What is Algorithmic Trading?
Last updated
Last updated
Algorithmic trading uses complex formulas, mathematical models, and human oversight to make decisions to buy or sell financial securities on an exchange. Algorithmic traders often use high-frequency trading technology, enabling a firm to make tens of thousands of trades per second. Algorithmic trading can be used in various situations, including order execution, arbitrage, and trend trading strategies.
The use of algorithms in trading increased after computerised trading systems were introduced in American financial markets during the 1970s. In 1976, the New York Stock Exchange introduced the Designated Order Turnaround (DOT) system for routing orders from traders to specialists on the exchange floor.1 In the following decades, exchanges enhanced their abilities to accept electronic trading, and by 2009, upwards of 60 per cent of all trades in the U.S. were executed by computers.2
Author Michael Lewis brought high-frequency, algorithmic trading to the public’s attention when he published the best-selling book Flash Boys, which documented the lives of Wall Street traders and entrepreneurs who helped build the companies that came to define the structure of electronic trading in America. His book argued that these companies were engaged in an arms race to build ever faster computers, which could communicate with exchanges ever more quickly, to gain an advantage over competitors with speed, using order types that benefited them to the detriment of average investors.
Algorithmic trading uses process- and rules-based algorithms to employ strategies for executing trades. It has grown significantly in popularity since the early 1980s and is used by institutional investors and large trading firms for various purposes.
