Neuro-Fuzzy Modeling Techniques in Economics

Neuro-Fuzzy Modeling Techniques in Economics

Fuzzy clustering approach to portfolio management considering ESG criteria: empirical evidence from the investment strategies of the EURO STOXX Index

DOI:

10.33111/nfmte.2023.040

Анотація:
Abstract: Environmental, social and governance (ESG) criteria are becoming increasingly important in the construction of investment portfolios. Analysis of the investment markets confirms that these criteria are being actively integrated into investment strategies. This paper presents our approach to incorporating ESG criteria into the portfolio construction process based on an index investment strategy. This strategy is enhanced by the inclusion of ESG criteria in the form of ESG scoring. Investment portfolio construction focuses on the application of three criteria: maximizing ESG score, minimizing risk and maximizing expected return. Our approach applies a fuzzy clustering toolkit to the set of index components. In the resulting fuzzy clusters, their core part (companies that do not belong to other clusters) and the fuzzy part are separated. The proposed investment strategy involves the construction of portfolios with a variation of the components of the fuzzy part. A VAWI (Value Added Weekly Index) curve is designed for each portfolio. The optimal strategy is implemented by constructing and reconstructing portfolios according to the upper line of the VAWI set. This investment strategy is demonstrated using the example of the EURO STOXX 50 index, which includes large companies from 11 Eurozone countries.
Ключові слова:
Key words: stock market, stock index, ESG criteria, ESG score, portfolio optimization, fuzzy clustering, portfolio performance evaluation
УДК:
UDC:

JEL: C45 G11 Q01

To cite paper
In APA style
Kaminskyi, A., & Nehrey, M. (2023). Fuzzy clustering approach to portfolio management considering ESG criteria: empirical evidence from the investment strategies of the EURO STOXX Index. Neuro-Fuzzy Modeling Techniques in Economics, 12, 40-66. http://doi.org/10.33111/nfmte.2023.040
In MON style
Камінський А.Б., Негрей М.В. Fuzzy clustering approach to portfolio management considering ESG criteria: empirical evidence from the investment strategies of the EURO STOXX Index. Нейро-нечіткі технології моделювання в економіці. 2023. № 12. С. 40-66. http://doi.org/10.33111/nfmte.2023.040 (дата звернення: 23.07.2024).
With transliteration
Kaminskyi, A., Nehrey, M. (2023) Fuzzy clustering approach to portfolio management considering ESG criteria: empirical evidence from the investment strategies of the EURO STOXX Index. Neuro-Fuzzy Modeling Techniques in Economics, no. 12. pp. 40-66. http://doi.org/10.33111/nfmte.2023.040 (accessed 23 Jul 2024).
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  1. Nasdaq. (2021, July 15). What Is ESG Investing and Why Is it Worth Trillions? https://www.nasdaq.com/articles/what-is-esg-investing-and-why-is-it-worth-trillions-2021-07-15
  2. Statista. (2023, June 14). Share of professional investors increasing their environmental, social, and governance (ESG) investments worldwide in 2023. https://www.statista.com/statistics/1191755/esg-etf-increased-investment-next-year-worldwide/
  3. Bernow, S., Klempner, B., & Magnin, C. (2017). From ‘why’ to ‘why not’: Sustainable investing as the new normal. McKinsey & Company. https://www.mckinsey.com/industries/private-equity-and-principal-investors/our-insights/from-why-to-why-not-sustainable-investing-as-the-new-normal
  4. Kaminskyi, A., Nehrey, M., & Fedchun, A. (2022). ESG-score effect in risk assessment of direct and portfolio investment: evidence from CEE markets. The Journal of V. N. Karazin Kharkiv National University. Series: International Relations. Economics. Country Studies. Tourism, 15, 38-44. https://doi.org/10.26565/2310-9513-2022-15-04
  5. Kaminskyi, A. (2022). Investment risk management specifics in ESG investing: CEE stock markets examining. Scientific Papers NaUKMA. Economics, 7(1), 54–60. https://doi.org/10.18523/2519-4739.2022.7.1.54-60
  6. UNCTAD. (2021). The rise of the sustainable fund market and its role in financing sustainable development. https://unctad.org/system/files/official-document/diae2021d1_en.pdf
  7. Gond, J-P., O’Sullivan, N., Slager, R., Homanen, M., Viehs, M., & Mosony, S. (2018). How ESG engagement creates value for investors and companies. UNEP Finance Initiative. https://www.unpri.org/download?ac=4637
  8. Zeidan, R. (2022). Why don’t asset managers accelerate ESG investing? A sentiment analysis based on 13,000 messages from finance professionals. Business Strategy and the Environment, 31(7), 3028-3039. https://doi.org/10.1002/bse.3062
  9. Meira, E., Cunha, F. A. F. D. S., Orsato, R. J., Miralles‐Quirós, M. M., & Miralles‐Quirós, J. L. (2023). The added value and differentiation among ESG investment strategies in stock markets. Business Strategy and the Environment, 32(4), 1816-1834. https://doi.org/10.1002/bse.3221
  10. Cerqueti, R., Ciciretti, R., Dalò, A., & Nicolosi, M. (2021). ESG investing: A chance to reduce systemic risk. Journal of Financial Stability, 54, Article 100887. https://doi.org/10.1016/j.jfs.2021.100887
  11. Jin, I. (2022). Systematic ESG risk and passive ESG investing. The Journal of Portfolio Management, 48(5), 71-86. https://doi.org/10.3905/jpm.2022.1.344
  12. Cesarone, F., Martino, M. L., & Carleo, A. (2022). Does ESG Impact Really Enhance Portfolio Profitability? Sustainability, 14(4), Article 2050. https://doi.org/10.3390/su14042050
  13. Kaiser, L., & Welters, J. (2019). Risk-mitigating effect of ESG on momentum portfolios. The Journal of Risk Finance, 20(5), 542-555. https://doi.org/10.1108/JRF-05-2019-0075
  14. Tiwari, A. K., Abakah, E. J. A., Gabauer, D., & Dwumfour, R. A. (2022). Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies. Global Finance Journal, 51, Article 100692. https://doi.org/10.1016/j.gfj.2021.100692
  15. Cagli, E. C. C., Mandaci, P. E., & Taşkın, D. (2022). Environmental, social, and governance (ESG) investing and commodities: dynamic connectedness and risk management strategies. Sustainability Accounting, Management and Policy Journal, 14(5), 1052-1074. https://doi.org/10.1108/SAMPJ-01-2022-0014
  16. Alessandrini, F., & Jondeau, E. (2021). Optimal strategies for ESG portfolios. The Journal of Portfolio Management, 47(6), 114-138. https://doi.org/10.3905/jpm.2021.1.241
  17. Ielasi, F., Ceccherini, P., & Zito, P. (2020). Integrating ESG analysis into smart beta strategies. Sustainability, 12(22), Article 9351. https://doi.org/10.3390/su12229351
  18. Abhayawansa, S., & Tyagi, S. (2021). Sustainable investing: The black box of environmental, social, and governance (ESG) ratings. The Journal of Wealth Management, 24(1), 49-54. https://doi.org/10.3905/jwm.2021.1.130
  19. Lee, T. K., Cho, J. H., Kwon, D. S., & Sohn, S. Y. (2019). Global stock market investment strategies based on financial network indicators using machine learning techniques. Expert Systems with Applications, 117, 228-242. https://doi.org/10.1016/j.eswa.2018.09.005
  20. Kaminskyi, A., & Nehrey, M. (2023). Clustering Stocks by ESG Score Values, Risks and Returns: Case of Expanded German Index DAX. In Z. Hu, Z. Ye, & M. He (Eds.), Lecture Notes on Data Engineering and Communications Technologies: Vol. 159. Advances in Artificial Systems for Medicine and Education VI (AIMEE 2022) (pp. 264–276). Springer, Cham. https://doi.org/10.1007/978-3-031-24468-1_24
  21. Chourmouziadis, K., & Chatzoglou, P. D. (2016). An intelligent short term stock trading fuzzy system for assisting investors in portfolio management. Expert Systems with Applications, 43, 298-311. https://doi.org/10.1016/j.eswa.2015.07.063
  22. Nguyen, T. T., Gordon-Brown, L., Khosravi, A., Creighton, D., & Nahavandi, S. (2015). Fuzzy portfolio allocation models through a new risk measure and fuzzy Sharpe ratio. IEEE Transactions on Fuzzy Systems, 23(3), 656-676. https://doi.org/10.1109/TFUZZ.2014.2321614
  23. Wang, B., Li, Y., & Watada, J. (2017). Multi-period portfolio selection with dynamic risk/expected-return level under fuzzy random uncertainty. Information Sciences, 385-386, 1-18. https://doi.org/10.1016/j.ins.2016.12.033
  24. Bielinskyi, A., Soloviev, V., Solovieva, V., & Velykoivanenko, H. (2022). Fuzzy time series forecasting using semantic artificial intelligence tools. Neuro-Fuzzy Modeling Techniques in Economics, 11, 157-198. http://doi.org/10.33111/nfmte.2022.157
  25. Matviychuk, A. (2006). Fuzzy logic approach to identification and forecasting of financial time series using Elliott wave theory. Fuzzy economic review, 11(2), 51-68. https://doi.org/10.25102/fer.2006.02.04
  26. Bondarenko, M. (2021). Modeling relation between at-the-money local volatility and realized volatility of stocks. Neuro-Fuzzy Modeling Techniques in Economics, 10, 46-66. http://doi.org/10.33111/nfmte.2021.046
  27. Tkachenko, R., Tkachenko, P., Izonin, I., Vitynskyi, P., Kryvinska, N., & Tsymbal, Y. (2019). Committee of the Combined RBF-SGTM Neural-Like Structures for Prediction Tasks. In I. Awan, M. Younas, P. Ünal, & M. Aleksy (Eds.), Lecture Notes in Computer Science: Vol. 11673. Mobile Web and Intelligent Information Systems (MobiWIS 2019) (pp. 267–277). Springer, Cham. https://doi.org/10.1007/978-3-030-27192-3_21
  28. Derbentsev, V., Velykoivanenko, H., & Datsenko, N. (2019). Machine learning approach for forecasting cryptocurrencies time series. Neuro-Fuzzy Modeling Techniques in Economics, 8, 65-93. http://doi.org/10.33111/nfmte.2019.065
  29. Fadilah, I., & Witiastuti, R. (2018). A Clustering Method Approach for Portfolio Optimization. Management Analysis Journal, 7(4), 436-447. https://doi.org/10.15294/maj.v7i4.23378
  30. Gularte, A. P. D. S., Feitosa, F. D. S. A., Pacheco, V. H. P., & Curtis, V. V. (2023). Clustering Approach for Portfolio Optimization. SSRN, Article 4474899. http://dx.doi.org/10.2139/ssrn.4474899
  31. Kaminskyi, A., Miroshnychenko, I., & Pysanets, K. (2019). Risk and return for cryptocurrencies as alternative investment: Kohonen maps clustering. Neuro-Fuzzy Modeling Techniques in Economics, 8, 175-193. http://doi.org/10.33111/nfmte.2019.175
  32. Kaminskyi, A., Butylo, D., & Nehrey, M. (2021). Integrated approach for risk assessment of alternative investments. International Journal of Risk Assessment and Management, 24(2-4), 156-177. https://doi.org/10.1504/IJRAM.2021.126413
  33. Lovas, G. (2023). The top ESG rating providers and how to use them. Broker Chooser. https://brokerchooser.com/education/investing/top-esg-rating-providers
  34. Bede, B. (2013). Fuzzy Clustering. In Studies in Fuzziness and Soft Computing: Vol. 295. Mathematics of Fuzzy Sets and Fuzzy Logic (pp. 213-219). Springer. https://doi.org/10.1007/978-3-642-35221-8_12
  35. Ganti, A. (2022, April 30). Value Added Monthly Index (VAMI): What It Is, How It Works. Investopedia. https://www.investopedia.com/terms/v/vami.asp
  36. Investing.com. (2023). Euro Stoxx 50 (STOXX50E) [Data set]. Retrieved January 15, 2023, from https://www.investing.com/indices/eu-stoxx50
  37. Liu, D., & Graham, J. (2017). Simple Measures of Individual Cluster-Membership Certainty for Hard Partitional Clustering. arXiv. https://doi.org/10.48550/arXiv.1704.00352