Sector Rotation by Factor Model and Fundamental Analysis
TLDR
This paper develops a predictive framework for sector rotation using factor models and fundamental metrics, showing strong predictive capabilities.
Key contributions
- Systematically classifies sectors and empirically investigates their returns.
- Identifies momentum and short-term reversion as key drivers in sector shifts via factor analysis.
- Utilizes in-depth fundamental metrics (PE, PB, EV-to-EBITDA, Dividend Yield) for analysis.
- Develops a robust predictive framework for sector rotation using these fundamental indicators.
Why it matters
This paper offers a nuanced understanding of sector rotation strategies. Its predictive framework, combining factor models and fundamental analysis, has significant implications for asset management and portfolio construction.
Original Abstract
This study presents an analytical approach to sector rotation, leveraging both factor models and fundamental metrics. We initiate with a systematic classification of sectors, followed by an empirical investigation into their returns. Through factor analysis, the paper underscores the significance of momentum and short-term reversion in dictating sectoral shifts. A subsequent in-depth fundamental analysis evaluates metrics such as PE, PB, EV-to-EBITDA, Dividend Yield, among others. Our primary contribution lies in developing a predictive framework based on these fundamental indicators. The constructed models, post rigorous training, exhibit noteworthy predictive capabilities. The findings furnish a nuanced understanding of sector rotation strategies, with implications for asset management and portfolio construction in the financial domain.
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