Forecasting the net investment position based on conventional and ESG stock market indices: The case of Ukraine and Austria

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This paper examines the relationship between traditional and ESG stock market indices and the net international investment position for the case of Austria and Ukraine. For these purposes, the following methods are used: variance analysis, ANOVA analysis, correlation analysis, VAR analysis, R/S analysis, and Granger causality test. According to the results, ESG indices are less volatile than conventional ones. Based on the correlation analysis, it is concluded that there is a significant direct connection between ESG indices and their traditional counterparts (0.98 for Austria and 0.68 for Ukraine). A substantial level of persistence in Austria’s investment position indicates the possibility of using autoregression models for forecasting. The results of the net investment position modelling for the case of Austria showed a statistically significant impact of stock market indices on the net investment position. But for the case of Ukraine, this impact is insignificant. This is indirect evidence in favor of poor performance of the Ukrainian stock market. Further development of Ukrainian stock market is required, because Austrian experience showed that stock market can be used as a transmission mechanism in boosting investment position both within conventional approach and ESG.

Acknowledgment
Alex Plastun, Mario Situm, Inna Makarenko, and Yulia Serpeninova gratefully acknowledge support from Ministry of Education and Science of Ukraine (0122U002659).

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    • Table 1. Descriptive statistics of conventional and ESG indices: the case of Ukraine and Austria
    • Table 2. Variance analysis of the investment position, ESG index and conventional indices: the case of Ukraine and Austria
    • Table 3. Analysis of correlations: the case of Ukraine and Austria
    • Table 4. Granger causality tests for the case of Ukraine and Austria
    • Table 5. Persistence analysis: the case of Ukraine and Austria
    • Table 6. Autocorrelation analysis for the case of Ukraine and Austria
    • Table 7. Regression modelling of the investment position: the case of Ukraine and Austria
    • Table 8. Stationarity test for the case of Ukraine and Austria
    • Table 9. Definition of lags for the case of Austria
    • Table 10. Determining the optimal number of lags: the case of Ukraine and Austria
    • Table 11. Results of the Johansen cointegration test: the case of Ukraine and Austria
    • Table 12. VAR analysis for the case of Ukraine and Austria
    • Formal Analysis
      Alex Plastun
    • Investigation
      Alex Plastun, Inna Makarenko
    • Methodology
      Alex Plastun
    • Writing – original draft
      Alex Plastun, Inna Makarenko, Daniel Salabura, Yulia Serpeninova, Mario Situm
    • Conceptualization
      Inna Makarenko
    • Resources
      Inna Makarenko, Yulia Serpeninova
    • Project administration
      Daniel Salabura, Yulia Serpeninova, Mario Situm
    • Supervision
      Daniel Salabura
    • Writing – review & editing
      Daniel Salabura, Mario Situm
    • Funding acquisition
      Yulia Serpeninova, Mario Situm