Start Submission Become a Reviewer

Reading: Inference for Diffusion Processes using Combined Estimating Functions

Download

A- A+
dyslexia friendly

Articles

Inference for Diffusion Processes using Combined Estimating Functions

Authors:

A Thavaneswaran ,

University of Manitoba, CA
X close

You Liang,

University of Manitoba, IN
X close

N Ravishanker

University of Connecticut, IN
X close

Abstract

A class of martingale estimating functions provides a convenient framework for studying inference for nonlinear time series models. Further, when information about higher order conditional moments of the observed process is available, the estimation based on combined estimating functions becomes more informative. In this paper, a general framework is developed for estimating parameters of diffusion processes with discretely sampled data using combined estimating functions. The approach is used to study parameter estimation for diffusion models for asset pricing including the Black Scholes model, the Vasicek model, and the Cox-Ingersoll-Ross (CIR) model. Closed form expressions for the gain in information are also discussed in some detail.

DOI: http://dx.doi.org/10.4038/sljastats.v12i0.4972

Sri Lankan Journal of Applied Statistics Vol.12 2011 pp.145-160

DOI: http://doi.org/10.4038/sljastats.v12i0.4972
How to Cite: Thavaneswaran, A., Liang, Y. & Ravishanker, N., (2012). Inference for Diffusion Processes using Combined Estimating Functions. Sri Lankan Journal of Applied Statistics. 12, pp.145–160. DOI: http://doi.org/10.4038/sljastats.v12i0.4972
237
Views
285
Downloads
Published on 02 Dec 2012.
Peer Reviewed

Downloads

  • PDF (EN)

    comments powered by Disqus