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

51 Pages Posted: 28 Jun 2001 Last revised: 9 Nov 2022

See all articles by Andrew Ang

Andrew Ang

BlackRock, Inc

Monika Piazzesi

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

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Date Written: July 2001

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 variables affect bond prices and the dynamics of the yield curve. The setup accommodates higher order autoregressive lags for the macro factors. The macro variables are augmented by traditional unobserved term structure factors. We find that the forecasting performance of a VAR improves when no-arbitrage restrictions are imposed. Models that incorporate macro factors forecast better than traditional term structure models with only unobservable factors. Variance decompositions show that macro factors explain up to 85% 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 of the movement at the long end of the yield curve.

Suggested Citation

Ang, Andrew and Piazzesi, Monika, A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables (July 2001). NBER Working Paper No. w8363, Available at SSRN: https://ssrn.com/abstract=275437

Andrew Ang (Contact Author)

BlackRock, Inc ( email )

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

Monika Piazzesi

Stanford University ( email )

Stanford, CA 94305
United States

University of Chicago - Booth School of Business ( email )

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773-834-3199 (Phone)
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National Bureau of Economic Research (NBER) ( email )

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