In financial markets, high-frequency trading (HFT) is a type of algorithmic trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools.[1] While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons.[2] HFT can be viewed as a primary form of algorithmic trading in finance.[3][4][5][6][7] Specifically, it is the use of sophisticated technological tools and computer algorithms to rapidly trade securities.[8][9][10] HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.[11] Aldridge and Krawciw, 2017 [12] estimate that in 2016 HFT on average initiated 10-40% of trading volume in equities, and 10-15% of volume in foreign exchange and commodities. Intraday, however, proportion of HFT may vary from 0% to 100% of short-term trading volume. Previous estimates reporting that HFT accounted for 60-73% of all US equity trading volume, with that number falling to approximately 50% in 2012 were highly inaccurate speculative guesses.[13][14] 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.[9] HFT firms do not consume significant amounts of capital, accumulate positions or hold their portfolios overnight.[15] 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.[16] High-frequency traders typically compete against other HFTs, rather than long-term investors.[15][17][18] HFT firms make up the low margins with incredibly high volumes of trades, frequently numbering in the millions.