A copula-based data augmentation strategy for the sensitivity analysis of extreme operational losses
A. Khorrami Chokami and
G. Rabitti
Quantitative Finance, 2025, vol. 25, issue 5, 841-849
Abstract:
In this work, we aim to assess the importance of macroeconomic and financial variables for operational losses of UniCredit Bank. To achieve this, we consider the Shapley effects as a variance-based measure of importance. However, the small number of observations of extreme losses makes the estimation of the Shapley effects challenging. To address this issue, we proposed augmenting the sample of extreme observations using vine copulas and calculating the Shapley effects on the augmented sample. The effectiveness of this procedure is supported by a numerical simulation. Findings obtained with our methodology applied to the UniCredit Bank data show its usefulness for the risk management of operational losses.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2025.2487103 (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:quantf:v:25:y:2025:i:5:p:841-849
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20
DOI: 10.1080/14697688.2025.2487103
Access Statistics for this article
Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral
More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().