Measures of Joint Default Dependence Risk based on Copulas

Aihua Huang, Wende Yi

2022

Abstract

This paper studies the problem of forecasting joint default. The default is the result that the credit rating of an obligor, determined by obligor’s operating situation and financing state, decreases to some certain degree. The dependence relationship of financing indexes is investigated to judge the credit rating of an obligor and the conditional dependence probability and probability density functions are proposed. A member of conditional dependence risk relationships is completely characterized by the marginal distribution and the copulas of random variables. These results can be applied to investigate the conditional dependence structure and the conditional dependence measure of obligor’s assets and of the defaults among obligors.

Paper Citation

in Harvard Style

Huang A. and Yi W. (2022). Measures of Joint Default Dependence Risk based on Copulas. In Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM, ISBN 978-989-758-593-7, pages 654-657. DOI: 10.5220/0011203700003440

in Bibtex Style

@conference{bdedm22,
author={Aihua Huang and Wende Yi},
title={Measures of Joint Default Dependence Risk based on Copulas},
booktitle={Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,},
year={2022},
pages={654-657},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011203700003440},
isbn={978-989-758-593-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,
TI - Measures of Joint Default Dependence Risk based on Copulas
SN - 978-989-758-593-7
AU - Huang A.
AU - Yi W.
PY - 2022
SP - 654
EP - 657
DO - 10.5220/0011203700003440