Buy this book
"Empirical evidence suggests that excess bond returns are forecastable by financial indicators such as forward spreads and yield spreads, a violation of the expectations hypothesis based on constant risk premia. But existing evidence does not tie the forecastable variation in excess bond returns to underlying macroeconomic fundamentals, as would be expected if the forecastability were attributable to time variation in risk premia. We use the methodology of dynamic factor analysis for large datasets to investigate possible empirical linkages between forecastable variation in excess bond returns and macroeconomic fundamentals. We find that several common factors estimated from a large dataset on U.S. economic activity have important forecasting power for future excess returns on U.S. government bonds. Following Cochrane and Piazzesi (2005), we also construct single predictor state variables by forming linear combinations of either five or six estimated common factors. The single state variables forecast excess bond returns at maturities from two to five years, and do so virtually as well as an unrestricted regression model that includes each common factor as a separate predictor variable. The linear combinations we form are driven by both "real" and "inflation" macro factors, in addition to financial factors, and contain important information about one year ahead excess bond returns that is not captured by forward spreads, yield spreads, or the principal components of the yield covariance matrix"--National Bureau of Economic Research web site.
Buy this book
Subjects
Bonds, Mathematical models, Rate of return, RiskPlaces
United States, Unites StatesEdition | Availability |
---|---|
1
Macro factors in bond risk premia
2005, National Bureau of Economic Research
Electronic resource
in English
|
aaaa
|
Book Details
Edition Notes
Includes bibliographical references.
Title from PDF file as viewed on 11/28/2005.
Also available in print.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.
Classifications
The Physical Object
ID Numbers
Community Reviews (0)
Feedback?December 13, 2020 | Edited by MARC Bot | import existing book |
December 5, 2010 | Edited by Open Library Bot | Added subjects from MARC records. |
December 10, 2009 | Created by WorkBot | add works page |