Can credit spreads help predict a yield curve?

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초록

In this paper we investigate whether information in credit spreads helps improve the forecasts of government bond yields. To do this, we propose and estimate a joint dynamic Nelson-Siegel (DNS) model of the U.S. Treasury yield curve and the credit spread curve. The model accounts for the possibility of regime changes in yield curve dynamics and incorporates a zero lower bound constraint on yields. We show that our joint model produces more accurate out-of sample density forecasts of bond yields than does the yield-only DNS model. In addition, we demonstrate that incorporating regime changes and a zero lower bound constraint is essential for forecast improvements. (C) 2016 Elsevier Ltd. All rights reserved.

키워드

Density predictionDynamic Nelson-SiegelPredictive likelihoodBayesian MCMC estimationGOVERNMENT BOND YIELDSTERM STRUCTURE MODELSAFFINE MODELSDETERMINANTSFORECASTSDENSITYUS
제목
Can credit spreads help predict a yield curve?
저자
Abdymomunov, AzamatKang, Kyu HoKim, Ki Jeong
DOI
10.1016/j.jimonfin.2016.02.003
발행일
2016-06
유형
Article
저널명
Journal of International Money and Finance
64
페이지
39 ~ 61