Algorithmic trading explained

Algorithmic trading is a way to process trading orders using preprogrammed and automated trading instructions for several variables including volume, price and timing. 

Simply put, an algorithm is a set of instructions for solving an issue. Algorithmic trading uses chart analysis and computer codes to enter and exit trades according to specified parameters, including price movements and volatility levels. 

When the market conditions match the predetermined parameters, trading algorithms execute a buy or sell order. This can save time for tracking the markets and help to execute trades in a matter of seconds. 

Digitisation of the order flow in financial markets started in the 1970s with the launch of the “designated order turnaround” system on the New York Stock Exchange. Algorithmic trading was designed to capitalise on the advantages of computers over human traders, using high-speed data processing. 

Algorithmic trading has gained popularity among institutional and retail traders. It is widely used by mutual funds, hedge funds, pension funds and investment banks, which have to execute large orders and make it much faster than a human being is capable of. 

How does algorithmic trading work? 

Algorithmic trading, which is based on high-speed software and complicated mathematical formulae, is often considered as a synonym to automated trading systems. 

Algorithmic traders often implement high-frequency trading technology, which enables the company to process tens of thousands of trades per second. This type of trading is often used for order execution, trend trading and arbitrage strategies.

The most recent Wall Street technology is connected with machine learning. Artificial Intelligence has allowed programmers to build programs that can improve themselves through deep-learning technology. This meant that traders had the opportunity to develop algorithms based on deep learning to boost their trading performance. 

Algorithmic trading is mostly used by big brokerage firms and institutional investors aiming to decrease costs associated with trading, while market makers usually use algorithmic trades to create liquidity. 

It helps to execute orders faster and easier, which means traders and investors can benefit from small changes in price. For example, the scalping strategy usually involves algorithms to facilitate fast buying and selling orders at small price fluctuations. 

Although algorithmic trading  provides major advantages, such as reduced costs and a higher speed of order execution, it can aggravate the market’s negative issues, contributing to instant loss of liquidity and flash crashes.