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On autocorrelation estimation of high frequency squared returnsPao, Hsiao-Yung 14 January 2010 (has links)
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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