Market Efficiency During the COVID-19 Pandemic. Some Insights Using Non-Parametric Tests

ABSTRACT

This paper examines the weak form of the Efficient Market Hypothesis (EMH) across fourteen European Stock Markets from October 2018 to April 2021, a period divided into subsamples based on the outbreak of the COVID-19 pandemic. Using non-parametric tests, including Runs, Bartel’s rank, and Wright’s rank and sign test, the findings indicate that EMH holds for developed capital markets. However, capital markets in Central and Eastern Europe exhibited a heterogeneous response to the pandemic. Some markets violated the efficiency hypothesis (Latvia and Lithuania), others consistently adhered to it (Hungary and Slovenia), while others became less efficient post-pandemic (Estonia and Romania).

JEL CLASSIFICATION:

• G14
• G15

KEYWORDS:

• Efficient Market Hypothesis (EMH)
• COVID-19 pandemic
• European capital markets
• Non-parametric Tests

Disclosure statement

The author has no relevant financial or non-financial interests to disclose.

Author Contributions

The author confirms sole responsibility for the following: study conception, design, data collection, empirical analysis, and conclusions.

Data availability statement

Raw data were generated at Thomson Reuters platform. Derived data supporting the findings of this study are available from the author on request.

Notes

1. The following countries are included in the analysis – Belgium, France, Germany, Greece, Spain, Ireland and Portugal.

2. At the suggestion of a participant at the 39th EBES conference, I also performed a parametric method, namely an auto-regression AR(1) model. The results of the model confirms the results of Bartels Rank test, with the exception of two markets. Nevertheless, the model suffered from heteroscedasticity while residuals were not normally distributed. In order to avoid the breach of OLS assumptions, in this study I apply a set of non-parametric tests.

3. I performed the tests on market indexes which presents a series of advantages compared to testing on certain shares. For example, it eliminates the problem of poor stock liquidity, which is often present in emerging capital markets. Moreover, it overcomes the limits of non-diversification (Dragotă and Țilică 2014).

4. There are numerous methods for testing the level of efficiency of a stock market (see Appendix A). The first filter was the classification of the stock markets included in the analysis. Most of the capital markets are characterized as emerging or frontier markets and, as a result, I considered only the methodologies employed to test the weak form of the EMH (Dragotă and Țilică 2014). Secondly, I observed that in most of the cases the series of returns do not follow a normal distribution (according to the results obtained by using the Jarque-Bera test), thus I selected only non-parametric methods (Vasileiou 2021).

5. The access to the Thomson Reuters platform was ensured by the Bucharest University of Economic Studies.

Additional information

Funding

This work was supported by the The Bucharest University of Economic Studies.

Notes on contributors

Andreea Iordache

Andreea Iordache is a PhD student at the Finance Doctoral School of the Bucharest University of Economic Studies. Her research interest revolves around market efficiency, information asymmetry and stock returns prediction. She has presented her work in conferences in Italy and Germany. Her PhD thesis aims to measure the impact of news on financial assets’ return and liquidity while also taking into consideration the information asymmetry between the market participants and their behavior.