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William W. Lamptey, Nicholas Appiah, Abootaleb Shirvani, Priscilla Ati-Tay, Svetlozar T. Rachev, Frank J. Fabozzi · 2026-07-03
The paper tests several portfolio-construction methods (buy-and-hold, mean-variance, CVaR-based, and tangency-type) across 30 mostly actively managed ETFs using daily data from late 2020 to late 2025. It finds the funds behave very differently across themes and asset classes, and that tangency-type portfolios tend to compete best with buy-and-hold on risk-adjusted terms, while minimum-variance and CVaR strategies give up upside for better downside protection. Tail-risk diagnostics show meaningful downside exposure persists even after combining funds into portfolios.
Why it matters: For someone building portfolios out of actively managed ETFs, the study illustrates trade-offs between chasing risk-adjusted returns and controlling downside/tail risk, and highlights that diversification across differing fund types matters. It also flags that dynamic strategies can look strong on paper but may suffer once turnover and trading costs are considered.
⚠ Results are historical backtests over a single 2020-2025 window with only 30 funds, and the authors note dynamic strategies are sensitive to turnover and implementation costs not fully captured.
This paper examines portfolio optimization and tail-risk analytics for a heterogeneous universe of actively managed investment funds. Using daily Bloomberg data for 30 funds from 4 December 2020 to 24 December 2025, the study evaluates buy-and-hold, mean--variance, CVaR-based, and tangency-type strategies under long-only and long--short constraints. The sample consists predominantly of actively managed ETFs, with PTTRX retained as an actively managed fixed-income mutual-fund comparator. The results show substantial heterogeneity across thematic equity, fixed-income, income-oriented, multi-asset, and alternative strategies, creating both diversification opportunities and meaningful differences in volatility, drawdown behavior, downside exposure, and tail risk. Historical results indicate that tangency-type portfolios are generally the strongest competitors to the buy-and-hold benchmark in cumulative and risk-adjusted terms, while minimum-variance and CVaR-minimizing portfolios sacrifice upside participation for stronger downside control. Dynamic allocation does not improve all strategies uniformly: the long-only dynamic CVaR-95 portfolio is consistently attractive across several risk-adjusted criteria, whereas long--short dynamic tangency-CVaR portfolios perform strongly but are more sensitive to turnover and implementation costs. Tail-risk diagnostics based on empirical VaR, Expected Shortfall, maximum drawdown, left-tail Hill estimators, and POT--GPD methods show that downside tail exposure remains meaningful after portfolio aggregation. Overall, actively managed ETFs are best evaluated as components of a joint investment opportunity set in which dependence structure, portfolio design, dynamic allocation, implementation frictions, and tail-risk exposure jointly shape performance.
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AI summary generated from the paper’s public abstract via arXiv; it may miss nuance — read the source before relying on it. Thank you to arXiv for its open-access interoperability; StockTools is not affiliated with arXiv, and all rights remain with the authors. Educational only, not financial advice.