Computation of VaR for portfolios in intensity models

Shiyu Song and Ying Lu

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 16, 5910-5923

Abstract: In this article, we calculate the value-at-risk (VaR) for large portfolios in intensity models, where the idiosyncratic and systematic risk exposures as well as the impact of past default losses are subsumed into the intensity processes. The adopted method is based on the theory of saddlepoint approximation for continuous-time Markov processes whose transition densities and distribution functions can be approximated in closed forms. A simple example with theoretical and numerical results is presented in the end.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2023.2237221 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:53:y:2024:i:16:p:5910-5923

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2023.2237221

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().