Bond-CDS Implied Rating Systems

34 Pages Posted: 25 Nov 2014 Last revised: 24 Mar 2020

See all articles by Tommaso Colozza

Tommaso Colozza

Scuola Normale Superiore

Stefano Marmi

Scuola Normale Superiore

Aldo Nassigh

UniCredit Group; Università Bocconi

Daniele Regoli

Scuola Normale Superiore

Date Written: October 20, 2019

Abstract

Market-implied ratings gained importance as efficient early warnings of official credit rating migrations. We build a two-dimensional implied rating system that gathers information from both the bond and the CDS markets. The system is able to outdo each of the corresponding one-dimensional implied ratings in terms of forecast performances. This allows to bypass the debate on which of the two markets can better anticipate eventual rating migrations, since the information is efficiently conveyed in a unique implied rating system. We show that this simple method is also able to outperform implied rating systems based on recent machine learning techniques.

Keywords: credit ratings, market implied ratings, support vector machine, machine learning, credit default swaps, default risk

JEL Classification: C38, D83, G17, G24

Suggested Citation

Colozza, Tommaso and Marmi, Stefano and Nassigh, Aldo and Regoli, Daniele, Bond-CDS Implied Rating Systems (October 20, 2019). Available at SSRN: https://ssrn.com/abstract=2512238 or http://dx.doi.org/10.2139/ssrn.2512238

Tommaso Colozza

Scuola Normale Superiore ( email )

Piazza dei Cavalieri, 7
Pisa, 56126
Italy

Stefano Marmi

Scuola Normale Superiore ( email )

Piazza dei Cavalieri, 7
Pisa, 56126
Italy
+39050509064 (Phone)
+39050563513 (Fax)

HOME PAGE: http://homepage.sns.it/marmi/

Aldo Nassigh

UniCredit Group ( email )

Via San Protaso, 3
Milan, 20121
Italy

Università Bocconi ( email )

Via Sarfatti, 25
Milan, MI 20136
Italy

Daniele Regoli (Contact Author)

Scuola Normale Superiore ( email )

Piazza dei Cavalieri, 7
Pisa, 56126
Italy

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