Algorithmic trading has been increasing in recent years as an overall percentage of daily trading volume. Why? Let’s briefly examine the motivations for why a more traditional buy-side firm would want to use algorithms to execute trades and why the sell-side has been eager to supply these solutions.

From the viewpoint of an asset manager, using algorithms (for executing trades, rather than screening arbitrage opportunities or making a market) reduces trading costs, provides a potentially higher degree of anonymity, a lower degree of risk, and allows for increased volumes to be executed. Though the strategy can differ, algorithms for the execution of trades possess many of the same basic properties- they break up large blocks of orders and programmatically attempt to execute them to achieve a particular goal. Some, for example, attempt to execute trades based on a VWAP strategy. Therefore, they increase trading during times of heavier volume (mornings and late afternoons), allowing for a minimization of market impact. Market impact, along with opportunity and delay costs, can be thought of as implicit costs. Essentially, they can be described as the delay between order and execution whereas market impact is the price fluctuation created in the market by trading a particular security. However, algorithmic trading has also driven down explicit costs, such as commissions and fees. It is cheaper for a trader to execute through a program rather than placing an order through a broker. Along these same lines, it can be argued that the use of programmatic trading increases anonymity. Traders are not explicitly revealing their positions to another party. One could argue that this reduces the potential for front-running, though nothing is guaranteed. Furthermore, the reduction in workflow by traders on either end decreases the odds of manual error, mitigating risk. Finally, a more computerized flow of information allows for higher volumes to be worked in the market.

The sell-side values algorithms because they maintain their positions as intermediaries between the buy-side and the market. Though algorithms result in decreased transaction costs on a per-share basis, they can handle and encourage higher volumes of trades, thus increasing revenues. Additionally, the creation of algorithms and their implementation possess a far lower variable cost when presented with the alternative; that is, the presence of highly paid brokers on the trading desk to execute trades. Thus, the sell-side can create economies of scale much easier with programmatic trading than with actual traders.