Does the Coronavirus Crash affect green equity markets’ efficiency? A multifractal analysis

ABSTRACT

This study assesses the multifractality and degree of efficiency regarding the following green equity markets: Dow Jones Sustainability Index, S&P Global Clean Energy, Nasdaq OMX Green Economy, and S&P Global 1200 Carbon Efficient. For that purpose, MF-DFA and three measures of efficiency analysis are applied. It is performed on two samples, corresponding to Full Sample and Full Sample without the Coronavirus Crash (excluding the period from February 20, 2020 to August 31, 2020). The outcomes ratify that the Coronavirus Crash increases markets’ multifractality and decreases their efficiency. S&P Global 1200 Carbon Efficient shows the highest degree of multifractality and the lowest efficiency, while S&P Global Clean Energy shows the lowest multifractality and highest efficiency. The sources of markets’ multifractality derive from long-range correlations and fat-tailed distributions for both samples. The time-varying efficiency of green equity markets confirms a decrease in efficiency after the Coronavirus Crash.

KEYWORDS:

• Green equity markets
• MF-DFA
• multifractality
• efficiency

JEL CLASSIFICATION:

• D53
• G15
• F64

Acknowledgments

Joaquim Ferreira gratefully acknowledges financial support from Fundacão para a Ciência e a Tecnologia within the projects: NECE UIDB/04630/2020; Flávio Morais gratefully acknowledges financial support from Fundacão para a Ciência e a Tecnologia within the projects: NECE UIDB/04630/2020; CEFAGE-UBI UIDB/04007/2020.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In this context, two types of agents with different time horizons can be presented as high-frequency investors and well-known buy-and-hold investors. Regarding buy-and-hold investors, the strategy they focus on is long-term, taking into account the fundamentals, whereas for high-frequency investors it is based on reducing latency, allowing for improvement in decoding the process of subsequent flash price (Conrad, Wahal, and Xiang 2015).

2 Islamic market refers to a market that integrates firms from different geographical locations (including Islamic geographical areas), following Sharia principles.

3 Although the MF-DFA presents as a robust approach to nonstationary time series, this procedure is enabled for stationary time series as well. Concerning stationary time series, h(2) is similar to Hurst exponent (Wang, Liu, and Gu 2009; Laib et al. 2018b). In this study, we transform time series indexes in log returns (stationary time series) as in finance and econophysics literature.

4 In several studies the fitting of multifractal spectrum use the quadratic function. Nevertheless, the 2nd order of polynomial may not present good quantitative analysis from f(α) (Benicio et al. 2013).

5 It uses the cubic form as this avoids bias in evaluating the degree of multifractality (Laib et al. 2018b; Oświe¸cimka et al. 2013).

6 The time-varying of Eff2 and Eff3 outcomes, for the sake of brevity, can be obtained on request from the authors.