Donald Mackenzie, a University of Edinburgh professor and author of *Trading at the Speed of Light*, dissects how financial markets evolved from manual trading floors to algorithms racing across continents. The drive for speed intensified as firms realized even microseconds could mean millions in profits. Proximity trading—placing systems near exchanges to cut wire lengths—became a billion-dollar arms race, with companies like Equinix and Zayo building fiber-optic networks to shave milliseconds off trade execution times.

The 1990s saw the rise of electronic trading, but the 2000s brought high-frequency trading (HFT), where algorithms process thousands of transactions per second. This shift forced exchanges like NYSE and NASDAQ to upgrade infrastructure, creating a feedback loop where speed became the primary competitive edge. Latency arbitrage, exploiting price differences across markets, now dominates trading strategies, with firms like Jump Trading and Akuna Capital leveraging AI to dominate.

Regulators face challenges balancing innovation and fairness. The 2010 Flash Crash highlighted risks when algorithms overwhelm markets, yet proposed rules like the SEC’s 2022 microwave link disclosure mandate remain contentious. Critics argue speed prioritization widens wealth gaps, as only capital-rich firms access cutting-edge tech. Meanwhile, blockchain and quantum computing threaten to disrupt existing models, though adoption remains speculative.

Mackenzie warns that the arms race risks destabilizing markets. "When trading becomes a physics problem," he argues, "the human element fades, leaving systems vulnerable to glitches." For investors, the takeaway is clear: understanding algorithmic dominance is critical to navigating modern finance. The next frontier? Whether regulators can curb the speed obsession before systemic risks escalate.