Credit risk assessment of fixed income portfolios using explicit expressions

Pagnoncelli, BK; Cifuentes, A.

Keywords: correlation, Credit risk, Expected loss

Abstract

We propose a model to assess the credit risk features of fixed income portfolios assuming they can be characterized by two parameters: their default probability and their default correlation. We rely on explicit expressions to assess their credit risk and demonstrate the benefits of our approach in a complex leveraged structure example. We show that using expected loss as a proxy for credit risk is misleading as it does not capture the dispersion effects introduced by correlation. The implications of these findings are relevant for improving current risk management practices and for regulation purposes. (C) 2014 Elsevier Inc. All rights reserved.

Más información

Título según WOS: Credit risk assessment of fixed income portfolios using explicit expressions
Título según SCOPUS: Credit risk assessment of fixed income portfolios using explicit expressions
Título de la Revista: FINANCE RESEARCH LETTERS
Volumen: 11
Número: 3
Editorial: ACADEMIC PRESS INC ELSEVIER SCIENCE
Fecha de publicación: 2014
Página de inicio: 224
Página final: 230
Idioma: English
DOI:

10.1016/j.frl.2014.02.007

Notas: ISI, SCOPUS