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Growing the Efficient Frontier on Panel Trees

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  • Lin William Cong
  • Guanhao Feng
  • Jingyu He
  • Xin He

Abstract

We develop a new class of tree-based models (P-Trees) for analyzing (unbalanced) panel data using economically guided, global (instead of local) split criteria that guard against overfitting while preserving sparsity and interpretability. To generalize security sorting and better estimate the efficient frontier, we grow a P-Tree top-down to split the cross section of asset returns to construct test assets and re-cover the stochastic discount factor under the mean-variance efficient framework, visualizing (asymmetric) nonlinear interactions among firm characteristics. When applied to U.S. equities, boosted (multi-factor) P-Trees significantly advance the efficient frontier relative to those constructed with established factors and common test assets. P-Tree test assets are diversified and exhibit significant unexplained alphas against benchmark models. The unified P-Tree factors outperform most known observable and latent factor models in pricing cross-sectional returns, delivering transparent and effective trading strategies. Beyond asset pricing, our framework offers a more interpretable and computationally efficient alternative to recent machine learning and AI models for analyzing panel data through goal-oriented, high-dimensional clustering.

Suggested Citation

  • Lin William Cong & Guanhao Feng & Jingyu He & Xin He, 2022. "Growing the Efficient Frontier on Panel Trees," NBER Working Papers 30805, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:30805
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    Cited by:

    1. Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
    2. Siyu Bie & Francis X. Diebold & Jingyu He & Junye Li, 2024. "Machine Learning and the Yield Curve: Tree-Based Macroeconomic Regime Switching," Papers 2408.12863, arXiv.org.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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