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Liquidity skewness in the London Stock Exchange

Hsieh, Tsung Han; Li, Youwei; McKillop, Donal G.; Wu, Yuliang

Authors

Tsung Han Hsieh

Donal G. McKillop

Yuliang Wu



Abstract

We study liquidity on the London Stock Exchange. We find that the average bid-ask spread declines, but that the skewness of the spread increases. These results are robust to firm size, trading volume and price level. Our findings hold when the bid-ask spread is estimated utilising high frequency data. We find that the bid-ask spread prior to earnings announcements dates is significantly higher than that of post earnings announcements, suggesting that asymmetric information has driven the increase in liquidity skewness. We also find that the effect of earnings announcements is more pronounced in the 2007 global financial crisis, consistent with the notion that extreme market downturns amplify asymmetric information. Our overall evidence also implies that increased competition and transparent trading environments limit market makers' abilities to cross-subsidize bid-ask spreads between periods of high and low levels of asymmetric information.

Journal Article Type Article
Publication Date 2018-03
Journal International Review of Financial Analysis
Print ISSN 1057-5219
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 56
Pages 12-18
APA6 Citation Hsieh, T. H., Li, Y., McKillop, D. G., & Wu, Y. (2018). Liquidity skewness in the London Stock Exchange. International review of financial analysis, 56, 12-18. https://doi.org/10.1016/j.irfa.2017.12.006
DOI https://doi.org/10.1016/j.irfa.2017.12.006
Keywords Asymmetric information; Bid-ask spread; Liquidity; London Stock Exchange; Skewness
Publisher URL https://www.sciencedirect.com/science/article/pii/S1057521917301928?via%3Dihub
Additional Information This article is maintained by: Elsevier; Article Title: Liquidity skewness in the London Stock Exchange; Journal Title: International Review of Financial Analysis; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.irfa.2017.12.006; Content Type: article; Copyright: © 2017 Elsevier Inc. All rights reserved.

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Copyright Statement
© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/





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