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ANDREA CIPOLLINI

Leading indicator properties of US high-yield credit spreads.

  • Authors: Cipollini, A; Aslanidis, N
  • Publication year: 2010
  • Type: Articolo in rivista (Articolo in rivista)
  • Key words: Credit spreads; Principal components; Forecasting; Real-time data
  • OA Link: http://hdl.handle.net/10447/99049

Abstract

In this paper we examine the out-of-sample forecast performance of high-yield credit spreads for real-time and revised data regarding employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest that the best results come from using only a few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. In particular, for employment and at short-run horizons, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks. Moreover, forecast results based on revised data are qualitatively similar to those obtained using real-time data