The Role of Financial Markets in Predicting BIST Sustainability Index Performance: New Evidence from Hybrid Machine Learning Models

Zeynep Çolak

Journal of Research in Economics, Politics & Finance, 2025, vol. 10, issue SI, 383-402

Abstract: The increasing importance of sustainable finance makes it critical to understand and accurately model the performance dynamics of investment instruments in this area. This study aims to forecast the return of the BIST Sustainability Index using financial market indicators and to explain the underlying dynamics of this forecasting process, thereby understanding the complex structures of financial markets, investor behavior, and information flow. In this study, eleven different machine learning models were compared with a validation strategy suitable for the time series structure, and the most successful candidates were subjected to hyperparameter optimization. In order to overcome the limitations of single models, a sequential hybrid model based on the Residual Fitting approach was developed. According to the results of the study, the two-stage hybrid model, which uses the Voting Regressor as the main predictor and Random Forest as the error corrector, provided the lowest error (RMSE) and the highest R² value. The findings indicate that the BIST_100 index is the most critical determinant, while risk aversion indicators such as Gold, USD, and VIX have a negative effect. This evidence has far-reaching implications for understanding the dynamic relationships between the Sustainability Index and macroeconomic variables.

Keywords: Sustainable Finance; BIST Sustainability Index; Machine Learning; SHAP; Explainable Artificial Intelligence (search for similar items in EconPapers)
JEL-codes: C53 C58 G19 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://dergipark.org.tr/tr/download/article-file/5375734 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ahs:journl:v:10:y:2025:i:si:p:383-402

DOI: 10.30784/epfad.1813752

Access Statistics for this article

More articles in Journal of Research in Economics, Politics & Finance from Ersan ERSOY
Bibliographic data for series maintained by Ersan Ersoy ().