Term Premia and Interest Rate Forecasts in Affine Models
标准仿射模型预测国债收益率效果差，因为风险补偿与利率波动挂钩；本文提出“本质仿射”模型，允许两者独立变化，从而改进预测。
ABSTRACT The standard class of affine models produces poor forecasts of future Treasury yields. Better forecasts are generated by assuming that yields follow random walks. The failure of these models is driven by one of their key features: Compensation for risk is a multiple of the variance of the risk. Thus risk compensation cannot vary independently of interest rate volatility. I also describe a broader class of models. These aessentially affine‐ models retain the tractability of standard models, but allow compensation for interest rate risk to vary independently of interest rate volatility. This additional flexibility proves useful in forecasting future yields.