MALLIAVIN CALCULUS FOR THE ESTIMATION OF TIME-VARYING REGRESSION MODELS USED IN FINANCIAL APPLICATIONS
Ahmed Abutaleb () and
International Journal of Theoretical and Applied Finance (IJTAF), 2007, vol. 10, issue 05, 771-800
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.
Keywords: Stochastic calculus; Malliavin calculus; time-varying parameters; time-series analysis; Clark–Ocone formula; Ornstein–Uhlenbeck process (search for similar items in EconPapers)
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