Recent Developments in Quantitative Investing: Evolving Theory from the Financial to Responsible Perspective and Machine Learning Tools

This paper reviews the fundamental theories supporting quantitative investment development. Four distinct stages of theoretical evolution are proposed: from classical portfolio management to practical factor identification, then to the consideration of investor behavioral factors, and finally to a much broader theoretical framework that incorporates societal and environmental impact. Based on those theories, the review article continues to discuss how machine learning tools are used in industry and presents the challenges of adopting them. Finally, this paper concludes by describing current research limitations and suggests new directions for future research that can combine quantitative investment and transition finance.