No arbitrage priors, drifting volatilities, and the term structure of interest rates

We propose a method to produce density forecasts of the term structure of government bond yields that accounts for (i) the possible mispeciÖcation of an underlying Gaussian A¢ ne Term Structure Model (GATSM) and (ii) the time varying volatility of interest rates. For this, we derive a Bayesian prior from a GATSM and use it to estimate the coe¢ cients of a BVAR for the term structure, specifying a common, multiplicative, time varying volatility for the VAR disturbances. Results based on U.S. data show that this method signiÖcantly improves the precision of point and density forecasts of the term structure. We Önd that the forecasting performance improves mainly because the factor structure is imposed not exactly, but as a prior within a more general VAR representation for the yields, and this allows to capture more information on the dynamics with respect to an exact factor model. Instead, the cross-equation no-arbitrage restrictions on the factor loadings only have a marginal role