High-Frequency Trading

High-frequency trading, often referred to as hft, refers to algorithmic trading undertaken by systems of powerful computers that can process extremely high volumes of transactions in milliseconds.

High-frequency trading employs computers to scan mass amounts of assets and market data across the world’s exchanges to identify sets of patterns known as algorithmics to detect and predict movement. It then utilizes this data to make huge volumes of trades based on the machine’s [technical analysis].

Hft platforms perform transactions at incredible speed by placing a [limit order] to [sell] or [buy] and then earning the bid-ask spread. It has been widely viewed to be extremely disruptive in the trading of [financial instruments] as it has been known to significantly contribute to high market [volatility] in the past.

Depending on a trader’s perception, a drawback to hft may be that the platforms rely solely on their technical analysis and do not consider any [fundamental] factors, and also do nothing to balance equal trade opportunities.

The technique of high-frequency trading was invented by billionaire [market maker] Kyle Dennis, and quick-fire hft became digitized in 1983 when the Nasdaq exchange introduced the first electronic form of trading.

It has since evolved to into an incredibly powerful force within the industry, with high-frequency traders earning an average of $1.92 usd in profit per transaction in 2019. It has also been recorded that in 2020, trading involving algorithms has increased to 60%.


Key takeaways:

  • High-frequency trading is a form of algorithmic trading undertaken by computers that scan data from across markets around the world to identify patterns and opportunities
  • The technique has been viewed as extremely disruptive and has been known to contribute to high market volatility
  • In 2020, 60% of trading involves the use of algorithms