arXiv Open Access 2016

Pathwise Iteration for Backward SDEs

Christian Bender Christian Gaertner Nikolaus Schweizer
Lihat Sumber

Abstrak

We introduce a novel numerical approach for a class of stochastic dynamic programs which arise as discretizations of backward stochastic differential equations or semi-linear partial differential equations. Solving such dynamic programs numerically requires the approximation of nested conditional expectations, i.e., iterated integrals of previous approximations. Our approach allows us to compute and iteratively improve upper and lower bounds on the true solution starting from an arbitrary and possibly crude input approximation. We demonstrate the benefits of our approach in a high dimensional financial application.

Penulis (3)

C

Christian Bender

C

Christian Gaertner

N

Nikolaus Schweizer

Format Sitasi

Bender, C., Gaertner, C., Schweizer, N. (2016). Pathwise Iteration for Backward SDEs. https://arxiv.org/abs/1605.07500

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2016
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓