Nguyễn Minh Trí, Nguyễn Trọng Đức, Nguyễn Chánh Nguyên, Thôi Uyên Uyên, Vũ Ngọc Lan Anh
Sinh viên K61 – CLC1 Quản trị kinh doanh quốc tế
Trường Đại học Ngoại thương Cơ sở II, TP. Hồ Chí Minh, Việt Nam
Đào Quốc Phương
Giảng viên Cơ sở II
Trường Đại học Ngoại thương Cơ sở II, TP. Hồ Chí Minh, Việt Nam
Abstract
This study examines how generative AI can be used to analyze textual data and forecast reader attitudes and behavior about stock market investing. Since investor psychology is creating a bigger impact on financial markets, it is essential to comprehend sentiment from news stories, social media, and financial reports to make wise investing choices. The study analyzes volumes of unstructured textual data using cutting-edge generative AI models, such as ChatGPT, to identify emotional triggers that influence investor behavior, such as fear, greed, and optimism. To gain insight into how textual narratives influence investing decisions, this project aims to identify patterns that link sentiment with market movements by fusing sentiment analysis with behavioral finance principles. Ultimately, the findings will enhance emotional prediction models, support improved investment strategies, and inform both academic research and real-world financial decision-making.
Keywords: Generative AI, emotional analysis, behavioral analysis, financial forecasting, stock market prediction.