Algorithmic trading

For trading using algorithms, see automated trading system.

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Organisations
Terms

Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume.[1] This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders.[2][3] A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.[4]

It is widely used by investment banks, pension funds, mutual funds, and hedge funds that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to. However, it is also available to private traders using simple retail tools.

The term algorithmic trading is often used synonymously with automated trading system. These encompass a variety of trading strategies, some of which are based on formulas and results from mathematical finance, and often rely on specialized software.[5][6]

Examples of strategies used in algorithmic trading include systematic trading, market making, inter-market spreading, arbitrage, or pure speculation, such as trend following. Many fall into the category of high-frequency trading (HFT), which is characterized by high turnover and high order-to-trade ratios.[7] HFT strategies utilize computers that make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. As a result, in February 2012, the Commodity Futures Trading Commission (CFTC) formed a special working group that included academics and industry experts to advise the CFTC on how best to define HFT.[8][9] Algorithmic trading and HFT have resulted in a dramatic change of the market microstructure and in the complexity and uncertainty of the market macrodynamic,[10] particularly in the way liquidity is provided.[11]

  1. ^ The New Investor, UCLA Law Review, available at: https://ssrn.com/abstract=2227498
  2. ^ "Business and finance". The Economist. Archived from the original on June 22, 2008. Retrieved April 18, 2007.
  3. ^ "| Aite Group". www.aitegroup.com.
  4. ^ Kissell, Robert (September 4, 2020), Algorithmic Trading Methods, Elsevier Science, ISBN 978-0-12-815630-8
  5. ^ The New Financial Industry, Alabama Law Review, available at: https://ssrn.com/abstract=2417988
  6. ^ Lemke and Lins, "Soft Dollars and Other Trading Activities," § 2:30 (Thomson West, 2015–2016 ed.).
  7. ^ Lemke and Lins, "Soft Dollars and Other Trading Activities," § 2:31 (Thomson West, 2015–2016 ed.).
  8. ^ Silla Brush (June 20, 2012). "CFTC Panel Urges Broad Definition of High-Frequency Trading". Bloomberg.com.
  9. ^ Futures Trading Commission Votes to Establish a New Subcommittee of the Technology Advisory Committee (TAC) to focus on High Frequency Trading, February 9, 2012, Commodity Futures Trading Commission
  10. ^ Cite error: The named reference HilbertDarmon2 was invoked but never defined (see the help page).
  11. ^ O'Hara, Maureen; Lopez De Prado, Marcos; Easley, David (2011), "Easley, D., M. López de Prado, M. O'Hara: The Microstructure of the 'Flash Crash': Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading", The Journal of Portfolio Management, Vol. 37, No. 2, pp. 118–128, Winter, SSRN 1695041