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A discrete-time benchmark tracking problem in two markets subject to random environments

Author

Listed:
  • Héctor Jasso-Fuentes

    (CINVESTAV-IPN)

  • Gladys D. Salgado-Suárez

    (CINVESTAV-IPN)

Abstract

In this manuscript, we study a benchmark tracking problem when prices evolve through a Binomial model with a random environment. The agent invests a given fund’s capital into different assets in a predetermined market to replicate at each stage of time a financial index or benchmark. To measure the actual deviation between the agent’s wealth and the current benchmark, we apply a deviation error expressed as a total sum of quadratic functions. We also assume the agent is obligated to change her/his investment between two markets when it is mandatory. This obligation happens when the fund’s wealth falls down a predetermined bankruptcy barrier. The dynamic programming method is then used to get optimal investment strategies that minimize the deviation error as well as to characterize the minimum deviation. We also apply the so-called potential function to analyze the influence of the environment on the prices. Numerical simulations are provided to illustrate our results.

Suggested Citation

  • Héctor Jasso-Fuentes & Gladys D. Salgado-Suárez, 2024. "A discrete-time benchmark tracking problem in two markets subject to random environments," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1265-1294, December.
  • Handle: RePEc:spr:orspec:v:46:y:2024:i:4:d:10.1007_s00291-024-00767-x
    DOI: 10.1007/s00291-024-00767-x
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    References listed on IDEAS

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    1. Lijun Bo & Huafu Liao & Xiang Yu, 2020. "Optimal Tracking Portfolio with A Ratcheting Capital Benchmark," Papers 2006.13661, arXiv.org, revised Apr 2021.
    2. S. Penev & P. V. Shevchenko & W. Wu, 2022. "Myopic robust index tracking with Bregman divergence," Quantitative Finance, Taylor & Francis Journals, vol. 22(2), pages 289-302, February.
    3. Gaivoronski, Alexei A. & Krylov, Sergiy & van der Wijst, Nico, 2005. "Optimal portfolio selection and dynamic benchmark tracking," European Journal of Operational Research, Elsevier, vol. 163(1), pages 115-131, May.
    4. Strub, O. & Baumann, P., 2018. "Optimal construction and rebalancing of index-tracking portfolios," European Journal of Operational Research, Elsevier, vol. 264(1), pages 370-387.
    5. Hu Xiaoping & Cao Jie, 2014. "Randomized Binomial Tree and Pricing of American-Style Options," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-6, March.
    6. Paskalis Glabadanidis, 2020. "Portfolio Strategies to Track and Outperform a Benchmark," JRFM, MDPI, vol. 13(8), pages 1-26, August.
    7. Isabel Castro & Carlos G. Pacheco, 2020. "Modeling and pricing with a random walk in random environment," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(04), pages 1-20, December.
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