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A Linear Stochastic Programming Model for Optimal Leveraged Portfolio Selection

Author

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  • Davi Michel Valladão

    (Pontifical Catholic University of Rio de Janeiro)

  • Álvaro Veiga

    (Pontifical Catholic University of Rio de Janeiro)

  • Alexandre Street

    (Pontifical Catholic University of Rio de Janeiro)

Abstract

The literature of portfolio optimization is extensive and covers several important aspects of the asset allocation problem. However, previous works consider simplified linear borrowing cost functions that leads to suboptimal allocations. This paper aims at efficiently solving the leveraged portfolio selection problem with a thorough borrowing cost representation comprising a number lenders with different rates and credit limits. We propose a two-stage stochastic programming model for asset and debt allocation considering a CVaR-based risk constraint and a convex piecewise-linear borrowing cost function. We compare our model to its counterpart with the fixed borrowing rate approximation used in literature. Numerical results show our model significantly improves performance in terms of risk-return trade-off.

Suggested Citation

  • Davi Michel Valladão & Álvaro Veiga & Alexandre Street, 2018. "A Linear Stochastic Programming Model for Optimal Leveraged Portfolio Selection," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 1021-1032, April.
    • Handle: RePEc:kap:compec:v:51:y:2018:i:4:d:10.1007_s10614-017-9656-x
    DOI: 10.1007/s10614-017-9656-x
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    References listed on IDEAS

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    Cited by:

    1. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    2. Gutierrez, Tomás & Pagnoncelli, Bernardo & Valladão, Davi & Cifuentes, Arturo, 2019. "Can asset allocation limits determine portfolio risk–return profiles in DC pension schemes?," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 134-144.
    3. Xiaonan Chen & Jianfeng Song, 2022. "Influence Path Analysis of Rural Household Portfolio Selection: A Empirical Study Using Structural Equation Modelling Method," The Journal of Real Estate Finance and Economics, Springer, vol. 64(2), pages 298-322, February.
    4. Davi Valladão & Thuener Silva & Marcus Poggi, 2019. "Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns," Annals of Operations Research, Springer, vol. 282(1), pages 379-405, November.

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