Estimation of continuous-time interest rate models: a nonparametric approach

This paper presents a general, nonlinear model for term structure interest rate. The approach is the same of Stanton (1997) but it has been extended to a multifactor model. The novel aspect is that rather than choosing the functional specification of the model, the process is generated from the data using approximation methods for multifactor continuous-time Markov processes. In applying this technique to the short and long end of the term structure for a general two-factor diffusion process for interest rates is possible to find some interesting nonlinearity in the interest rate data that are not considered in almost all parametric specifications of term structure interest rate model of the financial literature.continuous-time models, nonparametric estimation, multi-factor interest rate model

Nonparametric estimation of diffusion process: a closer look

A Monte Carlo simulation is performed to investigate the finite sample properties of a nonparametric estimator, based on discretely sampled observations of continuous-time Ito diffusion process. Chapman and Pearson (2000) studies finite-sample properties of the nonparametric estimator of Aýt-Sahalia (1996) and Stanton (1997) and they find that nonlinearity of the short rate drift is not a robust stylized fact but it’s an artifacts of the estimation procedure. This paper examine the finite sample properties of a different nonparametric estimator within the Stanton (1997)’s framework.ewp-mac/050417