Introduction
Executive summary
Humans’ constant emphasis on speed and efficiency is one of the key factors driving the rise of new trading strategies including high-frequency trading (HFT). However, it has some drawbacks, reflected in important changes in the financial market structure as well as disproportionate disadvantages for some users. This paper delves deep into the phenomenon, using two practical use cases – The Flash Crash of 2010 and the Knight Capital of 2012 – to illustrate HFT’s upsides and downsides. Through these cases, the paper underscores HFT’s complex nature, highlighting both its transformative role in the financial industry and risks that must be managed to prevent disruptions. A solution to continuous trading that eliminates latency arbitrage is also presented.
Key Takeaways
High-frequency trading (HFT) uses advanced computing and algorithms to execute trades in microseconds.
It is mainly adopted by investment banks, hedge funds, quantitative trading firms, and institutional investors.
HFT improves market liquidity, reduces costs, and boosts overall efficiency.
Risks include higher volatility, lack of fairness, transparency issues, and systemic vulnerabilities.
HFT evolved from manual trading in the 1960s to dominating over 50% of US equity turnover by 2010.
Co-location and advanced communication networks like microwave, laser, and fibre optics drive speed advantages.
Market abuse risks include spoofing and front-running, raising regulatory concerns.
The 2010 Flash Crash and 2012 Knight Capital glitch highlight HFT’s potential for massive disruptions.
Continuous trading markets are structurally flawed, favouring speed over fairness.
Frequent batch auctions are proposed as a solution to reduce latency arbitrage and enhance stability.
Conclusion
HFT has evolved from a niche strategy to a dominant force in financial markets, enabling firms to leverage advanced mathematics and computer science to execute thousands of trades in a fraction of a second. This fast trading strategy has transformed market dynamics by reducing transaction costs and increased liquidity. However, it has disadvantages including increased market volatility and systemic risk, in addition to the existing lag between continuous trading transactions and serial processing. A team helmed by Eric Budish proposed a solution for this discrepancy in an article in The Quarterly Journal of Economics, suggesting the aggregation of frequent batch auction trades into batches and execution at definite intervals (every few milliseconds or seconds) to pare the advantage of speed.
About the Author
Cristina is an associate of the Specialized Solutions business unit at Acuity and works on social media data analytics to understand consumer perception of specific products or brands. She joined Acuity in 2022. Prior to joining Acuity, Cristina did an internship focused on strategic internationalization and did her bachelor’s thesis on the quantitative impact of COVID-19 on female unemployment in Costa Rica. She holds a bachelor’s degree in Economics Leadership & Governance from the University of Navarra.
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