RT Journal Article SR Electronic T1 Explaining Yield Curve Dynamics JF The Journal of Fixed Income FD Institutional Investor Journals SP 68 OP 87 DO 10.3905/jfi.2011.21.2.068 VO 21 IS 2 A1 Roland Füss A1 Olena Nikitina YR 2011 UL https://pm-research.com/content/21/2/68.abstract AB Yield curve dynamics are usually analyzed in terms of the unobservable components—level, slope, and curvature. The factor-augmented vector autoregression (FAVAR) framework applied in this article has become increasingly popular for forecasting interest rates. To link these two strands of research, the authors operate in the space of latent yield and latent macroeconomic factors to analyze the relationship between the term structure of interest rates and the macroeconomic aggregates. They predict the yield curve dynamics by directly forecasting the unobservable yield curve factors. They use the FAVAR methodology to encompass a data-rich environment and to identify dynamic responses of the yield curve to the macroeconomic variables. The empirical results suggest that parsimonious FAVAR models with a few latent macroeconomic factors and a reduced lag order show superior short-horizon forecast performance over simple VAR systems and univariate autoregressions.TOPICS: Fixed-income portfolio management, statistical methods, factor-based models