Are Algorithmic Trades Informed? An Empirical Analysis of Algorithmic Trading around Earnings Announcements

2013 ◽  
Author(s):  
Alex Frino ◽  
Tina Viljoen ◽  
George H. K. Wang ◽  
P. Joakim Westerholm ◽  
Hui Zheng
Keyword(s):  
Empirical Analysis ◽  
Earnings Announcements ◽  
Algorithmic Trading

scholarly journals An empirical analysis of algorithmic trading around earnings announcements

2017 ◽  
Vol 45 ◽  
pp. 34-51 ◽  
Author(s):  
Alex Frino ◽  
Tina Prodromou ◽  
George H.K. Wang ◽  
P. Joakim Westerholm ◽  
Hui Zheng
Keyword(s):  
Empirical Analysis ◽  
Earnings Announcements ◽  
Algorithmic Trading

Are Algorithmic Trades Informed? - An Empirical Analysis of Algorithmic Trading Around Earnings Announcements

2012 ◽  
Author(s):  
Alex Frino ◽  
Tina Viljoen ◽  
George H. K. Wang ◽  
P. Joakim Westerholm ◽  
Hui Zheng
Keyword(s):  
Empirical Analysis ◽  
Earnings Announcements ◽  
Algorithmic Trading

Dark Pool Trading and Information Acquisition

2021 ◽  
Author(s):  
Jonathan Brogaard ◽  
Jing Pan
Keyword(s):  
Information Acquisition ◽  
Stock Price ◽  
Earnings Announcements ◽  
Algorithmic Trading ◽  
Price Dynamics ◽  
Pilot Program ◽  
Informational Efficiency ◽  
Tick Size ◽  
Dark Pool ◽  
Dark Pools

Abstract Theory suggests that dark pools may facilitate or discourage information acquisition. We find that more dark pool trading leads to greater information acquisition. We measure information acquisition using stock price dynamics around earnings announcements. To overcome endogeneity concerns, we exploit a large exogenous decrease to dark pool trading that results from the implementation of the Security and Exchange Commission’s (SEC’s) Tick Size Pilot Program. The results cannot be explained by lit venue liquidity, algorithmic trading, or informational efficiency. A battery of additional tests, such as documenting a shift in SEC EDGAR searches, supports the information acquisition interpretation.

Sign in / Sign up

Export Citation Format

Share Document