Abstract
In today's markets where high frequency traders (HFTs) act as both liquidity providers and takers, I argue that information asymmetry induced by liquidity-taking HFTs' use of machine-readable information is important. This particular type of information asymmetry arises because some machines may access the information before other machines or because of randomness in relative speed. Applying a novel statistical approach to measure HFT activity through limit order book data and using a natural experiment of index inclusion, I show that liquidity-providing HFTs supply less liquidity to stocks that suffer more from this information asymmetry problem. Moreover, when markets are volatile, this information asymmetry problem becomes more severe, and HFTs supply less liquidity. I discuss implications for market-making activity in times of market stress and for HFT regulations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
