Statistics and Its Interface

Volume 13 (2020)

Number 1

Leverage Effect in High-Frequency Data with Market Microstructure

Pages: 91 – 101



Huiling Yuan (School of Data Science, City University of Hong Kong)

Yan Mu (School of Economics, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China)

Yong Zhou (Key Laboratory of Advanced Theory and Application in Statistics and Data Science, Academy of Mathematics and Systems Science, CAS, East China Normal University, Shanghai, China)


The leverage effect is an important explanation for volatility asymmetry, which has got extensively attention in the recent years. In this paper, we introduces a new estimator of leverage effect. The key feature of the proposed estimator is explored in the setting when the microstructure noise model is the parameter function of trading information. The proposed estimator shows good statistical performances via theorems and simulations study. Specially, the estimator has a convergence rate $n^{1/4}$. The QQ-Plots, Histogram plots and quartiles perform sufficient asymptotical normality compared with the exist estimated methods. An empirical study is carried out to demonstrate that the proposed estimator could present the efficient application value, and confirm that the leverage effect plays an important role in forecasting volatility.


Quadratic Covariation, Integral volatility, Microstructure noise, Consistency.

2010 Mathematics Subject Classification

Primary 62M10, 62M20. Secondary 62G05, 62G20.

Zhou’s work was supported by the State Key Program of National Natural Science Foundation of China (71331006), the State Key Program in the Major Research Plan of National Natural Science Foundation of China (91546202).

Received 25 September 2018

Accepted 23 August 2019

Published 7 November 2019