A Two-Stage Realized Volatility Approach to Estimation of Diffusion Processes with Discrete Data
This paper motivates and introduces a two-stage method of 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 developed in [Jacod, J., 1994] and [Barndorff-Nielsen, O., Shephard, N.,...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2006
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| Online Access: | https://ink.library.smu.edu.sg/soe_research/946 https://ink.library.smu.edu.sg/context/soe_research/article/1945/viewcontent/PhillipsYu.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | This paper motivates and introduces a two-stage method of 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 developed in [Jacod, J., 1994] and [Barndorff-Nielsen, O., Shephard, N., 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 [Aït-Sahalia, Y., 2002]. |
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