that these markets have a tendency towards integration, this evidence may call into question the hypothesis of portfolio diversification. In period II (Covid-19) the λ_DCCA correlation coefficients have 7 strong market pairs (0.666 → ≌ 1,000), 5 pairs have weak pDCCA coefficient (0.000 → ≌ 0.333), 5 market pairs show anti-correlation (-1.000 → ≌ 0.000), and 4 market pairs show median coefficients (pDCCA) (0.333 → ≌ 0.666) (out of 21 possible). When compared to the previous subperiod, we found that the majority of the pDCCAs decreased, which shows that the markets have decreased their integration, making it possible to diversify portfolios in certain markets, especially in the Japanese market (NIKKEI 225). These conclusions open space for market regulators to take measures to ensure better informational information, in the stock markets, in the 7 most advanced economies in the world.



Covid-19, G7, Persistence, Long memories, Arbitration.


Aslam, F., Mohti, W., & Ferreira, P. (2020). Evidence of Intraday Multifractality in European Stock Markets during the Recent Coronavirus (COVID-19) Outbreak. International Journal of Financial Studies.
Awan, U., & Subayyal, M. (2018). Weak Form Efficient Market Hypothesis Study: Evidence from Gulf Stock Markets. SSRN Electronic Journal.
Ayentimi, D., Mensah, A., & Naa-Idar, F. (2013). Stock market efficiency of Ghana stock exchange: An objective analysis. International Journal of Management, Economics and Social Sciences (IJMESS).
Chaker, M. N., & Sabah, A. (2018). Testing the weak form of efficiency of the stock markets in Gulf Cooperation Council countries. Journal for Global Business Advancement.
Dourado, G. de A., & Tabak, B. M. (2014). Testing the adaptive markets hypothesis for Brazil. Brazilian Review of Finance.
Dsouza, J. J., & Mallikarjunappa, T. (2015). Does the Indian Stock Market Exhibit Random Walk? Paradigm.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance.
Fama, E. F., & French, K. R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics.
Fernando, P. N. D., & Gunasekara, A. L. (2018). Is the Market Efficiency Static or Dynamic – Evidence from Colombo Stock Exchange (CSE). Kelaniya Journal of Management.
Ferreira, P., Dionísio, A., Guedes, E. F., & Zebende, G. F. (2018). A sliding windows approach to analyse the evolution of bank shares in the European Union. Physica A: Statistical Mechanics and Its Applications, 490, 1355–1367.
Gallegati, M. (2016). Beyond econophysics (not to mention mainstream economics). European Physical Journal: Special Topics.
Guedes, E. F., Brito, A. A., Oliveira Filho, F. M., Fernandez, B. F., de Castro, A. P. N., da Silva Filho, A. M., & Zebende, G. F. (2018). Statistical test for ΔρDCCA: Methods and data. Data in Brief.
Hamid, K., Suleman, M. T., Ali Shah, S. Z., & Imdad Akash, R. S. (2017). Testing the Weak Form of Efficient Market Hypothesis: Empirical Evidence from Asia-Pacific Markets. SSRN Electronic Journal.
Karasiński, J. (2020). The Changing Efficiency of the European Stock Markets. Annales Universitatis Mariae Curie-Skłodowska, Sectio H – Oeconomia.
Lawrence H. Summers. (1986). Does the stock market rationally reflect fundamental values. The Journal of Finance.
Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020). The COVID-19 outbreak and affected countries stock markets response. International Journal of Environmental Research and Public Health.
Malafeyev, O., Awasthi, A., S.Kambekar, K., & Kupinskaya, A. (2019). Random Walks and Market Efficiency in Chinese and Indian Equity Markets. Statistics, Optimization & Information Computing.
Mphoeng, M. (2019). Testing for Weak-Form Market Efficiency in the Botswana Stock Market. Archives of Business Research.
Ngene, G., Tah, K. A., & Darrat, A. F. (2017). The random-walk hypothesis revisited: new evidence on multiple structural breaks in emerging markets. Macroeconomics and Finance in Emerging Market Economies.
Peng, C. K., Buldyrev, S. V., Havlin, S., Simons, M., Stanley, H. E., & Goldberger, A. L. (1994). Mosaic organization of DNA nucleotides. Physical Review E, 49(2), 1685–1689.
Pernagallo, G., & Torrisi, B. (2019). An empirical analysis on the degree of Gaussianity and long memory of financial returns in emerging economies. Physica A: Statistical Mechanics and Its Applications.
Podobnik, B., & Stanley, H. E. (2008). Detrended cross-correlation analysis: A new method for analyzing two nonstationary time series. Physical Review Letters, 100(8).
Poterba, J. M., & Summers, L. H. (1988). Mean reversion in stock prices. Evidence and Implications. Journal of Financial Economics.
Robinson, C. J. (2016). Stock Price Behaviour in Emerging Markets: Tests for Weak-Form Efficiency on the Jamaica Stock Exchange. SSRN Electronic Journal.
Tebyaniyan, H., Jahanshad, A., & Heidarpoor, F. (2020). Analysis of weak performance hypothesis, multi-fractality feature and long-term memory of stock price in Tehran stock exchange. International Journal of Nonlinear Analysis and Applications.
Zebende, G. F. (2011). DCCA cross-correlation coefficient: Quantifying level of cross-correlation. Physica A: Statistical Mechanics and Its Applications, 390(4), 614–618.
Zeren, F., & Hizarci, A. (2020). The impact of Covid-19 coronavirus on stock markets: evidence from selected countries. Muhasebe ve Finans İncelemeleri Dergisi.


Download Full Paper

Association of Economists and Managers of the Balkans – UdEkoM Balkan
179 Ustanicka St, 11000 Belgrade, Republic of Serbia

ITEMA conference publications are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.