Market-implied ratings gained importance as efficient early warnings of official credit rating migrations. We build a two-dimensional implied rating system based on bonds and CDS spreads, and test its forecast performances on a set of worldwide sovereign issuers. We show that the method efficiently uses the information from both markets, and is able to outperform implied ratings based on recent machine learning techniques. (c) 2022 Elsevier Inc. All rights reserved.

Bond-CDS implied rating systems

Colozza, Tommaso;Marmi, Stefano;Nassigh, Aldo;Regoli, Daniele
2022

Abstract

Market-implied ratings gained importance as efficient early warnings of official credit rating migrations. We build a two-dimensional implied rating system based on bonds and CDS spreads, and test its forecast performances on a set of worldwide sovereign issuers. We show that the method efficiently uses the information from both markets, and is able to outperform implied ratings based on recent machine learning techniques. (c) 2022 Elsevier Inc. All rights reserved.
2022
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
Implied rating; Machine learning; Rating migrations forecasts
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/129005
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