A general comparison theorem for reflected BSDEs
Mun-Chol Kim and
Statistics & Probability Letters, 2021, vol. 173, issue C
In this paper, we deal with a large class of reflected backward stochastic differential equations (RBSDEs for short) with an arbitrary filtered probability space. We prove the comparison theorem for them in three different methods: a direct argument, characterization method and penalization method.
Keywords: Reflected backward stochastic differential equation; Comparison theorem; Filtered probability space; Girsanov theorem; Characterization; Penalization method (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:173:y:2021:i:c:s0167715221000201
Ordering information: This journal article can be ordered from
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().