생성형 인공지능을 활용한 투자 포트폴리오 형성에 관한 실증 분석 연구

• 영문명: An Empirical Study on Investment Portfolio Formation Using Generative Artificial Intelligence
• 발행기관: 강원대학교 경영경제연구소
• 저자명: 홍태나(Tai-Na Hong) 김대룡(Dae-Lyong Kim)
• 간행물 정보: 『아태비즈니스연구』제15권 제4호, 249~263쪽, 전체 15쪽
• 주제분류: 인문학 > 문학
• 파일형태: PDF
• 발행일자: 2024.12.31

국문 초록

Purpose - The purpose of this study is to empirically verify whether generative artificial intelligence (AI) can be used as a tool to positively influence investors’ investment strategies. Design/methodology/approach - For this purpose, we received recommendations from GPT-4o for stocks of different sizes and weights among the large and liquid securities that make up the CSI 300 Index, formed five portfolios through mean-variance optimization, and compared and analyzed the changes in cumulative returns. Findings - The empirical results showed that the cumulative returns of portfolios based on stocks rated as excellent by GPT-4o were better than those of the market index, CSI300, regardless of the portfolio composition. In addition, the cumulative return performance estimated by the portfolios weighted by GPT-4o did not differ from the cumulative returns of the portfolios formed by applying the financial mean-variance optimization theory. Research implications or originality - The results of this empirical analysis show that generative AI models have ample potential to be used as a tool to have a positive effect on investment strategies, such as portfolio construction, beyond simple stock selection.

목차

Ⅰ. 서론

Ⅱ. 분석자료 형성 및 연구모형

Ⅲ. 실증 분석

Ⅳ. 결론

References

키워드

Generative AI Investment Management Portfolio Optimization