Nonparametric Estimation of the Short Rate Diffusion Process from a Panel of Yields
提出一种利用多期限收益率面板数据来估计短期利率扩散过程的非参数方法，能显著减少传统单序列估计的偏差，并提升效率，对债券和利率衍生品定价有重要经济含义。
Abstract In this paper, we propose a nonparametric estimator of the short rate diffusion process using observations of a panel of yields. The proposed estimator can greatly reduce the bias of the nonparametric estimator proposed in Stanton (1997) that uses a single time series of short rate observations. Simulations confirm that the new method significantly attenuates the spurious nonlinearity of the drift function as documented in Chapman and Pearson (2000). We apply the method to estimate the U.S. short rate process using a panel of six Treasury yields. With 42 years’ daily observations of the panel of yields, the proposed drift function estimator achieves the same efficiency as the Stanton (1997) estimator based on 145 years of daily short rate observations. Finally, we show that the proposed estimator also has significant economic implications on the pricing of bonds and interest rate derivatives.