Estimating the integrated volatility of high frequency realized prices is an important
issue in microstructure literature. Bandi and Russell (2006) derived the optimal-sampling
frequency, and Zhang et al. (2005) proposed a "two-scales estimator" to solve the problem.
In this study, we propose a new estimator based on a signal to noise ratio statistic with
convergence rate of Op (n^(−1/ 4) ). The method is applicable to both constant and stochastic
volatility models and modi¡Âes the Op (n^(−1/ 6) ) convergence rate of Zhang et al. (2005). The
proposed estimator is shown to be asymptotic e¡Ócient as the maximum likelihood estimate
for the constant volatility case. Furthermore, unbiased estimators of the two elements, the
variance of the microstructure noise and the fourth moment of the realized log returns, are
also proposed to facilitate the estimation of integrated volatility. The asymptotic prop-
erties and e®ectiveness of the proposed estimators are investigated both theoretically and
via simulation study.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0726107-094253 |
| Date | 26 July 2007 |
| Creators | Lin, Liang-ching |
| Contributors | Mong-Na Lo Huang, Mei-Hui Guo, Fu-Chuen Chang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0726107-094253 |
| Rights | withheld, Copyright information available at source archive |
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