High-frequency trading (HFT) is a type of algorithmic trading in finance characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools.[1][2][3] While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons in trading securities.[4][5][6][7] HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.[8]
In 2016, HFT on average initiated 10–40% of trading volume in equities, and 10–15% of volume in foreign exchange and commodities.[9] High-frequency traders move in and out of short-term positions at high volumes and high speeds aiming to capture sometimes a fraction of a cent in profit on every trade.[6] HFT firms do not consume significant amounts of capital, accumulate positions or hold their portfolios overnight.[10] As a result, HFT has a potential Sharpe ratio (a measure of reward to risk) tens of times higher than traditional buy-and-hold strategies.[11] High-frequency traders typically compete against other HFTs, rather than long-term investors.[10][12][13] HFT firms make up the low margins with incredibly high volumes of trades, frequently numbering in the millions.
A substantial body of research argues that HFT and electronic trading pose new types of challenges to the financial system.[5][14] Algorithmic and high-frequency traders were both found to have contributed to volatility in the Flash Crash of May 6, 2010, when high-frequency liquidity providers rapidly withdrew from the market.[5][13][14][15][16] Several European countries have proposed curtailing or banning HFT due to concerns about volatility.[17] Other complaints against HFT include the argument that some HFT firms scrape profits from investors when index funds rebalance their portfolios.[18][19][20]
^Aldridge, Irene (2013), High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems, 2nd edition, Wiley, ISBN978-1-118-34350-0
^Lin, Tom C. W. "The New Financial Industry" (March 30, 2014). 65 Alabama Law Review 567 (2014); Temple University Legal Studies Research Paper No. 2014-11; SSRN2417988.
^Aldridge, I., Krawciw, S., 2017. Real-Time Risk: What Investors Should Know About Fintech, High-Frequency Trading and Flash Crashes. Hoboken: Wiley. ISBN978-1-119-31896-5.
^Easley, David; Marcos Lopez de Prado; Maureen O'Hara (October 2010), "The Microstructure of the 'Flash Crash': Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading", Journal of Portfolio Management, SSRN1695041
^ abVuorenmaa, Tommi; Wang, Liang (October 2013), "An Agent-Based Model of the Flash Crash of May 6, 2010, with Policy Implications", VALO Research and University of Helsinki, SSRN2336772