Also known as “black box trading,” “automated trading,” “robo trading,” or “algo trading,” high frequency trading algorithms employ sophisticated computer programs to execute securities trades. Trade order aspects such as maximum or minimum price, quantity, and timing are determined by computer analysis. Subsequent trade execution may also be accomplished absent any human involvement whatsoever.
History of HFT
Automated trading finds its financial genesis in the early 1970s. During that era, the New York Stock Exchange introduced its designated order turnaround (“DOT”) system. DOT electronically routed trade orders to the appropriate destination for manual execution. An opening automated reporting system (“OARS”) followed closely behind to assist brokers in identifying optimal clearing opening prices.
Full automation came into fruition in the late 1980s and early 1990s. US exchanges’ implementation of decimalization that changed minimum ticker price increments from 1/16th of $1 USD to 1/100th of $1 USD probably played a major role in the development of high frequency trading algorithms. Much smaller price fluctuations could be identified and exploited, thus stimulating activity and liquidity within securities markets.
HFT algorithms may be incorporated into any substantive investment strategy, including technical, arbitrate, or purely speculative approaches. Specific trades that fall within pre-set criteria may be manually executed at any stage, or completely automated. High frequency trading algorithms are commonly utilized by institutional investors such as pension or mutual funds and investor-driven institutional traders.
In the latter instance, large lots of stocks or may be subdivided into smaller sections for market impact temperance and risk reduction. Sufficient liquidity is essential for effective functioning in the securities arena. The automated nature of algorithmic trading facilitates this vital marketplace condition by large-scale, extremely rapid cash infusions that occur very frequently.
According to Aite Group, a financial industry research and consulting firm, one-third of all stock trades conducted on US and EU markets were algorithmic-driven in 2006. A mere 3 years later, HFT firms accounted for 73 percent of all US equity trading. US and European commodities exchanges generally have relatively high percentages of algorithmic trades.
Algorithmic HFT trading has been the source of much debate and public controversy of late. The US Securities and Exchange Commission (“SEC”) condemned HFT in the wake of the “Flash Crash” of May 6, 2010. On this momentous historical occasion in high finance, the Dow Jones Industrial Average sustained its greatest plunge in history. The carnage equaled trillions of US Dollars. Although prices recovered within seconds, the phenomenon gave many market observers and participants much pause.
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