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Predictable forward utility processes under ambiguity

Author

Listed:
  • Jiale Du

    (Institute for Financial Studies and School of Mathematics, Shandong University, Jinan 250100, Shandong, China)

  • Shuo Li

    (��School of Mathematics and Data Sciences, Changji University, Changji 831100, Xinjiang, China)

  • Fuguo Liu

    (��School of Mathematics and Data Sciences, Changji University, Changji 831100, Xinjiang, China)

  • Yufeng Shi

    (Institute for Financial Studies and School of Mathematics, Shandong University, Jinan 250100, Shandong, China‡National Center for Applied Mathematics of Shandong, Shandong University, Jinan 250100, Shandong, China)

Abstract

Driven by the need for more effective decision-making tools amid market volatility and ambiguity, the authors aim to develop a robust and detailed forecasting model that enhances the understanding of market uncertainty and risk, providing investors with precise guidance for their decisions. To achieve this goal, we employ Bayesian functions to refine forward utility models, thereby improving market forecasting accuracy under uncertain conditions. This work contributes to the literature by introducing a more detailed method for estimating model parameters. The adaptability of this model allows for its application across various market scenarios, representing a significant advancement over traditional methods. In summary, this research deepens our understanding of market dynamics and equips investors with a more reliable tool for navigating uncertain financial landscapes.

Suggested Citation

  • Jiale Du & Shuo Li & Fuguo Liu & Yufeng Shi, 2025. "Predictable forward utility processes under ambiguity," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 1-16, June.
    • Handle: RePEc:wsi:ijfexx:v:12:y:2025:i:02:n:s2424786325500148
    DOI: 10.1142/S2424786325500148
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