Forecasting the yield curve with linear factor models

In this work we compare the interest rate forecasting performance of a broad class of linear models. The models are estimated through a MCMC procedure with data from the US and Brazilian markets. We show that a simple parametric specification has the best predictive power, but it does not outperform the random walk. We also find that macroeconomic variables and no-arbitrage conditions have little effect to improve the out-of-sample fit, while a financial variable (Stock Index) increases the forecasting accuracy.