Efficient Estimation of Integrated Volatility Incorporating Trading Information

48 Pages Posted: 1 Jan 2014 Last revised: 11 May 2016

Yingying Li

Hong Kong University of Science & Technology (HKUST), Dept of ISOM and Dept of Finance; Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management; Hong Kong University of Science & Technology (HKUST) - Department of Finance

Shangyu Xie

University of International Business and Economics (UIBE) - School of Banking and Finance

Xinghua Zheng

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management

Date Written: May 10, 2016

Abstract

We consider a setting where market microstructure noise is a parametric function of trading information, possibly with a remaining noise component. Assuming that the remaining noise is $O_p(1/\sqrt{n})$, allowing irregular times and jumps, we show that we can estimate the parameters at rate $n$, and propose a volatility estimator which enjoys $\sqrt{n}$ convergence rate. Simulation studies show that our method performs well even with model misspecification and rounding. Empirical studies demonstrate the practical relevance and advantages of our method. Furthermore, we find that a simple model can account for a high percentage of the total variation of the microstructure noise.

Keywords: High frequency data, integrated volatility, market microstructure noise, realized volatility, efficiency

JEL Classification: G12, C22, C14

Suggested Citation

Li, Yingying and Xie, Shangyu and Zheng, Xinghua, Efficient Estimation of Integrated Volatility Incorporating Trading Information (May 10, 2016). Available at SSRN: https://ssrn.com/abstract=2373489 or http://dx.doi.org/10.2139/ssrn.2373489

Yingying Li

Hong Kong University of Science & Technology (HKUST), Dept of ISOM and Dept of Finance ( email )

Clear Water Bay, Kowloon
Hong Kong

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

Hong Kong University of Science & Technology (HKUST) - Department of Finance ( email )

Clear Water Bay, Kowloon
Hong Kong

Shangyu Xie

University of International Business and Economics (UIBE) - School of Banking and Finance ( email )

No.10, Huixindong Street
Chaoyang District
Beijing, 100029
China

Xinghua Zheng (Contact Author)

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

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