9
IRUS TotalDownloads
Altmetric
A unified approach to well-posedness of type-I backward stochastic Volterra integral equations
File | Description | Size | Format | |
---|---|---|---|---|
21-EJP653.pdf | Published version | 757.29 kB | Adobe PDF | View/Open |
Title: | A unified approach to well-posedness of type-I backward stochastic Volterra integral equations |
Authors: | Hernández, C Possamaï, D |
Item Type: | Journal Article |
Abstract: | We study a novel general class of multidimensional type-I backward stochastic Volterra integral equations. Toward this goal, we introduce an infinite family of standard backward SDEs and establish its well-posedness, and we show that it is equivalent to that of a type-I backward stochastic Volterra integral equation. We also establish a representation formula in terms of non-linear semi-linear partial differential equation of Hamilton–Jacobi–Bellman type. As an application, we consider the study of time-inconsistent stochastic control from a game-theoretic point of view. We show the equivalence of two current approaches to this problem from both a probabilistic and an analytic point of view. |
Issue Date: | 22-Jun-2021 |
Date of Acceptance: | 22-May-2021 |
URI: | http://hdl.handle.net/10044/1/91794 |
DOI: | 10.1214/21-ejp653 |
ISSN: | 1083-6489 |
Publisher: | Institute of Mathematical Statistics |
Start Page: | 1 |
End Page: | 35 |
Journal / Book Title: | Electronic Journal of Probability |
Volume: | 26 |
Issue: | none |
Copyright Statement: | © 2021 The Author(s). This work is licensed under Creative Commons Attribution 4.0 International License. |
Keywords: | 0104 Statistics 0105 Mathematical Physics Statistics & Probability |
Publication Status: | Published |
Open Access location: | https://projecteuclid.org/journals/electronic-journal-of-probability/volume-26/issue-none/A-unified-approach-to-well-posedness-of-type-I-backward/10.1214/21-EJP653.full |
Online Publication Date: | 2021-06-22 |
Appears in Collections: | Financial Mathematics Mathematics |
This item is licensed under a Creative Commons License