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Malliavin Calculus For The Estimation Of Time-Varying Regression Models Used In Financial Applications

Author

Listed:
  • AHMED ABUTALEB

    (Cairo University, School of Engineering, Systems and Bioengineering Departments, Giza, Egypt)

  • MICHAEL G. PAPAIOANNOU

    (International Monetary Fund, 700 19th Street, N.W., Washington D. C. 20431, USA)

Abstract

The paper introduces a new method for the estimation of time-varying regression coefficients employed in financial modeling. We use Malliavin calculus (stochastic calculus of variations) to estimate the time-varying regression coefficients that appear in linear regression models, and the generalized Clark–Ocone formula to derive a closed-form solution for the estimates of the time-varying coefficients. While this approach can be applied to any signal model, we present its application to signals modeled as a Brownian motion and an Ornstein–Uhlenbeck process. Simulation results prove the superiority of the proposed method, as compared to conventional methods.

Suggested Citation

  • Ahmed Abutaleb & Michael G. Papaioannou, 2007. "Malliavin Calculus For The Estimation Of Time-Varying Regression Models Used In Financial Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 771-800.
    • Handle: RePEc:wsi:ijtafx:v:10:y:2007:i:05:n:s021902490700441x
    DOI: 10.1142/S021902490700441X
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