Do Domestic Institutional Trades Exacerbate Information Asymmetry? Evidence from the Korean Stock Market
Chune Young Chung (),
Yunjae Lee () and
Doojin Ryu ()
Additional contact information
Chune Young Chung: Chung-Ang University
Yunjae Lee: Chung-Ang University
Doojin Ryu: Sungkyunkwan University
Asia-Pacific Financial Markets, 2017, vol. 24, issue 4, 309-322
Abstract We analyze a trading dataset from the Korean stock market, a representative and leading emerging equity market, to study the impact of domestic institutional trades on information asymmetry. Using the bid–ask spread as a proxy for the adverse selection cost imposed by information asymmetry, we empirically examine the relationship between domestic institutional trades and their corresponding bid–ask spreads. We find that bid–ask spreads tend to increase when the trading volume of domestic institutional investors is high, suggesting that such investors tend to aggravate information asymmetry as informed traders in the Korean stock market.
Keywords: Bid–ask spread; Domestic institution; Information asymmetry; Institutional trade; Korean stock market (search for similar items in EconPapers)
JEL-codes: G14 G15 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s10690-017-9235-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:kap:apfinm:v:24:y:2017:i:4:d:10.1007_s10690-017-9235-0
Ordering information: This journal article can be ordered from
Access Statistics for this article
Asia-Pacific Financial Markets is currently edited by Jiro Akahori
More articles in Asia-Pacific Financial Markets from Springer, Japanese Association of Financial Economics and Engineering
Series data maintained by Sonal Shukla ().