Please use this identifier to cite or link to this item: doi:10.22028/D291-30263
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Title: A PRIMAL–DUAL ALGORITHM FOR BSDES
Author(s): Bender, Christian
Schweizer, Nikolaus
Zhuo, Jia
Language: English
Title: Mathematical Finance
Volume: 27
Issue: 3
Startpage: 866
Endpage: 901
Publisher/Platform: Wiley-Blackwell - SSH
Year of Publication: 2017
Publikation type: Journal Article
Abstract: We generalize the primal–dual methodology, which is popular in the pricing of early‐exercise options, to a backward dynamic programming equation associated with time discretization schemes of (reflected) backward stochastic differential equations (BSDEs). Taking as an input some approximate solution of the backward dynamic program, which was precomputed, e.g., by least‐squares Monte Carlo, this methodology enables us to construct a confidence interval for the unknown true solution of the time‐discretized (reflected) BSDE at time 0. We numerically demonstrate the practical applicability of our method in two 5‐dimensional nonlinear pricing problems where tight price bounds were previously unavailable.
DOI of the first publication: 10.1111/mafi.12100
URL of the first publication: https://onlinelibrary.wiley.com/doi/full/10.1111/mafi.12100
Link to this record: hdl:20.500.11880/28700
http://dx.doi.org/10.22028/D291-30263
ISSN: 1467-9965
0960-1627
Date of registration: 17-Feb-2020
Third-party funds sponsorship: Deutsche Forschungsgemeinschaft
Sponsorship ID: BE3933/5‐1
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Mathematik
Professorship: MI - Prof. Dr. Christian Bender
Collections:UniBib – Die Universitätsbibliographie

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