TAN-DISSERTATION-2020.pdf (564.62 kB)
Download fileHigh Frequency Trading Volatility, Market Microstructure Noise and Institutional Investors
thesis
posted on 2020-12-01, 00:00 authored by Yuting TanAs stocks being traded more intensely daily, many recent studies show that the efficiency and accuracy of some measures developed from low frequency data may not be well guaranteed. It is worth investigating the relationship between institutional investor's behavior and stock return volatility in this new circumstance. We estimate stock return volatility with the two-scales realized volatility (TSRV) estimator which corrects the effect from market microstructure noise on stock prices. Using all transactions of S\&P 500 constituent stocks over the most recent 10 years, we find a positive association between the levels of institutional ownership and daily stock return volatility. This association is not constant over time. Institutional investors are more conservative while the market is more volatile, and they become more aggressive when market calms down. We also analyze quarterly changes in stock return volatility and institutional ownership ratio, and we find evidence that past increase in institutional ownership changes will positively impact the changes in volatility for the future, and past increases in volatility changes will decrease the institutional ownership in the future. But there is no causality relationship between institutional ownership and market microstructure noise. Most institutional investors act similarly except banks. We also find evidence for institutional herding and that stocks with higher institutional ownership ratios attract more high turnover traders, which could be the possible channels through which institutional investors affect stock return volatility.
History
Advisor
Zhang, LanChair
Zhang, LanDepartment
Business AdministrationDegree Grantor
University of Illinois at ChicagoDegree Level
- Doctoral
Degree name
PhD, Doctor of PhilosophyCommittee Member
Bassett, Gilbert W Chen, Hsiu-Lang Sclove, Stanley L Yang, JieSubmitted date
December 2020Thesis type
application/pdfLanguage
- en