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Prediction Law of Mixed Gaussian Volterra Processes

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  • Tommi Sottinen
  • Lauri Viitasaari

Abstract

We study the regular conditional law of mixed Gaussian Volterra processes under the influence of model disturbances. More precisely, we study prediction of Gaussian Volterra processes driven by a Brownian motion in a case where the Brownian motion is not observable, but only a noisy version is observed. As an application, we discuss how our result can be applied to variance reduction in the presence of measurement errors.

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  • Tommi Sottinen & Lauri Viitasaari, 2019. "Prediction Law of Mixed Gaussian Volterra Processes," Papers 1904.09799, arXiv.org.
    • Handle: RePEc:arx:papers:1904.09799
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    File URL: http://arxiv.org/pdf/1904.09799
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    References listed on IDEAS

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    1. Sottinen, Tommi & Yazigi, Adil, 2014. "Generalized Gaussian bridges," Stochastic Processes and their Applications, Elsevier, vol. 124(9), pages 3084-3105.
    2. Foad Shokrollahi & Tommi Sottinen, 2017. "Hedging in fractional Black-Scholes model with transaction costs," Papers 1706.01534, arXiv.org, revised Jul 2017.
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