High Frequency Trading

High-frequency trading ( HFT ) is a type of algorithmic financial trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools. While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons. HFT can be viewed as a primary form of algorithmic trading in finance. Specifically, it is the use of sophisticated technological tools and computer algorithms to rapidly trade securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second. In 2017, Aldridge and Krawciw estimated 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

High-frequency trading has taken place at least since the 1930s, mostly in the form of specialists and pit traders buying and selling positions at the physical location of the exchange, with high-speed telegraph service to other exchanges. The rapid-fire computer-based HFT developed gradually since 1983 after NASDAQ introduced a purely electronic form of trading. At the turn of the 21st century, HFT trades had an execution time of several seconds, whereas by 2010 this had decreased to milli- and even microseconds. Until recently, high-frequency trading was a little-known topic outside the financial sector, with an article published by the New York Times in July 2009 being one of the first to bring the subject to the public's attention. On September 2, 2013, Italy became the world's first country to introduce a tax specifically targeted at HFT, charging a levy of 0.02% on equity transactions lasting less than 0.5 seconds. Market growth edit In the early 2000s, high-frequency tr

High-frequency trading is quantitative trading that is characterized by short portfolio holding periods. All portfolio-allocation decisions are made by computerized quantitative models. The success of high-frequency trading strategies is largely driven by their ability to simultaneously process large volumes of information, something ordinary human traders cannot do. Specific algorithms are closely guarded by their owners. Many practical algorithms are in fact quite simple arbitrages which could previously have been performed at lower frequency—competition tends to occur through who can execute them the fastest rather than who can create new breakthrough algorithms. The common types of high-frequency trading include several types of market-making, event arbitrage, statistical arbitrage, and latency arbitrage. Most high-frequency trading strategies are not fraudulent, but instead exploit minute deviations from market equilibrium. Market making edit According to SEC: A "market ma

The effects of algorithmic and high-frequency trading are the subject of ongoing research. High frequency trading causes regulatory concerns as a contributor to market fragility. Regulators claim these practices contributed to volatility in the May 6, 2010 Flash Crash and find that risk controls are much less stringent for faster trades. Members of the financial industry generally claim high-frequency trading substantially improves market liquidity, narrows bid-offer spread, lowers volatility and makes trading and investing cheaper for other market participants. An academic study found that, for large-cap stocks and in quiescent markets during periods of "generally rising stock prices", high-frequency trading lowers the cost of trading and increases the informativeness of quotes;: 31 however, it found "no significant effects for smaller-cap stocks",: 3 and "it remains an open question whether algorithmic trading and algorithmic liquidity supply are equally be

In 2015 the Paris-based regulator of the 28-nation European Union, the European Securities and Markets Authority, proposed time standards to span the EU, that would more accurately synchronize trading clocks "to within a nanosecond, or one-billionth of a second" to refine regulation of gateway-to-gateway latency time—"the speed at which trading venues acknowledge an order after receiving a trade request". Using these more detailed time-stamps, regulators would be better able to distinguish the order in which trade requests are received and executed, to identify market abuse and prevent potential manipulation of European securities markets by traders using advanced, powerful, fast computers and networks. The fastest technologies give traders an advantage over other "slower" investors as they can change prices of the securities they trade.

According to author Walter Mattli, the ability of regulators to enforce the rules has greatly declined since 2005 with the passing of the Regulation National Market System (Reg NMS) by the US Securities and Exchange Commission. As a result, the NYSE's quasi monopoly role as a stock rule maker was undermined and turned the stock exchange into one of many globally operating exchanges. The market then became more fractured and granular, as did the regulatory bodies, and since stock exchanges had turned into entities also seeking to maximize profits, the one with the most lenient regulators were rewarded, and oversight over traders' activities was lost. This fragmentation has greatly benefitted HFT. High-frequency trading comprises many different types of algorithms. Various studies reported that certain types of market-making high-frequency trading reduces volatility and does not pose a systemic risk, and lowers transaction costs for retail investors, without impacting long term i

Regulation and enforcement edit In March 2012, regulators fined Octeg LLC, the equities market-making unit of high-frequency trading firm Getco LLC, for $450,000. Octeg violated Nasdaq rules and failed to maintain proper supervision over its stock trading activities. The fine resulted from a request by Nasdaq OMX for regulators to investigate the activity at Octeg LLC from the day after the May 6, 2010 Flash Crash through the following December. Nasdaq determined the Getco subsidiary lacked reasonable oversight of its algo-driven high-frequency trading. In October 2013, regulators fined Knight Capital $12 million for the trading malfunction that led to its collapse. Knight was found to have violated the SEC's market access rule, in effect since 2010 to prevent such mistakes. Regulators stated the HFT firm ignored dozens of error messages before its computers sent millions of unintended orders to the market. Knight Capital eventually merged with Getco to form KCG Holdings. Knight lo

Advanced computerized trading platforms and market gateways are becoming standard tools of most types of traders, including high-frequency traders. Broker-dealers now compete on routing order flow directly, in the fastest and most efficient manner, to the line handler where it undergoes a strict set of risk filters before hitting the execution venue(s). Ultra-low latency direct market access (ULLDMA) is a hot topic amongst brokers and technology vendors such as Goldman Sachs, Credit Suisse, and UBS. Typically, ULLDMA systems can currently handle high amounts of volume and boast round-trip order execution speeds (from hitting "transmit order" to receiving an acknowledgment) of 10 milliseconds or less. Such performance is achieved with the use of hardware acceleration or even full-hardware processing of incoming market data, in association with high-speed communication protocols, such as 10 Gigabit Ethernet or PCI Express. More specifically, some companies provide full-hardware