In this paper, we investigate the problem of estimating the autocorrelation of squared returns modeled by diffusion processes with data observed at non-equi-spaced discrete times. Throughout, we will suppose that the stock price processes evolve in continuous time as the Heston-type stochastic volatility processes and the transactions arrive randomly according to a Poisson process. In order to estimate the autocorrelation at a fixed delay, the original non-equispaced data will be synchronized. When imputing missing data, we adopt the previous-tick
interpolation scheme. Asymptotic property of the sample autocorrelation of squared returns
based on the previous-tick synchronized data will be investigated. Simulation studies are performed
and applications to real examples are illustrated.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0114110-133726 |
| Date | 14 January 2010 |
| Creators | Pao, Hsiao-Yung |
| Contributors | Shih-Feng Huang, Mong-Na Lo Huang, Mei-Hui Guo, May-Ru Chen, 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-0114110-133726 |
| Rights | unrestricted, Copyright information available at source archive |
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