This review was commissioned as part of the UK Government’s Foresight Project, The Future of Computer Trading in Financial Markets. The views expressed do not represent the policy of any Government or organisation.

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Terrence Hendershott

Executive Summary

This review examines high frequency trading (HFT) and price efficiency. Technological advances typically replace the most repetitive human activity with automation. For short-run speculation such as HFT it involves processing as much data as quickly as possible to find predictability in future price changes and then to capitalize quickly by submitting orders. As technology improves the trend of substituting technology for labor will continue in the investment process. This review focuses on how greater investment in computing and communications technologies impact HFT and price efficiency.

HFT strategies are discussed along with their differing impacts on price efficiency. The relatively sparse empirical literature on HFT and price efficiency is examined together with its conclusion that HFT appears to improve price efficiency. In the context of the future impact of HFT on price efficiency four broad questions and their impact are discussed along with the italicized conclusions below:

1) Is HFT competitive?
Standardizing market access and data and restricting the benefits of very small increases in speed enhances competition.

2) Will HFT-like services be offered to low-frequency investors?
Algorithms for non-HFT already offer tools incorporating HFT approaches; this trend will continue, especially if HFT is competitive.

3) Are automated markets with automated trading less stable, e.g., prices occasionally become quite inefficient, than markets with more human intervention?
While no systematic evidence that HFT reduced stability, the interactions between algorithms may cause instability different from interactions between human.

4) If HFT begins to reduce price efficiency will market structures evolve to limit HFT?
Rules requiring trading in markets with HFT should be re-examined.

The review concludes with the importance of expanding the availability of data on HFT across markets and asset classes. Well structured policy experiments and data availability will enable deeper understanding of HFT and its roles in financial market performance.