Abstract
We study backward doubly stochastic differential equations when the coefficients are continuous with stochastic linear growth. Via an approximation and comparison theorem, the existence of minimal and maximal solutions are obtained.
References
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© 2018 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- An approximation result and Monte Carlo simulation of the adapted solution of the one-dimensional backward stochastic differential equation
- Fractional anticipated BSDEs with stochastic Lipschitz coefficients
- A multi-class extension of the mean field Bolker–Pacala population model
- Backward doubly SDEs with continuous and stochastic linear growth coefficients
- The stationary regions for the parameter space of unilateral second-order spatial AR model
Artikel in diesem Heft
- Frontmatter
- An approximation result and Monte Carlo simulation of the adapted solution of the one-dimensional backward stochastic differential equation
- Fractional anticipated BSDEs with stochastic Lipschitz coefficients
- A multi-class extension of the mean field Bolker–Pacala population model
- Backward doubly SDEs with continuous and stochastic linear growth coefficients
- The stationary regions for the parameter space of unilateral second-order spatial AR model