Nonparametric Density Estimation and Tests of Continuous Time Interest Rate Models
A number of recent papers have used nonparametric density estimation or nonparametric regression to study the instantaneous spot interest rate, and to test term structure models. However, little is known about the performance of these methods when applied to persistent time-series, such as U.S. interest rates. This paper uses the Vasicek [1977] model to study the performance of kernel density estimates of the ergodic distribution of the instantaneous spot rate. The model's tractability allows me to analyze the MISE of the kernel estimate as a function of persistence, variance of the ergodic distribution, span of the data, sampling frequency, and kernel bandwidth. Our principle result is that persistence has an important impact on optimal bandwidth selection and on finite sample performance. We also find that sampling the data more frequently has little effect on estimator quality. We also examine one of Ait-Sahalia's [1996a] new nonparametric tests of parametric continuous-time Markov ...