High-Frequency Trading and Latency Arbitrage › High-Frequency Trading and Latency Arbitrage
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In the previous chapter, we explored market making and liquidity provision, where traders profit by capturing bid-ask spreads while managing inventory risk. High-frequency trading (HFT) takes these concepts to their logical extreme: holding periods are measured in milliseconds. Trading infrastructure is optimized for microsecond response times. Profit margins are so thin that success depends on executing millions of trades with near-perfect consistency.
High-frequency trading emerged in the early 2000s as electronic markets replaced human floor traders. What began as simple automation of existing strategies evolved into a sophisticated ecosystem where algorithms compete with each microsecond of latency advantage worth millions of dollars. Firms invest in microwave towers and hollow-core fiber optics to shave microseconds off transmission times between exchanges. This infrastructure investment reflects the extraordinary value of marginal speed advantages. By some estimates, HFT accounts for 50 to 60% of U.S. equity trading volume and fundamentally reshapes market microstructure.
The defining characteristic of HFT is not the strategies themselves. Many are conceptually similar to traditional arbitrage and market making. Instead, it's the timescales involved that define HFT. A statistical arbitrage fund might hold positions for days or weeks, while an HFT firm might hold for seconds or less. With traditional strategies, you might execute dozens of trades per day. An HFT algorithm executes thousands per second. This compression of time creates both opportunities and challenges that distinguish HFT from other quantitative strategies.
This chapter examines the core strategies employed by HFT firms, the technology infrastructure that makes sub-millisecond trading possible, and the economic and regulatory forces shaping this industry. You'll see how concepts from earlier chapters (no-arbitrage pricing from Part III, market making from the previous chapter, and statistical analysis from Part I) combine with specialized low-latency systems to create one of the most competitive domains in finance.