Predictive Accuracy of Generative AI Models (Transformers/LLMs) vs. Traditional Machine Learning Models in Forecasting Financial Indices: A Comparative Analysis using MAE and RMSE Metrics
Abstract
The primary aim of this research is to quantitatively evaluate the predictive accuracy of cutting-edge Generative AI models—specifically Transformers and Large Language Models (LLMs)—against traditional statistical and Machine Learning models in the context of financial forecasting.
Fields of Study & Subjects
Stock Market Forecasting Methods
Forecasting Techniques and Applications
Time Series Analysis and Forecasting
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 19 January 2026