SDEs with uniform distributions: Peacocks, conic martingales and mean reverting uniform diffusions

Damiano Brigo, Monique Jeanblanc and Frédéric Vrins

Stochastic Processes and their Applications, 2020, vol. 130, issue 7, 3895-3919

Abstract: Peacocks are increasing processes for the convex order. To any peacock, one can associate martingales with the same marginal laws. We are interested in finding the diffusion associated to the uniform peacock, i.e., the peacock with uniform law at all times on a time-varying support [a(t),b(t)]. Following an idea from Dupire (1994), Madan and Yor (2002) propose a construction to find a diffusion martingale associated to a Peacock, under the assumption of existence of a solution to a particular stochastic differential equation (SDE). In this paper we study the SDE associated to the uniform Peacock and give sufficient conditions on the (conic) boundary to have a unique strong or weak solution and analyze the local time at the boundary. Eventually, we focus on the constant support case. Given that the only uniform martingale with time-independent support seems to be a constant, we consider more general (mean-reverting) diffusions. We prove existence of a solution to the related SDE and derive the moments of transition densities. Limit-laws and ergodic results show that the transition law tends to a uniform distribution.

Keywords: Uniformly distributed stochastic differential equation; Conic martingales; Peacock process; Uniformly distributed diffusion; Mean reverting uniform SDE (search for similar items in EconPapers)
Date: 2020
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Related works:
Working Paper: SDES with uniform distributions: Peacocks, conic martingales and mean reverting uniform diffusions (2019)
Working Paper: SDEs with uniform distributions: Peacocks, conic martingales and mean reverting uniform diffusions (2019)
Working Paper: SDEs with Uniform Distributions: Peacocks, Conic Martingales and Mean Reverting Uniform Diffusions (2016)
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DOI: 10.1016/j.spa.2019.11.003

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