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Optimal Portfolios for Different Anticipating Integrals under Insider Information

Author

Listed:
  • Carlos Escudero

    (Departamento de Matemáticas Fundamentales, Universidad Nacional de Educación a Distancia, 28040 Madrid, Spain)

  • Sandra Ranilla-Cortina

    (Departamento de Análisis Matemático y Matemática Aplicada, Universidad Complutense de Madrid, 28040 Madrid, Spain)

Abstract

We consider the non-adapted version of a simple problem of portfolio optimization in a financial market that results from the presence of insider information. We analyze it via anticipating stochastic calculus and compare the results obtained by means of the Russo-Vallois forward, the Ayed-Kuo, and the Hitsuda-Skorokhod integrals. We compute the optimal portfolio for each of these cases with the aim of establishing a comparison between these integrals in order to clarify their potential use in this type of problem. Our results give a partial indication that, while the forward integral yields a portfolio that is financially meaningful, the Ayed-Kuo and the Hitsuda-Skorokhod integrals do not provide an appropriate investment strategy for this problem.

Suggested Citation

  • Carlos Escudero & Sandra Ranilla-Cortina, 2020. "Optimal Portfolios for Different Anticipating Integrals under Insider Information," Mathematics, MDPI, vol. 9(1), pages 1-19, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2020:i:1:p:75-:d:472914
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    References listed on IDEAS

    as
    1. Jorge A. León & Reyla Navarro & David Nualart, 2003. "An Anticipating Calculus Approach to the Utility Maximization of an Insider," Mathematical Finance, Wiley Blackwell, vol. 13(1), pages 171-185, January.
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