@article{a4e070a0366e4c0a9c67d8855558729e,
title = "Conditional estimation of diffusion processes",
abstract = "There are a number of circumstances in finance in which it is useful to estimate diffusion processes conditional on some event. In this paper, we develop the theoretical and numerical tools necessary to perform conditional estimation of diffusion processes within a generalized method of moments framework. We illustrate our method by estimating a univariate diffusion process for a standard time-series of interest rate data conditioned to remain between lower and upper boundaries. A test statistic fails to reject by a wide margin the linearity of the conditionally estimated drift coefficient.",
keywords = "Diffusion process, Estimation, Interest rates, Nonlinearity",
author = "Minqiang Li and Pearson, {Neil D.} and Poteshman, {Allen M.}",
note = "We thank Yacine A{\"ı}t-Sahalia for making available the interest rate data used in this paper, Reza Mahani for performing some of the preliminary computations, and William Goetzmann, Matthew Pritsker, Andrea Roncoroni, Bill Schwert (the editor), and participants in seminars at the University of Texas at Austin, Pennsylvania State University, the 2001 WFA meetings, MathWeek 2001, and the 2003 EFMA meetings for helpful comments. We also especially thank an anonymous referee for comments and suggestions that greatly improved the paper. Some of the computations were performed on computer workstations provided by the Intel Corporation under its Technology for Education 2000 program. Minqiang Li was supported by the Corzine Assistantship of the Office for Futures and Options Research of the University of Illinois at Urbana-Champaign.",
year = "2004",
month = oct,
doi = "10.1016/j.jfineco.2004.03.001",
language = "English (US)",
volume = "74",
pages = "31--66",
journal = "Journal of Financial Economics",
issn = "0304-405X",
publisher = "Elsevier B.V.",
number = "1",
}