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Evolutionary models in cash management policies with multiple assets

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  • Moraes, Marcelo Botelho da Costa
  • Nagano, Marcelo Seido

Abstract

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using multiple asset investments. This problem consists of a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the total cost of cash maintenance, by obtaining the parameters of a cash management policy with three assets (cash and two investments), and using the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash management policy, but with better results for the PSO model.

Suggested Citation

  • Moraes, Marcelo Botelho da Costa & Nagano, Marcelo Seido, 2014. "Evolutionary models in cash management policies with multiple assets," Economic Modelling, Elsevier, vol. 39(C), pages 1-7.
    • Handle: RePEc:eee:ecmode:v:39:y:2014:i:c:p:1-7
    DOI: 10.1016/j.econmod.2014.02.010
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    References listed on IDEAS

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    8. Hinderer, K. & Waldmann, K. -H., 2001. "Cash management in a randomly varying environment," European Journal of Operational Research, Elsevier, vol. 130(3), pages 468-485, May.
    9. Baccarin, Stefano, 2009. "Optimal impulse control for a multidimensional cash management system with generalized cost functions," European Journal of Operational Research, Elsevier, vol. 196(1), pages 198-206, July.
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    Citations

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    Cited by:

    1. Salas-Molina, Francisco & Martin, Francisco J. & Rodríguez-Aguilar, Juan A. & Serrà, Joan & Arcos, Josep Ll., 2017. "Empowering cash managers to achieve cost savings by improving predictive accuracy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 403-415.
    2. Francisco Salas-Molina, 2024. "Fitting random cash management models to data," Papers 2401.08548, arXiv.org.
    3. Francisco Salas-Molina, 2020. "Risk-sensitive control of cash management systems," Operational Research, Springer, vol. 20(2), pages 1159-1176, June.
    4. Francisco Salas-Molina & Juan A. Rodríguez-Aguilar & Montserrat Guillen, 2023. "A multidimensional review of the cash management problem," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-35, December.
    5. Schroeder, Pascal & Kacem, Imed, 2020. "Competitive difference analysis of the cash management problem with uncertain demands," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1183-1192.
    6. Francisco Salas-Molina & Juan A. Rodríguez-Aguilar, 2018. "Data-driven multiobjective decision-making in cash management," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 77-91, June.
    7. Yonit Barron, 2022. "A probabilistic approach to the stochastic fluid cash management balance problem," Annals of Operations Research, Springer, vol. 312(2), pages 607-645, May.
    8. Francisco Salas-Molina & David Pla-Santamaria & Juan A. Rodriguez-Aguilar, 2018. "A multi-objective approach to the cash management problem," Annals of Operations Research, Springer, vol. 267(1), pages 515-529, August.
    9. Barron, Yonit, 2023. "A stochastic card balance management problem with continuous and batch-type bilateral transactions," Operations Research Perspectives, Elsevier, vol. 10(C).

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