We examine whether the predictive power of initial yield spreads of mortgage-backed securities (MBS) vary with the financial cycle. Using a cross-country sample of 4203 MBS, we find that initial yield spreads of MBS incorporate more information than credit ratings and predict future downgrades, even after conditioning on initial credit ratings. Predictive power of spreads is higher during credit and housing bubbles and for the least risky AAA-rated MBS. We find that initial yield spreads capture the magnitude of rating downgrades, especially during asset bubble periods. As a novel approach in this literature, we also utilise machine learning techniques (regression trees, naïve Bayes, support vector machines and random forests) to confirm our results.
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FunderThe authors thank David Marques-Ibanez, Philip Molyneux, Yener Altunbas, Alberto Pozzolo and Mark Rhodes for helpful comments and discussions. Our thanks also to participants at the 2018 Financial Data Science and Econometrics Workshop at the Loughborough University, the 2017 Southern Finance Association?s Key West Conference, the 4th European Conference on Banking and the Economy, and at seminars held at the University of Huddersfield and Nottingham Trent University.
- Asset bubbles
- Credit ratings
- MBS pricing
- Machine learning
ASJC Scopus subject areas
- Business, Management and Accounting(all)