Work

A copula-based data augmentation strategy for the sensitivity analysis of extreme operational losses

Year: 2025

Type: article

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.

Source: Quantitative Finance

DOI: 10.1080/14697688.2025.2487103

Authors: A. Khorrami Chokami, G. Rabitti

Institutions: University of Cagliari, Heriot-Watt University, Maxwell Institute for Mathematical Sciences

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W4409726624

FWCI: 0.939

Cites: 34

Cited by: 1

Related to: 10