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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: ECB Working Paper ; No. 544

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Interest Rates: Determination, Term Structure, and Effects ; Financial Markets and the Macroeconomy ; Monetary Policy
• Subject: Affine term structure models ; Dynamic Factor Models ; FAVAR ; yield curve ; Zinsstruktur ; Rendite ; VAR-Modell ; Theorie ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Mönch, Emanuel
• Event: Veröffentlichung
• (who): European Central Bank (ECB)
• (where): Frankfurt a. M.
• (when): 2005

Further information

• Handle: http://hdl.handle.net/10419/152978
• Last update: 10.03.2025, 11:42 AM CET