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Stochastic Analysis of Gaussian Processes via Fredholm Representation

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  • Tommi Sottinen
  • Lauri Viitasaari

Abstract

We show that every separable Gaussian process with integrable variance function admits a Fredholm representation with respect to a Brownian motion. We extend the Fredholm representation to a transfer principle and develop stochastic analysis by using it. We show the convenience of the Fredholm representation by giving applications to equivalence in law, bridges, series expansions, stochastic differential equations, and maximum likelihood estimations.

Suggested Citation

  • Tommi Sottinen & Lauri Viitasaari, 2016. "Stochastic Analysis of Gaussian Processes via Fredholm Representation," International Journal of Stochastic Analysis, Hindawi, vol. 2016, pages 1-15, July.
    • Handle: RePEc:hin:jnijsa:8694365
    DOI: 10.1155/2016/8694365
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    Cited by:

    1. Eduardo Abi Jaber, 2022. "The characteristic function of Gaussian stochastic volatility models: an analytic expression," Finance and Stochastics, Springer, vol. 26(4), pages 733-769, October.
    2. Tommi Sottinen & Lauri Viitasaari, 2018. "Parameter estimation for the Langevin equation with stationary-increment Gaussian noise," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 569-601, October.
    3. Eduardo Abi Jaber, 2022. "The Laplace transform of the integrated Volterra Wishart process," Mathematical Finance, Wiley Blackwell, vol. 32(1), pages 309-348, January.
    4. Miriana Cellupica & Barbara Pacchiarotti, 2021. "Pathwise Asymptotics for Volterra Type Stochastic Volatility Models," Journal of Theoretical Probability, Springer, vol. 34(2), pages 682-727, June.
    5. Tommi Sottinen & Lauri Viitasaari, 2018. "Conditional-Mean Hedging Under Transaction Costs In Gaussian Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-15, March.
    6. Gulisashvili, Archil, 2020. "Gaussian stochastic volatility models: Scaling regimes, large deviations, and moment explosions," Stochastic Processes and their Applications, Elsevier, vol. 130(6), pages 3648-3686.

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