GREEN BONDS IN CLIMATE FINANCE AND FORECASTING OF CORPORATE GREEN BOND INDEX VALUE WITH ARTIFICIAL INTELLIGENCE

The effects of global climate change and increasing environmental awareness have led to an increase in the significance projects and, accordingly, finance green bonds. Despite significance, fact that price forecasting studies on bonds are extremely scarce has been main motivation this study. aim paper is forecast corporate bond prices with Artificial Neural Network model determine predictor by addressing conceptual framework For purpose, Multi-Layer Feedback (MLF-ANN) model, which S&P 500 index determined as input output, designed. To whether conventional bonds, was used sole model. findings show forecasted 1.13% Mean Absolute Percentage Error (MAPE) 98.93% Regression Determination Coefficient (R2). results research provide data maximize profits and/or minimize risk for investors market makers, while providing insight into effectiveness financing policy makers. This first study literature terms proving MLF-ANN revealing Thus, it expected will shed light future studies.