Volatility-Managed Target Date Funds
Byounghyo Lim, CFA
A volatility-managed target date fund adjusts equity exposure based on market volatility rather than age alone, improving risk control and retirement wealth outcomes while remaining practical to implement.
Regimes Matter: Regime-Based Dynamic Asset Allocation Using Neural Networks
Uri Carl, Yaacov Kopeliovich, Michael Pokojovy, and Kevin Shea, CFA
Artificial neural networks can help investors adapt portfolios to changing market conditions. This study shows that regime-aware allocation strategies based on neural networks outperform traditional dynamic portfolios.
Machine Learning Classification and Portfolio Construction: Does the Loss Function Matter?
Yang Bai and Kuntara Pukthuanthong
Classification-based machine learning outperforms matched regression models in portfolio construction, highlighting how loss-function choice can improve return classification and portfolio performance.
Foreign Signal Radar
Wei Jiao
Machine learning can uncover foreign market signals that predict US stock returns, revealing global linkages across both domestic and multinational firms and expanding the investable universe for portfolio managers to exploit foreign information.
Volatility Carry Strategies Across Global Asset Classes
Walid Khalfallah, CFA, and Nikolaos Tessaromatis
Volatility carry predicts volatility risk premia across equities, currencies, fixed income, and commodities. Diversified carry and timing strategies deliver strong performance, with volatility swaps proving most resilient to trading costs.
