Cilt 14 Sayı 1 (2026): Business & Management Studies: An International Journal
Makaleler

Yeşil finans perspektifinden ESG endekslerinin borsa dinamikleri üzerindeki rolü: Türkiye örneği

İlknur Ülkü Armağan
Dr. Öğr. Üyesi, Süleyman Demirel Üniversitesi, Isparta, Türkiye

Yayınlanmış 25.03.2026

Anahtar Kelimeler

  • ESG Stock Indices, ARDL Bounds Testing Approach, MSCI EM SI, XUSRD, Financial Markets
  • ESG Hisse Endeksleri, ARDL Sınır Testi Yaklaşımı, MSCI EM SI, XUSRD, Finansal Piyasalar

Nasıl Atıf Yapılır

Yeşil finans perspektifinden ESG endekslerinin borsa dinamikleri üzerindeki rolü: Türkiye örneği. (2026). Business & Management Studies: An International Journal, 14(1), 143-161. https://doi.org/10.15295/bmij.v14i1.2690

Nasıl Atıf Yapılır

Yeşil finans perspektifinden ESG endekslerinin borsa dinamikleri üzerindeki rolü: Türkiye örneği. (2026). Business & Management Studies: An International Journal, 14(1), 143-161. https://doi.org/10.15295/bmij.v14i1.2690

Öz

Bu çalışma, MSCI Gelişmekte Olan Piyasalar Seçim Endeksi (MSCI EM SI), Borsa İstanbul Sürdürülebilirlik Endeksi (XUSRD) ve Borsa İstanbul 100 Endeksi (XU100) arasındaki kısa ve uzun vadeli ilişkileri analiz ederek, hem küresel hem de ulusal finans piyasalarında Çevresel, Sosyal ve Yönetişim (ESG) kriterlerinin artan önemini vurgulamaktadır. ESG ilkelerinin finans piyasalarına entegrasyonu, yatırımcıların risk ve getiriyi değerlendirme biçimini dönüştürmüş ve iklim değişikliği, jeopolitik istikrarsızlıklar ve COVİD-19 pandemisi gibi son küresel krizlerin ardından daha da kritik hale gelmiştir. Sonuç olarak, hem uluslararası hem de ulusal ESG endeksleri, özellikle gelişmekte olan ekonomiler için sürdürülebilir finansal varlıklara geçişi destekleyen temel göstergeler olarak ortaya çıkmıştır. Bu çalışmada, seçilen endekslerin aylık kapanış verileri kullanılarak ARDL Sınır Testi Yaklaşımı ile ampirik bir analiz yapılmıştır. Bulgular, MSCI EM SI ile XU100 Endeksi arasında kısa veya uzun vadede anlamlı bir ilişki olmadığını, buna karşılık XUSRD Endeksi’nin kısa ve uzun vadede XU100 Endeksi ile istatistiksel olarak anlamlı bir etkileşim gösterdiğini ortaya koymaktadır.

Referanslar

  1. Akhtaruzzaman, M.D., Boubaker, S. & Umar, Z. (2022). COVID-19 media coverage and ESG leader indices. Finance Research Letters, 45. https://doi.org/10.1016/j.frl.2021.102170
  2. Arslan, Z., Erdaş, M. L., & Göçmen Yağcılar, G. (2025). A research on the relationship between ESG performance of companies and systematic risk. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, 12(1), 348-362. https://doi.org/10.30798/makuiibf.1600852
  3. Aykut, M. M. (2025). Dynamic connectedness and risk spillovers between Brent oil prices and the BIST-100 sustainability index. Journal of Anadolu University Vocational Education and Practice, 4(2), 233-249. https://doi.org/10.70756/anameud.1788575
  4. Başkaya, H. (2025). An analysis of the relationship and causality between the BIST Sustainability Index and other financial indices. Fiscaoeconomia, 9(2), 1003-1021. https://doi.org/10.25295/fsecon.1541942
  5. Borsa Istanbul. (2025a). Indices. BIST Stock Indices. Benchmark Indices. BIST 100. 01 August 2025, https://www.borsaistanbul.com/en/indices/bist-stock-indices/benchmark-indices
  6. Borsa Istanbul. (2025b). Indices. BIST Stock Indices. Sustainability. 01 August 2025, https://www.borsaistanbul.com/en/indices/bist-stock-indices/sustainability
  7. Breusch, T. S., & Godfrey, L. G. (1978). Testing for autocorrelation in dynamic linear models. Econometrica, 46(6), 1287–1296.
  8. Çakmak, A.O. & Çalış, E. (2024). Sürdürülebilirlik performansının borsa performansına etkisi. Press Academia Procedia, 19(1), 61-74. https://doi.org/10.17261/Pressacademia.2024.1910
  9. Çetin, F. A., Öztürk, S. & Akarsu, O. N. (2024). The effect of ESG data of companies on financial performance: A panel data analysis on The BIST Sustainability Index. Sosyoekonomi, 32(61), 125-146. https://doi.org/10.17233/sosyoekonomi.2024.03.07
  10. Dickey, D.A. & Fuller, W.A. (1981). Distribution of the estimators for autoregressive time series with a Unit Root. Econometrica, 49, 1057-1072
  11. Duran, N. I. (2025). Navigating uncertainty: Dynamic linkages between sustainability indices and ESG-related shocks. Anadolu University Journal of Economics and Administrative Sciences, 26(4), 456-484. https://doi.org/10.53443/anadoluibfd.1705330
  12. Engle, R.F. & Granger, C. W. J. (1987). Cointegration and Error Correction: Representation, estimation, and testing, Econometrica, 55(2), 251-276. https://doi.org/10.2307/1913236
  13. Gherghina, S.C., Armeanu, D.S. & Joldes, C.C. (2020). Stock market reactions to COVID-19 pandemic outbreak: Quantitative evidence from ARDL Bounds Tests and Granger Causality analysis. International Journal of Environmental Research And Public Health, 17(18). https://doi.org/10.3390/ijerph17186729
  14. Gujarati, N.D. (1995). Basic Econometrics. Nobel Yayın Dağıtım.
  15. Gülcemal, T. (2025). Return connectedness between ESG stock indices and the impact of ESG attention on return connectedness. International Journal of Economics and Administrative Studies, (48), 161-182. https://doi.org/10.18092/ulikidince.1633961.
  16. Investing.com. (2025). Indices. 01 August 2025, https://tr.investing.com/indices/ise-100.
  17. Johansen, S. & Juselius, K. (1990) Maximum Likelihood estimation and inference on Cointegration with applications to the demand for money. Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, 52(2), 169-210. http://dx.doi.org/10.1111/j.1468-0084.1990.mp52002003.x
  18. Karaca, S. S., Koyuncu, T. & Çevik, M. (2021). Analysıs of Borsa Istanbul Financial Index and macroeconomic variables with ARDL Boundary Test. The Journal of Financial Researches and Studies, 13(25), 572-585. https://doi.org/10.14784/marufacd.976614
  19. Korkmazgöz, Ç., Şahin, S. & Ege, I (2022). The relationship between Bitcoin and Borsa Istanbul Indices: ARDL Bounds Testing approach. The World of Accounting Science, 24(1), 89-108. https://doi.org/10.31460/mbdd.898812
  20. Morgan Stanley Capital International (2025a). MSCI EM Selection Index. 01 August 2025, https://www.msci.com/indexes/index/703304.
  21. Morgan Stanley Capital International (2025b). MSCI EM Selection Index. Documents, Index Factsheet (31 July 2025). 01 August 2025, https://www.msci.com/documents/10199/255599/msci-emerging-markets-selection-index-usd-gross.pdf.
  22. Nkoro, E. & Uko, A.K. (2016) Autoregressive Distributed Lag (ARDL) Cointegration technique: Application and interpretation. Journal of Statistical and Econometric Methods, 5, 63-91.
  23. Özman, H. (2022). New generation fund type for social responsibilities: Sustainable (ESG) investment funds. Journal of Banking and Capital Markets Research, 6(13), 1-20.
  24. Pesaran, M. H., Shin, Y. & Smith, R. J. (2001). Bounds Testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
  25. Pesaran, M.H., Shin, Y. & Smith, R.P. (1997). Pooled estimation of long run relationships in dynamic Heterogeneous panels. Cambridge Working Papers in Economics 9721, Faculty of Economics, University of Cambridge.
  26. Pesaran H. & Shin, Y. (1995). An Autoregressive Distributed lag modeling approach to cointegration analysis. Department of Applied Economics, University of Cambridge. https://doi.org/10.1017/CCOL0521633230.011
  27. Phillips, P.C.B & Perron, P. (1988). Testing for a Unit Root in time series regression. Biometrika, 75(2), 335-346.
  28. Rubbaniy, G., Khalid, A.A., Rizwan, M.F. & Ali, S. (2022). Are ESG stocks safe-haven during COVID-19? Studies in Economics and Finance, 39(2), 239-255. 10.1108/SEF-08-2021-0320
  29. Sahabi, A. M. (2023). The impact of sustainability performance on stock returns and volatility: Evidence from Borsa Istanbul. Bingöl University Journal of Social Sciences Institute, 25, 57-70. https://doi.org/10.29029/busbed.1205759
  30. Shaik, M. & Rehman, M.Z. (2023). The dynamic volatility connectedness of major environmental, social, and governance (ESG) stock indices: Evidence based on DCC-GARCH model. Asia-Pacific Financial Markets, Special Issue, 30(1), 231-246. https://doi.org/10.1007/s10690-022-09393-5
  31. Sharma, G.D., Sarker, T., Rao, A., Talan, G. & Jain, M. (2022). Revisiting conventional and green finance spillover in post-COVID world: Evidence from robust econometric models. Global Finance Journal, 51. https://doi.org/10.1016/j.gfj.2021.100691
  32. Tian, H., Long, S.B. & Li, Z.X. (2022). Asymmetric effects of climate policy uncertainty, infectious diseases-related uncertainty, crude oil volatility, and geopolitical risks on green bond prices. Finance Research Letters, 48. https://doi.org/10.1016/j.frl.2022.103008
  33. Umar, Z., Kenourgios, D. & Papathanasiou, S. (2020). The static and dynamic connectedness of environmental, social, and governance investments: International evidence. Economic Modelling, 93, 112-124. https://doi.org/10.1016/j.econmod.2020.08.007
  34. Wan, J.R., Yin, L.B. & Wu, Y. (2023). Return and volatility connectedness across global ESG stock indexes: Evidence from the time-frequency domain analysis. Internatıonal Review Of Economics and Finance, 89, Part B, 397-428. https://doi.org/10.1016/j.iref.2023.10.038
  35. Zhang, W.T., He, X. & Hamori, S. (2022). Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach. International Review of Financial Analysis, 83. https://doi.org/10.1016/j.irfa.2022.102223