Title

A Two-Stage Realized Volatility Approach to the Estimation for Diffusion Processes from Discrete Observations

Publication Type

Conference Paper

Publication Date

6-2005

Abstract

This paper motivates and introduces a two-stage method for estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as recently developed in Barndorff-Nielsen and Shephard (2002), to provide a regression model for estimating the parameters in the diffusion function. In the second stage the in-fill likelihood function is derived by means of the Girsanov theorem and then used to estimate the parameters in the drift function. Consistency and asymptotic distribution theory for these estimates are established in various contexts. The finite sample performance of the proposed method is compared with that of the approximate maximum likelihood method of Ait-Sahalia (2002).

Keywords

Maximum likelihood, Girsnov theorem, Discrete sampling, Continuous record, Realized volatility

Discipline

Econometrics

Research Areas

Econometrics

Publication

Inaugural Symposium on Econometric Theory and Applications

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://econpapers.repec.org/paper/cwlcwldpp/1523.htm

Comments

Cowles Foundation Discussion Papers No 1523

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