Information in the Term Structure: A Forecasting Perspective

Hitesh Doshi (), Kris Jacobs () and Rui Liu ()
Additional contact information
Hitesh Doshi: Bauer College of Business, University of Houston, Houston, Texas 77004
Kris Jacobs: Bauer College of Business, University of Houston, Houston, Texas 77004
Rui Liu: Palumbo Donahue School of Business, Duquesne University, Pittsburgh, Pennsylvania 15282

Management Science, 2021, vol. 67, issue 8, 5255-5277

Abstract: The existing literature finds that information not captured by traditional term structure factors helps predict excess bond returns. When estimating no-arbitrage affine term structure models, aligning in-sample and out-of-sample objective functions results in term structure factors that capture information that remains hidden from existing approaches. Specifically, the estimates of the third term structure factor radically differ and are related to the fourth principal component, which helps forecast bond returns. The new objective function leads to substantial improvements in forecasting performance. It also results in higher model term premiums and lower expected future short rates.

Keywords: term structure; forecasting; loss function; state variables; hidden factor (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2020.3715 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:67:y:2021:i:8:p:5255-5277

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().