Algorithmic trading uses mathematical models to make decisions and trades in financial markets. It is most widely used by large institutional investors due to its advantages, including the ability to break up large trades and the speed of decision-making. Trading algorithms have a longer history and are used to recognize patterns in real-time market data. Traders are still required for algorithmic trading to be employed.
In the financial markets, there are almost as many trading strategies as there are investors and traders. Markets are becoming more accessible electronically, which opens up even more possibilities for the development of trading systems. One of them is algorithmic trading, a trading system that uses advanced mathematical models called algorithms to make decisions and trades in financial markets. A computer, programmed with an algorithm, will enter electronic trading orders when certain technical conditions are met. These conditions may include time, price, order quantity, and general market trends, among other factors.
Algorithmic trading is most widely used by large institutional investors such as hedge funds, mutual funds, and pension funds. This is the case because the advantages it presents are more relevant to large funds. When a fund buys a large quantity of a given stock, for example, this can have the effect of increasing the share price enough to negatively impact the profit margin the fund expected to achieve. However, with algorithmic trading, it is simple to break up a large trade into several smaller trades to reduce the impact on the market.
Institutional investors have the added advantage of the speed with which automated algorithmic trading programs can make decisions. When market information is received electronically, trading decisions are made automatically, often without the need for any human intervention. Decisions are made and orders are initiated before human traders are even aware of the information. This is part of the great competitive advantage that hedge funds and similar traders can have over individual investors.
Trading algorithms have a much longer history than algorithmic trading. An algorithm simply refers to a sequence of steps to recognize patterns in real-time market data to spot trading opportunities. Historically, investment firms would employ a large number of individual traders to manually carry out the process of creating trading algorithms. However, with the advanced technologies now available, it is a much quicker process to build trading algorithms and put them to use, and much less staff is required. Algorithmic trading has effectively replaced much of the staff previously needed by investment firms.
However, traders are still required for algorithmic trading to be employed. In many cases, a trader will monitor data from many algorithms at once on a digital dashboard, making the trader much more productive. The work of traders and analysts is also needed to design new algorithms and optimize existing ones.
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