ESG vs conventional indices: Comparing efficiency in the Ukrainian stock market

  • Received February 12, 2023;
    Accepted March 24, 2023;
    Published April 3, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(2).2023.01
  • Article Info
    Volume 20 2023, Issue #2, pp. 1-15
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This work is licensed under a Creative Commons Attribution 4.0 International License

This paper explores market efficiency in the Ukrainian stock market to determine whether there are differences between traditional and ESG indices. Different data properties related to market efficiency are explored: persistence (R/S analysis is used for these purposes), stationarity (ADF tests), normality (Kolmogorov-Smirnoff, Anderson-Darling test, etc.), resistance to market anomalies (Day of the week effect, abnormal returns and patterns they generate are tested using parametrical and non-parametrical statistical tests), etc. Database includes daily data from 2 conventional Ukrainian stock market indices (UX and PFTS) and ESG index (WIG Ukraine) over the period 2015–2022. The following hypothesis is tested in this paper: ESG indices are more efficient than traditional ones. The findings suggest that there are no significant differences between traditional and ESG indices: they have the same persistence, stationarity, do not fit normal distribution and are not influenced by explored market anomalies. So, despite the fact that companies listed in the ESG index are more transparent and thus characterized by lower information asymmetry, they are more liquid and popular among investors, ESG index is not more efficient than traditional ones. This might be the result of unfair practices called “washing” aimed at signaling the active ESG involvement with actual absence of it. This means that many ESG companies are actually traditional. To prevent such practices, the ESG reporting regulation needs to be revised.

Acknowledgment
Alex Plastun gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0121U100473).

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    • Figure 1. Cluster analysis results for the research areas related to ESG, SRI, sustainability and conventional (traditional) indices in 2017–2022
    • Figure 2. Dynamic R/S analysis results
    • Figure 3. Average returns for the different days of the week
    • Figure 4. Average returns on usual days and on the days after the days with abnormal returns
    • Figure A1. Frequency of returns for the case of the PFTS index
    • Figure A2. Frequency of returns for the case of the UX index
    • Figure A3. Frequency of returns for the case of the WIG Ukraine index
    • Table 1. Descriptive statistics for ESG and conventional indices (case of returns)
    • Table 2. t-test results for ESG and conventional indices (case of returns)
    • Table 3. ANOVA and Kruskal-Wallis test results for ESG and conventional indices (case of returns)
    • Table 4. Normality tests for ESG and conventional indices (case of returns)
    • Table 5. Stationarity tests for the ESG and conventional indices
    • Table 6. Static R/S analysis results
    • Table 7. Results of yield difference tests for different days of the week
    • Table 8. Number of days with abnormal returns for ESG and conventional indices
    • Table 9. Results of tests for differences in returns on days after days with abnormal returns and usual days
    • Table 10. Emerging regulations in ESG investment landscape
    • Conceptualization
      Alex Plastun, Iryna Shalyhina
    • Data curation
      Alex Plastun
    • Methodology
      Alex Plastun
    • Project administration
      Alex Plastun, Inna Makarenko
    • Resources
      Alex Plastun, Inna Makarenko
    • Writing – original draft
      Alex Plastun, Inna Makarenko, Liudmyla Huliaieva
    • Formal Analysis
      Inna Makarenko
    • Funding acquisition
      Inna Makarenko
    • Investigation
      Liudmyla Huliaieva, Iryna Shalyhina
    • Validation
      Liudmyla Huliaieva
    • Visualization
      Liudmyla Huliaieva, Tetiana Guzenko
    • Software
      Tetiana Guzenko
    • Supervision
      Tetiana Guzenko, Iryna Shalyhina
    • Writing – review & editing
      Tetiana Guzenko, Iryna Shalyhina