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A master's thesis from Aalborg University
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Smart Beta ETFs Under Stress: Cross-Regional Factor Loadings and Performance During COVID-19 and the Russia-Ukraine War

Author

Term

4. semester

Publication year

2025

Abstract

Dette speciale undersøger, hvordan mere end 200 Smart Beta-aktie-ETF’er fra USA og Europa ændrede deres faktoreksponeringer og performance under to nylige kriser—COVID-19-pandemien og Rusland–Ukraine-krigen. Med et totrins empirisk design estimeres først tidsvarierende faktorbelastninger via panelregressioner baseret på Carharts 4-faktormodel og en udvidet 6-faktormodel med kriseinteraktioner. Dernæst vurderes risikojusteret performance med rullende Sharpe-, Sortino- og information-ratioer. Resultaterne indikerer, at faktoreksponeringer ikke er statiske, men skifter under stress—særligt for momentum og value—og at europæiske ETF’er udviser større udsving end amerikanske. Smart Beta-strategier overperformer ikke konsekvent deres benchmarks, mens multifaktorprodukter tenderer mod mere stabile resultater. Studiet bidrager med tværregional evidens fra kriseperioder om, hvordan Smart Beta-ETF’er tilpasser sig i praksis.

This thesis examines how more than 200 US- and Europe-domiciled Smart Beta equity ETFs adjusted their factor exposures and performance during two recent crises—the COVID-19 pandemic and the Russia-Ukraine war. Using a two-stage empirical design, it first estimates time-varying loadings on standard risk factors via panel regressions based on the Carhart four-factor and an extended six-factor model with crisis interaction terms. It then evaluates risk-adjusted performance with rolling Sharpe, Sortino, and Information ratios. The evidence indicates that factor exposures are not static but shift under stress—especially for momentum and value—and that European ETFs exhibit larger fluctuations than US funds. While Smart Beta strategies do not consistently outperform their benchmarks, multifactor products tend to deliver more stable outcomes. The study provides cross-regional, crisis-period evidence on how Smart Beta ETFs adapt in real markets.

[This summary has been generated with the help of AI directly from the project (PDF)]