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Optimal Investment with Insider Information Using Skorokhod & Russo-Vallois Integration

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  • Mauricio Elizalde

    (Departamento de Matemáticas Fundamentales Universidad Nacional de Educación a Distancia Calle de Juan del Rosal, 10)

  • Carlos Escudero

    (Departamento de Matemáticas Fundamentales Universidad Nacional de Educación a Distancia Calle de Juan del Rosal, 10)

  • Tomoyuki Ichiba

    (University of California Santa Barbara)

Abstract

We study the maximization of the logarithmic utility for an insider with different anticipating techniques. Our aim is to compare the utilization of Russo-Vallois forward integral and Skorokhod integral in this context. Theoretical analysis and illustrative numerical examples showcase that the Skorokhod insider outperforms the forward insider. This remarkable observation stands in contrast to the scenario involving risk-neutral traders. Furthermore, an ordinary trader could surpass both insiders if a significant negative fluctuation in the driving stochastic process leads to a sufficiently negative final value. These findings underline the intricate interplay between anticipating stochastic calculus and nonlinear utilities, which may yield non-intuitive results from the financial viewpoint.

Suggested Citation

  • Mauricio Elizalde & Carlos Escudero & Tomoyuki Ichiba, 2025. "Optimal Investment with Insider Information Using Skorokhod & Russo-Vallois Integration," Journal of Optimization Theory and Applications, Springer, vol. 207(3), pages 1-43, December.
    • Handle: RePEc:spr:joptap:v:207:y:2025:i:3:d:10.1007_s10957-025-02789-z
    DOI: 10.1007/s10957-025-02789-z
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    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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