Abstract
We analyze high frequency trading (HFT) activity in equities during US Treasury permanent open market (POMO) purchases by the Federal Reserve. We construct a model to study HFT quote and trade behavior when private information is released and confirm it empirically. We estimate that HFT firms reduce their inside quote participation by up to 8% during POMO auctions. HFT firms trade more aggressively, and they supply less passive liquidity to non-HFT firms. Market impact also rises during Treasury POMO. Aggressive HFT trading becomes more consistently profitable, and HFT firms earn a higher return per share. We also estimate that HFT firms earn profits of over $105 million during US Treasury POMO events.
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- 1.
See, e.g., Christopher Matthews, “High Frequency Trading: Wall Street’s Doomsday Machine?”, Time Magazine, August 8, 2012.
- 2.
SEC Chairman Mary Jo White, in testimony before the Senate Banking Committee on March 13, 2013, noted “..high frequency trading, complex trading algorithms, dark pools, and intricate new order types raise many questions and concerns.”
- 3.
The history and motivation of the Federal Reserve program is analyzed in Gagnon et al. (2011).
- 4.
See, e.g., David Tepper, manager of the Apaloosa Hedge Fund, in the Financial Times of October 8, 2010.
- 5.
There are three purchases of Treasury Inflation Protected securities (TIPS) totaling $4.5 billion, but we did not include them in our analysis.
- 6.
This effect is present from 1-min up to 30-min after the auction. The peak impact on equity returns is at the 15-min horizon.
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Acknowledgements
We would like to thank Nasdaq OMX for providing the high frequency dataset, an anonymous referee, Michael Fleming and seminar participants at National Chiao Tung, Nankai, the Modeling High Frequency Data in Finance Conference, and the Second International Symposium in Computational Economics and Finance.
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Gao, C., Mizrach, B. (2018). High Frequency Trading in the Equity Markets During US Treasury POMO. In: Jawadi, F. (eds) Uncertainty, Expectations and Asset Price Dynamics. Dynamic Modeling and Econometrics in Economics and Finance, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-98714-9_4
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