Jumps at Ultra-High Frequency: Evidence From the Chinese Stock Market

32 Pages Posted: 20 Aug 2019

See all articles by Chuanhai Zhang

Chuanhai Zhang

Zhongnan University of Economics and Law - School of Finance

Zhi Liu

University of Macau

Qiang Liu

University of Macau

Date Written: August 17, 2019

Abstract

This paper proposes a new jump test for semi-martingale contained by microstructure noise based on the threshold pre-averaging bi-power estimation. Theoretically, we prove that such test has asymptotical size and power. Monte Carlo simulations show that the new test has better performance than Christensen et al(2014)'s test in noisy setting and we also consider adopting the false discovery rate (FDR) threshold technique to avoid spurious detections. In the empirical part, we investigate the contributions of jumps to total return variance from the Chinese stock market based on the tick-by-tick transaction data. The empirical results imply that the jump variation is an order of magnitude smaller than typical estimates found in the existing literature from different perspectives.

Keywords: jumps, market microstructure noise, spurious detections, threshold pre-averaged bi-power variation, ultra high frequency data

JEL Classification: C14, C58, G17

Suggested Citation

Zhang, Chuanhai and Liu, Zhi and Liu, Qiang, Jumps at Ultra-High Frequency: Evidence From the Chinese Stock Market (August 17, 2019). Available at SSRN: https://ssrn.com/abstract=3438616 or http://dx.doi.org/10.2139/ssrn.3438616

Chuanhai Zhang (Contact Author)

Zhongnan University of Economics and Law - School of Finance ( email )

WenQuan Building, 182# Nanhu Avenue
East Lake High-tech Development Zone
Wuhan, Hubei 430073
China

Zhi Liu

University of Macau ( email )

P.O. Box 3001
Macau

Qiang Liu

University of Macau ( email )

P.O. Box 3001
Macau

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
36
Abstract Views
349
PlumX Metrics