Faster Convergence to the Estimation of Quadratic Variation with Microstructure Noise

Yun-Cheng Tsai and Yuh-Dauh Lyuu

Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 13, 2827-2841

Abstract: The continuous quadratic variation of asset return plays a critical role for high-frequency trading. However, the microstructure noise could bias the estimation of the continuous quadratic variation. Zhang et al. (2005) proposed a batch estimator for the continuous quadratic variation of high-frequency data in the presence of microstructure noise. It gives the estimates after all the data arrive. This article proposes a recursive version of their estimator that outputs variation estimates as the data arrive. Our estimator gives excellent estimates well before all the data arrive. Both real high-frequency futures data and simulation data confirm the performance of the recursive estimator.

Date: 2015
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DOI: 10.1080/03610926.2013.847103

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