Earnings announcements and the components of the bid-ask spread: Evidence from the London Stock Exchange

被引:5
|
作者
Gregoriou, Andros [1 ]
机构
[1] Univ Bournemouth, Bournemouth Business Sch, Bournemouth, Dorset, England
关键词
Bid-ask spread; Order-processing costs; Inventory costs; Asymmetric information costs; Stock exchanges; United Kingdom;
D O I
10.1108/01443581311283646
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose - The purpose of this paper is to investigate the impact of the components of the bid-ask spread around earnings announcements on the London Stock Exchange using intraday data obtained from the ICV Marketeye database. The paper finds that the information asymmetry cost component significantly increases around the earnings announcements, while the inventory holding and order processing cost components significantly decrease around the same period. Specifically, the economic magnitude of the increase in the asymmetric cost component implies that earnings announcements significantly increase the total bid-ask spread, even when they result in decreased inventory holding and order processing costs. Design/methodology/approach - Liquidity in financial markets around earnings announcements in the London Stock Exchange obtained by bid-ask spread decompositions. Findings - This paper investigates the impact of earnings announcements on the components of the bid-ask spread on the London Stock Exchange using intraday data. The fundamental conclusion from the empirical findings is that the bid-ask spread increases once the earnings have been announced, because the market makers' increased concerns about asymmetric information is more pronounced, than the lower inventory and order processing costs due to the higher levels of trading volume. This empirical finding also holds when the earnings announcements are partitioned into positive and negative surprises. Originality/value - This is the first paper to decompose the bid-ask spread around earnings announcements on the London Stock Exchange. The paper uses a unique intraday dataset.
引用
收藏
页码:112 / 126
页数:15
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