Course Reform and Practice of Quantitative Analysis in Behavioral Finance Based on Big Data and Artificial Intelligence

Abstract

This study focuses on the innovative application of data science and artificial intelligence technologies in behavioral finance courses. By dissecting the limitations of traditional courses in the quantitative analysis training section, it proposes a teaching framework that integrates natural language processing, machine learning, and agent simulation technologies. The study designed a complete teaching process from data collection, feature engineering, model construction to simulation verification, and based on the real scenarios of the Chinese securities market, constructed a three-level progressive teaching program. After several rounds of empirical teaching tests, the curriculum framework has effectively enhanced students' quantitative research ability and critical thinking literacy, provided an innovative solution for cultivating compound financial talents in the digital age, and the research results have positive significance for promoting the innovative development of the financial discipline and the cultivation of interdisciplinary talents.