In electronic financial markets, algorithmic trading or automated trading, also known as algo trading, black-box trading or robo trading, is the use of computer programs for entering trading orders with the computer algorithm deciding on aspects of the order such as the timing, price, or quantity of the order, or in many cases initiating the order without human intervention. Algorithmic Trading is widely used by pension funds, mutual funds, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades in order to manage market impact, and risk.[1][2] Sell side traders, such as market makers and some hedge funds, provide liquidity to the market, generating and executing orders automatically. A special class of algorithmic trading is "high-frequency trading" (HFT), in which computers make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe.
Algorithmic trading may be used in any investment strategy, including market making, inter-market spreading, arbitrage, or pure speculation (including trend following). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically ("on auto-pilot").
A third of all EU and US stock trades in 2006 were driven by automatic programs, or algorithms, according to Boston-based financial services industry research and consulting firm Aite Group.[3] As of 2009, high frequency trading firms account for 73% of all US equity trading volume.[4]
In 2006 at the London Stock Exchange, over 40% of all orders were entered by algo traders, with 60% predicted for 2007. American markets and equity markets generally have a higher proportion of algo trades than other markets, and estimates for 2008 range as high as an 80% proportion in some markets. Foreign exchange markets also have active algo trading (about 25% of orders in 2006).[5] Futures and options markets are considered to be fairly easily integrated into algorithmic trading,[6] with about 20% of options volume expected to be computer generated by 2010.[7] Bond markets are moving toward more access to algorithmic traders.[8]
One of the main issues regarding high frequency trading is the difficulty in determining just how profitable it is. A report released in August 2009 by the TABB Group, a financial services industry research firm, estimated that the 300 securities firms and hedge funds that specialize in this type of trading took in roughly $21 billion in profits in 2008[9].
...High-frequency trading In the U.S., high-frequency trading firms represent 2% of the approximately 20,000 firms operating today, but account for 73% of all equity trading volume.[19] As of the first quarter in 2009, total assets under management for hedge funds with high frequency trading strategies were $141 billion, down about 21% from their high.[20] The high frequency strategy was first made successful by Renaissance Technologies.[21] High frequency funds started to become especially popular in 2007 and 2008.[20] Many high frequency firms say they are market makers and that the liquidity they add to the market has lowered volatility and helped narrow spreads, but unlike traditional market makers, such as specialists on the New York Stock Exchange, they have few or no regulatory requirements.
High-frequency trading is quantitative trading that is characterized by short portfolio holding periods (see Wilmott (2008), Aldridge (2009)). There are four key categories of high-frequency trading strategies: market-making based on order flow, market-making based on tick data information, event arbitrage and statistical arbitrage. 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 volumes of information, something ordinary human traders cannot do. Various types of high-frequency strategies are covered in Aldridge, I., "High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems" (Wiley, 2009).
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