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Tensor Portfolios

Author

Listed:
  • Tae-Hwy Lee

    (Department of Economics, University of California Riverside)

  • Tianyan Tu

    (University of California, Riverside)

Abstract

Motivated by the multi-dimensional nature of financial data, we propose the tensor portfolios, a framework exploiting the intrinsic multi-way structure of stock returns to reduce the number of free parameters required for portfolio construction. We develop three distinct methods tailored to specific structural assumptions. We systematically compare tensor and vector portfolios through Monte Carlo simulations and empirical studies. The simulation results show tensor portfolios yield significantly higher out-of-sample Sharpe ratios whenever the data exhibits a tensor structure. Empirical analysis further corroborates the effectiveness of tensor portfolios; their general outperformance over vector portfolios in read-world markets highlights the practical significance of exploiting multi-way information.

Suggested Citation

  • Tae-Hwy Lee & Tianyan Tu, 2026. "Tensor Portfolios," Working Papers 202601, University of California at Riverside, Department of Economics.
    • Handle: RePEc:ucr:wpaper:202601
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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