RT Journal Article
SR Electronic
T1 Online Search Frequency, Information Asymmetry, and Market Liquidity
JF The Journal of Index Investing
FD Institutional Investor Journals
SP 71
OP 81
DO 10.3905/jii.2016.6.4.071
VO 6
IS 4
A1 Xing Lu
A1 Hunter M. Holzhauer
A1 Jun Wang
YR 2016
UL https://pm-research.com/content/6/4/71.abstract
AB The notion that information has a different value based on the time of its first availability is at the heart of being able to quantify the value of any stock market indicators. Compared to using investors’ trading data to predict liquidity and volatility in the stock market, the use of investors’ information-seeking behavior before the actual trading has an important advantage in time value. This article investigates the online search frequency of Google users to explore how traders’ response to information asymmetry would predict future market liquidity. The findings show that the Google Insight for Search (GIS) daily index is an effective measure of the level of information asymmetry and inversely predicts the future liquidity level. This predictive power is significant at the 1% level. More importantly, the GIS indicators remain strong and significant even after including traditional information asymmetry variables in all the regressions. Last but not least, we find that the GIS index can capture the change in investors’ attention and provide indications on future stock return at the 1% significance level.TOPICS: Big data/machine learning, in portfolio management, volatility measures