Abstract
Nearly one-half of all trades in financial markets are executed by high-speed autonomous computer programs—a type of trading often called high-frequency trading (HFT). Although evidence suggests that HFT increases the efficiency of markets, it is unclear how or why it produces this outcome. Here we create a simple model to study the impact of HFT on investors who trade similar securities in different markets. We show that HFT can improve liquidity by allowing more transactions to take place without adversely affecting pricing or volatility. In the model, HFT synchronizes the prices of the securities, which allows buyers and sellers to find one another across markets and increases the likelihood of competitive orders being filled.
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Notes
- 1.
Several research firms provide estimates of HFT activity for subscribers; examples are the TABB Group, the Aite Group, and Celent. Publicly, this information is available in articles such as “The fast and the furious”, Feb. 25, 2012, The Economist and “Superfast traders feel the heat as bourses act”, Mar. 6, 2012, Financial Times.
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Acknowledgements
This chapter is a modified version of Benjamin Myers MPhys thesis originally entitled “Agent Based Simulations of High-Frequency Trading in Financial Markets.” This work was supported by the European Commission FP7 FET-Open Project FOC-II (no. 255987).
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Myers, B., Gerig, A. (2015). Simulating the Synchronizing Behavior of High-Frequency Trading in Multiple Markets. In: Bera, A., Ivliev, S., Lillo, F. (eds) Financial Econometrics and Empirical Market Microstructure. Springer, Cham. https://doi.org/10.1007/978-3-319-09946-0_13
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DOI: https://doi.org/10.1007/978-3-319-09946-0_13
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