Subscribing to Transparency

He, Yinghua, Nielsson, Ulf, Guo, Hong and Yang, Jiong (2012) Subscribing to Transparency. TSE Working Paper, n. 12-351

WarningThere is a more recent version of this item available.
[img]
Preview
Text
Download (1MB) | Preview
Official URL: http://tse-fr.eu/pub/26441

Abstract

The paper empirically explores how more trade transparency affects market liquidity. The analysis takes advantage of a unique setting in which the Shanghai Stock Exchange offered more trade transparency to market participants subscribing to a new software package. First, the results show that the additional data disclosure increased trading activity, but also increased transactions costs through wider bid-ask spreads. Thus, in contrast to popular policy belief, the paper finds that more transparency need not improve market liquidity. Second, the paper finds a particularly strong immediate liquidity impact accompanied by altered trading behavior, which suggests a significant impact on institutional traders subscribing relatively early. Lastly, since the effective level of market transparency is bound to depend on how many traders are subscribing to the data, the study can empirically establish the functional form between market-wide transparency and liquidity. The relationship is non-monotonic, which can explain the lack of consensus in the existing literature where each empirical study is naturally confined to specific parts of the transparency domain.

Item Type: Monograph (Working Paper)
Date: July 2012
Uncontrolled Keywords: transparency, liquidity, market microstructure, market design
JEL codes: G14 - Information and Market Efficiency; Event Studies
G28 - Government Policy and Regulation
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 09 Jul 2014 17:30
Last Modified: 07 Mar 2018 13:22
OAI ID: oai:tse-fr.eu:26441
URI: http://publications.ut-capitole.fr/id/eprint/15425

Available Versions of this Item

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year