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Machines vs. Machines: High Frequency Trading and Hard Information

Yesol Huh
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Yesol Huh:

No 2014-33, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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.

Keywords: High frequency trading; liquidity; market microstructure; information asymmetry (search for similar items in EconPapers)
Pages: 57 pages
Date: 2014-03-19
New Economics Papers: this item is included in nep-cta and nep-mst
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Citations: View citations in EconPapers (1)

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