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A Family of Non-Gaussian Martingales with Gaussian Marginals

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  • Kais Hamza
  • Fima C. Klebaner

Abstract

We construct a family of martingales with Gaussian marginal distributions. We give a weak construction as Markov, inhomogeneous in time processes, and compute their infinitesimal generators. We give the predictable quadratic variation and show that the paths are not continuous. The construction uses distributions G σ having a log-convolution semigroup property. Further, we categorize these processes as belonging to one of two classes, one of which is made up of piecewise deterministic pure jump processes. This class includes the case where G σ is an inverse log-Poisson distribution. The processes in the second class include the case where G σ is an inverse log-gamma distribution. The richness of the family has the potential to allow for the imposition of specifications other than the marginal distributions.

Suggested Citation

  • Kais Hamza & Fima C. Klebaner, 2007. "A Family of Non-Gaussian Martingales with Gaussian Marginals," International Journal of Stochastic Analysis, Hindawi, vol. 2007, pages 1-19, August.
    • Handle: RePEc:hin:jnijsa:092723
    DOI: 10.1155/2007/92723
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    Cited by:

    1. Mathias Beiglbock & George Lowther & Gudmund Pammer & Walter Schachermayer, 2021. "Faking Brownian motion with continuous Markov martingales," Papers 2109.12927, arXiv.org.
    2. Mathias Beiglbock & Gudmund Pammer & Walter Schachermayer, 2021. "From Bachelier to Dupire via Optimal Transport," Papers 2106.12395, arXiv.org.

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