Log-Harnack Inequality and Exponential Ergodicity for Distribution Dependent Chan–Karolyi–Longstaff–Sanders and Vasicek Models

Yifan Bai () and Xing Huang ()
Additional contact information
Yifan Bai: Peking University
Xing Huang: Tianjin University

Journal of Theoretical Probability, 2023, vol. 36, issue 3, 1902-1921

Abstract: Abstract In this paper, Wang’s log-Harnack inequality and exponential ergodicity are derived for two types of distribution dependent SDEs: one is the Chan–Karolyi–Longstaff–Sanders (CKLS) model, where the diffusion coefficient is a power function of order $$\theta $$ θ with $$\theta \in [\frac{1}{2},1)$$ θ ∈ [ 1 2 , 1 ) ; the other one is the Vasicek model, where the diffusion coefficient only depends on distribution. Both models in the distribution-independent case can be used to characterize the interest rate in mathematical finance.

Keywords: Log-Harnack inequality; Exponential ergodicity; McKean–Vlasov SDEs; Wasserstein distance; Relative entropy; 60H10; 60H15 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10959-022-01210-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jotpro:v:36:y:2023:i:3:d:10.1007_s10959-022-01210-z

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10959

DOI: 10.1007/s10959-022-01210-z

Access Statistics for this article

Journal of Theoretical Probability is currently edited by Andrea Monica

More articles in Journal of Theoretical Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().