A simulation-based method for estimating systemic risk measures

Wuyi Ye, Yi Zhou, Pengzhan Chen and Bin Wu

European Journal of Operational Research, 2024, vol. 313, issue 1, 312-324

Abstract: This paper focuses on simulation-based approaches for estimating systemic risk measures. In particular, we provide the asymptotic forms of the relative errors for widely used systemic risk measures including conditional value-at-risk (CoVaR), coexpected shortfall (CoES) and marginal expected shortfall (MES). Based on asymptotic expansions, a general framework is provided for the simulation of systemic risk measures. The numerical results show that the proposed simulation framework works well, and it is more user-friendly, easier to expand and less time-consuming than simulation approaches using the resampling method and importance sampling.

Keywords: Risk management; Systemic risk measures; Relative errors; Asymptotic expansions; Simulation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221723006616
Full text for ScienceDirect subscribers only

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:eee:ejores:v:313:y:2024:i:1:p:312-324

DOI: 10.1016/j.ejor.2023.08.032

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().