THE FUTURE OF FACTOR INVESTING: CAN WE IDENTIFY NEW SOURCES OF ALPHA?

Abstract

Factor investing has revolutionized asset allocation, capturing market inefficiencies through systematic exposure to well-defined return drivers. However, concerns linger about diminishing alpha in established factors and the potential overvaluation of trendy alternatives. This article delves into the evolving landscape of factor investing, exploring the viability of identifying new sources of alpha through two key avenues: (1) novel modeling techniques leveraging artificial intelligence and machine learning, and (2) emerging alternative data sets like satellite imagery, social media sentiment, and alternative transaction data. We critically examine the potential and pitfalls of these approaches, drawing upon academic research and industry insights. We conclude that while challenges exist, the future of factor investing appears bright, with a renewed focus on interpretability, explainability, and responsible factor construction.