Reflected Backward Stochastic Differential Equation with Rank-Based Data

Zhen Qing Chen, Xinwei Feng*

*Corresponding author for this work

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Abstract

In this paper, we study reflected backward stochastic differential equation (reflected BSDE) with rank-based data in a Markovian framework; that is, the solution to the reflected BSDE is above a prescribed boundary process in a minimal fashion and the generator and terminal value of the reflected BSDE depend on the solution of another stochastic differential equation (SDE) with rank-based drift and diffusion coefficients. We derive regularity properties of the solution to such reflected BSDE and show that the solution at the initial starting time t and position x, which is a deterministic function, is the unique viscosity solution to some obstacle problem (or variational inequality) for the corresponding parabolic partial differential equation.

Original languageEnglish
Pages (from-to)1213-1247
Number of pages35
JournalJournal of Theoretical Probability
Volume34
Issue number3
DOIs
Publication statusPublished - Sept 2021
Externally publishedYes

Keywords

  • Obstacle problem
  • Partial differential equation
  • Rank-based coefficients
  • Reflected backward stochastic differential equation
  • Viscosity solution

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Chen, Z. Q., & Feng, X. (2021). Reflected Backward Stochastic Differential Equation with Rank-Based Data. Journal of Theoretical Probability, 34(3), 1213-1247. https://doi.org/10.1007/s10959-020-01026-9