Forecasting the yield curve in a data-rich environment: a no-arbitrage factor-augmented VAR approach

Emanuel Mönch
Authors registered in the RePEc Author Service: Emanuel Moench

No 544, Working Paper Series from European Central Bank

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

Keywords: Affine term structure models; dynamic factor models; FAVAR; yield curve (search for similar items in EconPapers)
Date: 2005-11
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Citations: View citations in EconPapers (9)

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Journal Article: Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:2005544

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