This research paper presents a comprehensive analytical approach to sector rotation by integrating factor models with fundamental analysis. The study begins with a systematic classification of sectors and an empirical investigation into their returns, using factor analysis to identify key drivers such as momentum and short-term reversion. This is followed by an in-depth fundamental analysis that evaluates various metrics, including PE, PB, EV-to-EBITDA, and Dividend Yield, to develop a predictive framework for sector shifts.

The primary contribution of this work lies in the development of a robust predictive model based on these fundamental indicators, which undergoes rigorous training to enhance its capabilities. The findings provide a nuanced understanding of sector rotation strategies, highlighting the significance of both factor-driven and fundamental insights. This research has important implications for asset management and portfolio construction in the financial domain, offering practical tools for improving investment decisions through a data-driven approach to sector allocation.