A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables

44 Pages Posted: 22 Nov 1999

See all articles by Andrew Ang

Andrew Ang

BlackRock, Inc

Monika Piazzesi

University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: June 6, 2000

Abstract

This paper describes the joint dynamics of bond yields and macroeconomic variables in a vector autoregression, where identifying restrictions are based on the absence of arbitrage. Using a term structure model with inflation and economic growth factors, we investigate how macro factors affect bond prices and the dynamics of the yield curve. Higher order autoregressive lags and moving-average error terms for macro factors are accommodated. The macro factors are augmented by traditional unobserved term-structure factors. Models that incorporate macro factors give better forecasts than traditional term-structure models with only unobservable factors. Variance decompositions show that macro factors explain up to 30\% of the variation in bond yields. Macro factors primarily explain movements at the short end and middle of the yield curve while unobservable factors still account for most movement at the long end of the yield curve.

JEL Classification: C13, C32, E43, E44, E52

Suggested Citation

Ang, Andrew and Piazzesi, Monika, A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables (June 6, 2000). Available at SSRN: https://ssrn.com/abstract=194748 or http://dx.doi.org/10.2139/ssrn.194748

Andrew Ang (Contact Author)

BlackRock, Inc ( email )

55 East 52nd Street
New York City, NY 10055
United States

Monika Piazzesi

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-834-3199 (Phone)
773-702-0458 (Fax)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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