Forecasting the Yield Curve in a Data-Rich Environment: A No-Arbitrage Factor-Augmented VAR Approach
Federal Reserve Bank of New York
EFA 2005 Moscow Meetings
ECB Working Paper No. 544
AFA 2007 Chicago Meetings Paper
This paper suggests a term structure model which parsimoniously exploits a broad macroeconomic information set. The model does not incorporate latent yield curve factors, but instead uses the common components of a large number of macroeconomic variables and the short rate as explanatory factors. Precisely, an affine term structure model with parameter restrictions implied by no-arbitrage is added to a Factor-Augmented Vector Autoregression (FAVAR). The model is found to strongly outperform different benchmark models in out-of-sample yield forecasts, reducing root mean squared forecast errors relative to the random walk up to 50% for short and around 20% for long maturities.
Number of Pages in PDF File: 41
Keywords: Affine term structure models, Yield curve, dynamic factor models, FAVAR
JEL Classification: C13, C32, E43, E44, E52working papers series
Date posted: March 6, 2005
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