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A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables
Institution:1. Cass Business School and Centre for Economic Policy Research (CEPR), London, UK;2. Institute of Finance, University of Lugano, Via Buffi 13, CH-6900 Lugano, Switzerland;3. Department of Finance, Copenhagen Business School, DK-2000 Frederiksberg, Denmark;2. The Woodrow Wilson School, Princeton University, Princeton, NJ, United States;3. The National Bureau of Economic Research, Cambridge, MA, United States
Abstract:We describe 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, together with latent variables, we investigate how macro variables affect bond prices and the dynamics of the yield curve. We find that the forecasting performance of a VAR improves when no-arbitrage restrictions are imposed and that models with macro factors forecast better than 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.
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