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Algorithmic trading uses mathematical models to make decisions and transactions in financial markets. It is most used by large institutional investors due to its ability to split large trades and make quick decisions. Trading algorithms have a long history and have replaced many staff previously needed by investment firms, but traders and analysts are still needed to monitor and optimize the algorithms.
There are almost as many trading strategies in the financial markets as there are investors and traders. Markets are increasingly accessible electronically, opening 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 transactions in the financial markets. A computer, programmed with an algorithm, will enter electronic trading orders when certain technical conditions are met. These conditions may include timing, 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 for large funds. When a fund buys a large amount of a particular stock, for example, this can have the effect of raising the price of the stock enough to negatively impact the profit margin the fund was hoping to make. However, with algorithmic trading, it’s easy to split a large trade into several smaller trades to reduce the impact on the market.
Institutional investors have the added benefit of how quickly 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 forms part of the broad competitive advantage that hedge funds and similar traders can have over individual investors.
Trading algorithms themselves have a much longer history than algorithmic trading. An algorithm simply refers to a sequence of steps for recognizing patterns in real-time market data to detect trading opportunities. Historically, investment firms would employ a large number of individual traders to manually go through the process of creating trading algorithms. However, with the advanced technologies now available, it is a much faster process to build trading algorithms and put them into practice, and far fewer personnel are required. Algorithmic trading has effectively replaced much of the staff previously needed by investment firms.
Traders are still needed, however, to be able to use algorithmic trading. In many cases, a trader will monitor data from many algorithms simultaneously on a digital dashboard, making the trader much more productive. The work of traders and analysts is also still needed to devise new algorithms and optimize existing ones.
Smart Asset.
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