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Machines vs. Machines: High Frequency Trading and Hard Information

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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.

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  • Yesol Huh, 2014. "Machines vs. Machines: High Frequency Trading and Hard Information," Finance and Economics Discussion Series 2014-33, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2014-33
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    1. Stenfors, Alexis & Susai, Masayuki, 2019. "Liquidity withdrawal in the FX spot market: A cross-country study using high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 59(C), pages 36-57.

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    Keywords

    High frequency trading; liquidity; market microstructure; information asymmetry;
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