This paper motivates and introduces a two-stage method of estimating di¤u- sion processes based on discretely sampled observations. In the …rst stage we make use of the feasible central limit theory for realized volatility, as developed in Jacod (1994) and Barndor¤-Nielsen and Shephard (2002), to provide a regression model for estimating the parameters in the di¤usion function. In the second stage the in-…ll 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 …nite sample performance of the proposed method is compared with that of the approximate maximum likelihood method of Aït-Sahalia
PHILLIPS, Peter C. B. and YU, Jun.
A Two-Stage Realized Volatility Approach to Estimation of Diffusion Processes with Discrete Data. (2006). 29-2006, 1-27. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/946
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