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A Comprehensive Machine Learning Framework for Dynamic Portfolio Choice With Transaction Costs

Author

Listed:
  • Luca Gaegauf

    (University of Zurich)

  • Simon Scheidegger

    (University of Lausanne)

  • Fabio Trojani

    (University of Geneva; University of Turin; Swiss Finance Institute)

Abstract

We introduce a comprehensive computational framework for solving dynamic portfolio choice problems with many risky assets, transaction costs, and borrowing and short-selling constraints. Our approach leverages the synergy between Gaussian process regression and Bayesian active learning to efficiently approximate value and policy functions with a novel, formal way of characterizing the irregularly-shaped no-trade region; we then embed this into a discrete-time dynamic programming algorithm. This combination allows us to study dynamic portfolio choice problems with more risky assets than was previously possible. Our results indicate that giving the agent access to more assets may alleviate some illiquidity resulting from the presence of transaction costs.

Suggested Citation

  • Luca Gaegauf & Simon Scheidegger & Fabio Trojani, 2023. "A Comprehensive Machine Learning Framework for Dynamic Portfolio Choice With Transaction Costs," Swiss Finance Institute Research Paper Series 23-114, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp23114
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    More about this item

    Keywords

    Machine learning; computational finance; computational economics; Gaussian process regression; dynamic portfolio optimization; transaction costs; liquidity premia;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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