FORECASTING THE YIELD CURVE USING PRIORS FROM NO‐ARBITRAGE AFFINE TERM STRUCTURE MODELS*
提出一种利用无套利仿射期限结构模型约束作为先验信息而非强制约束的策略，用于预测美国五类收益率，在12个月预测期内显著提升了预测精度。
I propose a strategy for forecasting the term structure of interest rates that may produce significant gains in predictive accuracy. The key idea is to use the restrictions implied by Gaussian, no‐arbitrage, affine term structure models on a vector autoregression as prior information instead of imposing the restrictions dogmatically. This allows us to account for possible model misspecification. We use the proposed method to forecast a system of five U.S. yields up to 12 months ahead, and we find it provides significant gains in forecast accuracy.