Algorithmic Trading – Driving Competitiveness to New Levels
Ongoing developments in information technology have resulted in dramatic changes in the business environment of stock exchanges. An increase in algorithmic trading is seen as a driving force behind many of these changes that have resulted in established stock exchanges investing millions of dollars in information technology, as well as lowering commissions and trade processing fees in order to remain competitive and attract algorithmic traders.
Algorithmic trading in electronic financial markets makes use of computer programs for entering trading orders, relying on the computer algorithm to decide on a number of aspects of the order, such as price, timing and even the quantity of the order. Algorithmic trading has the benefit of receiving vital information electronically, generally quite some time before human traders have access to the information. This trading strategy is widely used by pension funds, mutual funds, hedge funds and other institutional traders in order to split a large trade into a number of smaller trades with the objective of managing risk, market impact and opportunity cost.
Different algorithms have been developed in order to implement specific trading strategies, allowing algorithmic trading to be utilized effectively in any investment strategy, including inter-market spreading, market making, speculation, trend following, mean reversion and statistical arbitrage. According to a report by Aite Group LLC, a Boston-based consulting firm, one third of all US and EU stock trades in 2006 were implemented by algorithms and it is anticipated that this figure will rise to at least 50 percent by 2010, with some analysts predicting that the figure will be even higher.
Although algorithmic trading, also referred to as algo, black-box, automated, or robo trading, is widely accepted as an efficient means of trading, it is not without its drawbacks. Concerns have been raised by regulators in Great Britain that increased reliance on black-box, or algorithmic trading, makes the market vulnerable in the event of systems failure. A system breakdown could even lead to a market crash, with devastating results. Other negative issues relating to algorithmic trading include security, front-running and latency – a technical time delay in getting quotes to traders.
Although these are valid concerns, the fact remains that algorithmic trading implements transactions at a speed that no human trader could ever hope to match. With the intense level of competition between major stock exchanges and the increasing number of new electronic trading platforms, such as Chi-X and Turquoise, milliseconds can make a huge difference.