In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding employment and industrial production in the US, using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor.
Cipollini, A. e N., Aslanidis. "Leading indicator properties of US high-yield credit spread" Working paper, RECENT WORKING PAPER SERIES, Dipartimento di Economia Marco Biagi – Università di Modena e Reggio Emilia, 2007.
Leading indicator properties of US high-yield credit spread
Cipollini, A.;
2007
Abstract
In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding employment and industrial production in the US, using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor.File | Dimensione | Formato | |
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