On autocorrelation estimation of high frequency squared returns
碩士 === 國立中山大學 === 應用數學系研究所 === 98 === 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 ti...
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| Format: | Others |
| Language: | en_US |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/51598320107837477106 |
| Summary: | 碩士 === 國立中山大學 === 應用數學系研究所 === 98 === 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.
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