Spectral methods for identifying scalar diffusions

被引：65

作者：

Hansen, LP ^{[1
]}

Scheinkman, JA ^{[1
]}

Touzi, N ^{[1
]}

机构：

[1] Univ Chicago, Dept Econ, Chicago, IL 60637 USA

来源：

JOURNAL OF ECONOMETRICS | 1998年 / 86卷 / 01期

基金：

美国国家科学基金会;

关键词：

diffusion; identification; embeddability; continuous-time models in finance; spectral decomposition;

D O I：

10.1016/S0304-4076(97)00107-3

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper shows how to identify nonparametrically scalar stationary diffusions from discrete-time data. The local evolution of the diffusion is characterized by a drift and diffusion coefficient along with the specification of boundary behavior. We recover this local evolution from two objects that can be inferred directly from discrete-time data: the stationary density and a conveniently chosen eigenvalue-eigenfunction pair of the conditional expectation operator over a unit interval of time. This construction also lends itself to a spectral characterization of the over-identifying restrictions implied by a scalar diffusion model of a discrete-time Markov process. (C) 1998 Elsevier Science S.A. All rights reserved.

引用

页码：1 / 32

页数：32

共 28 条

[1] Nonparametric pricing of interest rate derivative securities [J].