A Unified Approach to Volatility Estimation in the Presence of Both Rounding and Random Market Microstructure Noise

78 Pages Posted: 23 Dec 2015 Last revised: 24 Nov 2017

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

Zhiyuan Zhang

Shanghai University of Finance and Economics - School of Statistics and Management

Yichu Li

Investment Technology Group

Date Written: November 21, 2017

Abstract

Widely used volatility estimation methods mainly consider one of the following two simple microstructure noise models: random additive noise on log prices, or pure rounding errors. Apparently in real data these two types of noise co-exist. In this paper, we discover a common feature of these two types of noise and propose a unified volatility estimation approach in the presence of both rounding and random noise. Our data-driven method enjoys superior properties in terms of bias and convergence rate. We establish feasible central limit theorems and show their superior performance via simulations. Empirical studies show clear advantages of our method when applied to both stocks data and currency exchange data.

Keywords: High-Frequency Data, Rounding Error, Market Microstructure Noise, Integrated Volatility, Realized Volatility

JEL Classification: G12, C22, C14

Suggested Citation

Li, Yingying and Zhang, Zhiyuan and Li, Yichu, A Unified Approach to Volatility Estimation in the Presence of Both Rounding and Random Market Microstructure Noise (November 21, 2017). Available at SSRN: https://ssrn.com/abstract=2707177 or http://dx.doi.org/10.2139/ssrn.2707177

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

Zhiyuan Zhang (Contact Author)

Shanghai University of Finance and Economics - School of Statistics and Management ( email )

777 Guoding Road
Shanghai, Shanghai 200433
China

Yichu Li

Investment Technology Group ( email )

165 Broadway
9th Floor
New York, NY New York 10006
United States

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