STATISTICS COLLOQUIUM
Kung-Sik Chan
Professor
Statistics and Actuarial Science
University of Iowa
Inference for Threshold Diffusions
ABSTRACT
The threshold diffusion model assumes the underlying diffusion process to have a piece-wise linear drift term and a piece-wise smooth diffusion term, which is useful for analyzing nonlinear continuous-time processes. In practice, the functional form of the diffusion term is often unknown. We develop a quasi-likelihood approach for testing and estimating a threshold diffusion model, by employing a constant working diffusion term, which amounts to a least squares approach. Large-sample properties of the proposed methods are derived under mild regularity conditions. Unlike the discrete-time case, the threshold estimate admits a closed-form asymptotic distribution. We apply the threshold model to examine the nonlinearity in the term structure of a long time series of US interest rates.
DATE: Wednesday, October 12, 2016
TIME: 4:00 pm
PLACE: Philip E. Austin Bldg., Rm. 105
Coffee will be served at 3:30 pm in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu