Growing the efficient frontier on panel trees

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number104024
Journal / PublicationJournal of Financial Economics
Volume167
Online published18 Feb 2025
Publication statusOnline published - 18 Feb 2025

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Abstract

We introduce a new class of tree-based models, P-Trees, for analyzing (unbalanced) panel of individual asset returns, generalizing high-dimensional sorting with economic guidance and interpretability. Under the mean–variance efficient framework, P-Trees construct test assets that significantly advance the efficient frontier compared to commonly used test assets, with alphas unexplained by benchmark pricing models. P-Tree tangency portfolios also constitute traded factors, recovering the pricing kernel and outperforming popular observable and latent factor models for investments and cross-sectional pricing. Finally, P-Trees capture the complexity of asset returns with sparsity, achieving out-of-sample Sharpe ratios close to those attained only by over-parameterized large models. © 2025 The Authors.

Research Area(s)

  • Decision tree, Factors, Generative models, Interpretable AI, Test assets

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Citation Format(s)

Growing the efficient frontier on panel trees. / Cong, Lin William; Feng, Guanhao; He, Jingyu et al.
In: Journal of Financial Economics, Vol. 167, 104024, 05.2025.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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