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Bond Risk Premia and Gaussian Term Structure Models.
- Source :
- Management Science; Mar2018, Vol. 64 Issue 3, p1413-1439, 28p
- Publication Year :
- 2018
-
Abstract
- Existing results show that (i) lagged forward rates help predict bond returns and (ii) modern Markovian dynamic term structure models (DTSMs) cannot match the evidence [Cochrane JH, Piazzesi M (2005) Bond risk premia. Amer. Econom. Rev.95(1): 138-160]. We develop the family of conditional mean DTSMs where the dynamics depend on current yields and their history through a moving-average component. Our preferred conditional mean model combines one moving average with the usual three Gaussian risk factors, closely matches the bond risk premium measured from predictive regressions, and provides better forecasts of bond returns. Our framework nests Duffee's models with a small "hidden" factor [Duffee G (2011) Information in (and not in) the term structure. Rev. Financial Stud.24(9):2895-2934], and our results compare favorably with his five-factor model. Conditional mean models are easier to estimate than state-space term structure models based on Kalman estimates of latent factors. [ABSTRACT FROM AUTHOR]
- Subjects :
- BONDS (Finance)
YIELD curve (Finance)
RISK premiums
RATE of return
INTEREST rates
Subjects
Details
- Language :
- English
- ISSN :
- 00251909
- Volume :
- 64
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Management Science
- Publication Type :
- Academic Journal
- Accession number :
- 128850185
- Full Text :
- https://doi.org/10.1287/mnsc.2016.2602