Sustainable Stock Screening Based on Fundamental and Technical Indicators using Gaussian Naive Bayes Classifier - Risky Gunawan; Cinta Priscillia Maharani; Gita Fitriyana; Dwi Indah Maharani (Department of Mathematics, Hasanuddin University, 2026)
Investors increasingly require systematic methods for sustainable stock screening, particularly for ESG-focused benchmarks like Inodnesia's SRI-KEHATI Index. This Study addresses a gap by developing and evaluating a stock screening framework using a Gaussian Naive Bayes (GNB) classifier to integrate both fundamental and technical analysis. The model utilized quarterly data from 25 SRI-KEHATI stocks from Q1 2024 to Q2 2025, training on 11 indicators to predict future quarterly returns, classifying stocks as