The authors examine whether quantitative investing has evolved enough to avoid another “Quant Winter.” They argue past drawdowns stemmed from macro sensitivity and crowding, while newer approaches use alternative data, machine learning, and dynamic factor selection; during stress, macro factors have explained over 50% of quant-manager return variation.
The Quant Renaissance Part III: Who’s Ready for the Next Winter?
Man Group
Valerie Xiang, Ori Ben-Akiva
Research
22 Pages
Key Takeaways
Macro risk spikes: Macro factors explain 15–25% of generic factor variation normally but over 40% in Quant Winters; manager exposure peaks above 50%.
New models diversify: Current alpha models correlate only 40–50% with 2018–2020 versions, versus 70–80% correlations often seen across traditional systematic approaches.
Static weights constrain: Their generic benchmark allocates 40% to Value, 30% Momentum, and 10% each to Capital Efficiency, Earnings Quality, and Size.
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