High-frequency trading is a form of algorithmic trading that uses automated systems to execute a large volume of orders in fractions of a second to profit from minor price discrepancies.
Mechanics of high-frequency trading
This trading method relies on computers running specific quantitative models to analyze multiple financial markets simultaneously. The software identifies emerging market trends and executes buy and sell orders faster than human reaction times allow. High-frequency trading operations are active across global financial centers, interacting directly with equity and derivative markets.
The core component of this practice is the extreme speed of execution. Firms invest heavily in networking technology to reduce latency, which is the time it takes for a trade signal to travel from the firm to the exchange. Market participants often place their physical computer servers in the same data centers as the exchange servers. This practice is known as co-location. Physical proximity cuts data transmission times down to microseconds.
Strategies utilized in high-frequency trading include statistical arbitrage and automated market making. In market making, the algorithms provide liquidity by continuously offering to buy and sell securities. The systems profit from the spread between the bid and ask prices. The profit margins on individual trades are incredibly small. The systems must execute millions of trades daily to generate returns. The infrastructure costs required to maintain these speeds mean the practice is restricted to large institutional firms.
Example
Suppose you, as an Elephant, are monitoring international agricultural markets and notice a brief pricing anomaly. The price of raw peanut oil on a London commodity exchange is 1,200.00 GBP per metric ton, while on a Frankfurt exchange, the exact same asset is trading for 1,200.05 GBP. A high-frequency trading system detects this fractional price gap. In less than a millisecond, the algorithm buys a massive volume of peanut oil in London and immediately sells the same volume in Frankfurt. The system secures the five-pence price difference as profit long before human traders see the price update on their monitors. By repeating this action thousands of times a day across various assets, the algorithm accumulates profit from the tiny price differences.