Are African Stock Markets Efficient? A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic

Abakah, E. J. A., Alagidede, P., Mensah, Lord, & Ohene-Asare, K. (2018). Non-linear approach to Random Walk Test in selected African countries. International Journal of Managerial Finance, 14(3), 362-376. https://doi.org/10.1108/IJMF-10-2017-023510.1108/IJMF-10-2017-0235 Search in Google Scholar

Aggarwal, D. (2018). Random walk model and asymmetric effect in Korean composite stock price index. Afro-Asian J. of Finance and Accounting, 8(1), 85-104. https://doi.org/10.1504/aajfa.2018.1000990610.1504/AAJFA.2018.10009906 Search in Google Scholar

Ajekwe, C. C. M., Ibiamke, A., & Haruna, H. A. (2017). Testing the Random Walk Theory in the Nigerian Stock Market. IRA-International Journal of Management & Social Sciences, 6(3), 500-508. https://doi.org/10.21013/jmss.v6.n3.p1510.21013/jmss.v6.n3.p15 Search in Google Scholar

Bashir, U., Yu, Y., Hussain, M., & Zebende, G. F. (2016). Do foreign exchange and equity markets co-move in Latin American region? Detrended cross-correlation approach. Physica A: Statistical Mechanics and Its Applications, 462, 889-897. https://doi.org/10.1016/j.physa.2016.06.09010.1016/j.physa.2016.06.090 Search in Google Scholar

Clemente, J., Montañés, A., & Reyes, M. (1998). Testing for a unit root in variables with a double change in the mean. Economics Letters, 59(2), 175–182. https://doi.org/10.1016/S0165-1765(98)00052-410.1016/S0165-1765(98)00052-4 Search in Google Scholar

Fusthane, O., & M, K. F. (2017). Weak Form Market Efficiency of the Johannesburg Stock Exchange: Pre, During and Post the 2008 Global Financial Crisis. Journal of Economics and Behavioral Studies, 9(5), 29-42. https://doi.org/10.22610/jebs.v9i5.190710.22610/jebs.v9i5.1907 Search in Google Scholar

Guedes, E. F., Ferreira, P., Dionísio, A., & Zebende, G. F. (2019). An econophysics approach to study the effect of BREXIT referendum on European Union stock markets. Physica A: Statistical Mechanics and Its Applications, 523(C), 1175-1182. https://doi.org/10.1016/j.physa.2019.04.13210.1016/j.physa.2019.04.132 Search in Google Scholar

Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal. 3, 148-161. https://doi.org/10.1111/1368-423x.0004310.1111/1368-423X.00043 Search in Google Scholar

Hawaldar, I. T., Rohith, B., & Pinto, P. (2020). Testing of Weak Form of Efficient Market Hypothesis: Evidence from the Bahrain Bourse. SSRN Electronic Journal, 14(2-2), 376-385. https://doi.org/10.2139/ssrn.350448510.2139/ssrn.3504485 Search in Google Scholar

He, Q., Liu, J., Wang, S., & Yu, J. (2020). The impact of COVID-19 on stock markets. Economic and Political Studies, 8(3), 275-288. https://doi.org/10.1080/20954816.2020.175757010.1080/20954816.2020.1757570 Search in Google Scholar

Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255-259. https://doi.org/10.1016/0165-1765(80)90024-510.1016/0165-1765(80)90024-5 Search in Google Scholar

Kelikume, I. (2016). New evidence from the efficient market hypothesis for the Nigerian stock index using the wavelet unit root test approach. The Journal of Developing Areas, 50(5), 185-197. https://doi.org/10.1353/jda.2016.004110.1353/jda.2016.0041 Search in Google Scholar

Lawal, A. I., Nwanji, T. I., Adama, I. J., & Otekunrin, A. O. (2017). Examining the nigerian stock market efficiency: Empirical evidence from wavelet unit root test approach. Journal of Applied Economic Sciences, 12(6), 1680-1689. Search in Google Scholar

Lawal, A. I., Somoye, R. O., & Babajide, A. A. (2017). Are African stock markets efficient? Evidence from wavelet unit root test for random walk. Economics Bulletin, 37(4), 2665-2679. Search in Google Scholar

Lawrence H. Summers. (1986). Does the stock market rationally reflect fundamental values. The Journal of Finance, 41(3), 591-601. https://doi.org/10.2307/232848710.2307/2328487 Search in Google Scholar

Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24. https://doi.org/10.1016/S0304-4076(01)00098-710.1016/S0304-4076(01)00098-7 Search in Google Scholar

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, 17(8), 2800. https://doi.org/10.3390/ijerph1708280010.3390/ijerph17082800 Search in Google Scholar

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, 7(1), 1-25. https://doi.org/10.19139/soic.v7i1.49910.19139/soic.v7i1.499 Search in Google Scholar

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, 10(1), 88-106. https://doi.org/10.1080/17520843.2016.121018910.1080/17520843.2016.1210189 Search in Google Scholar

Nsoesie, E. O., Rader, B., Barnoon, Y. L., Goodwin, L., & Brownstein, J. S. (2020). Analysis of hospital traffic and search engine data in Wuhan China indicates early disease activity in the Fall of 2019. Search in Google Scholar

Obayagbona, J., & Igbinosa, S. O. (2015). Test of Random Walk Hypothesis in the Nigerian Stock Market. Current Research Journal of Social Sciences, 7(2), 27-36. https://doi.org/10.19026/crjss.7.522010.19026/crjss.7.5220 Search in Google Scholar

Ogbulu, O. M. (2016). Weak-form Market Efficiency, Estimation Interval and the Nigerian Stock Exchange: Empirical Evidence. Indian Journal of Economics and Business, 5(1), 84-116. Search in Google Scholar

Sadat, A. R., & Hasan, M. E. (2019). Testing Weak Form of Market Efficiency of DSE Based on Random Walk Hypothesis Model: A Parametric Test Approach. International Journal of Accounting and Financial Reporting, 9(1), 1-14. https://doi.org/10.5296/ijafr.v9i1.1445410.5296/ijafr.v9i1.14454 Search in Google Scholar

Sansa, N. A. (2020). The Impact of the COVID-19 on the Financial Markets: Evidence from China and USA. SSRN Electronic Journal, 3, 1-26 https://doi.org/10.2139/ssrn.356790110.2139/ssrn.3567901 Search in Google Scholar

Simons, D., & Laryea, S. (2006). Testing the Efficiency of Selected African Stock Markets. Finance India. 6, 1-31. https://doi.org/10.1.1.467.7105 Search in Google Scholar

Smith, G., Jefferis, K., & Ryoo, H. J. (2002). African stock markets: Multiple variance ratio tests of random walks. Applied Financial Economics, 12(7), 475-484. https://doi.org/10.1080/0960310001000995710.1080/09603100010009957 Search in Google Scholar

Tiwari, A. K., & Kyophilavong, P. (2014). New evidence from the random walk hypothesis for BRICS stock indices: A wavelet unit root test approach. Economic Modelling, 43, 38-41. https://doi.org/10.1016/j.econmod.2014.07.00510.1016/j.econmod.2014.07.005 Search in Google Scholar

Tweneboah, G., Owusu, P., & Oseifuah, E. K. (2019). Integration of major african stock markets: Evidence from multi-scale wavelets correlation. Academy of Accounting and Financial Studies Journal, 23(6). Retrieved from https://www.researchgate.net/publication/340647142_INTEGRATION_OF_MAJOR_AFRICAN_STOCK_MARKETS_EVIDENCE_FROM_MULTI-SCALE_WAVELETS_CORRELATION Search in Google Scholar

Whisky, A. E. (2015). An Empirical Analysis of Stochastic Implications of Stock Price Movements in the Nigerian Capital Market. International Finance and Banking, 2(2), 39-51. https://doi.org/10.5296/ifb.v2i2.874310.5296/ifb.v2i2.8743 Search in Google Scholar

Wright, J. H. (2000). Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18(1), Retrieved from https://www.tandfonline.com/doi/pdf/10.1080/07350015.2000.10524842?needAccess=true https://doi.org/10.1080/07350015.2000.1052484210.1080/07350015.2000.10524842 Search in Google Scholar

Zebende, G. F. (2011). DCCA cross-correlation coefficient: Quantifying level of cross-correlation. Physica A: Statistical Mechanics and Its Applications, 390(4), 614-618. https://doi.org/10.1016/j.physa.2010.10.02210.1016/j.physa.2010.10.022 Search in Google Scholar