A Dynamic Model for the Forward Curve
构建并估计了一个动态无套利的远期曲线模型，将远期曲线分解为无条件、期限特定和日期特定三个成分，结合了偏好栖息地、预期假说和仿射模型的特点，并用于利率衍生品定价和预测，在6个月以上预测中显著优于基准模型。
This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesis (ET) and affine yield curve models; it permits a class of low-parameter, multiple state variable dynamic models for the forward curve. We show how to construct alternative parametric examples of the three components from a sum of exponential functions, verify that the resulting forward curves satisfy the Heath-Jarrow-Morton (HJM) conditions, and derive the risk-neutral dynamics for the purpose of pricing interest rate derivatives. We select a model from alternative affine examples that are fitted to the Fama-Bliss Treasury data over an initial training period and use it to generate out-of-sample forecasts for forward rates and yields. For forecast horizons of 6 months or longer, the forecasts of this model significantly outperform those from common benchmark models. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies., Oxford University Press.