All About Algorithm Trading

Did you know that you could feed a computer with a pre-defined algorithm with conditions for buying a stock on a particular stock market, and it buys the stock of a company when these conditions are met? This is called Algorithm Trading.

Algorithm Trading or Algo Trading is defined as the use of the pre-defined program(s) to execute trades. These pre-defined programs are instructions fed into a computer program that provides the conditions in which the trade should be executed; when the said conditions are met, the trade is executed. The set of instructions can be based on the timing of the trade, price, quantity, or any other mathematical metric. 

This trade can generate profits at a speed and frequency that is impossible for a human trader to generate. Algorithm Trading is beneficial.

It helps in eliminating human-made manual errors such as typing in wrong values. Apart from this, conflicting human emotions and psychological factors are also eliminated as the computer making the trade is neutral. Thus, this helps make trading hassle-free, error-free, and systematic. 

Algorithm trading can execute trades at the best possible prices because it executes trades instantly and accurately to avoid price fluctuations. Therefore, there is a high chance that the trades are executed at the investor's desired levels.

Additionally, algorithm trading involves reduced transaction costs, and it is capable of ‘Simultaneous Monitoring’, that is, it can check on multiple market conditions simultaneously while executing a trade. Back-testing, using real-time and historical data to test a trading strategy, is also possible through Algo-Trading.

However, there are also disadvantages to Algo Trading. Since Algo Trading is done based on mathematical models and historical data, it can’t consider qualitative factors that can influence market movements. Further, it won’t be able to consider market disruptions that might occur in the future, known as ‘Black Swan Events’, resulting in algorithm traders incurring losses. 

Algo trading is also capable of increasing market instability at times. The development of Algo-Trading into a system can be expensive, and Algo-Traders may need to pay ongoing fees for software and data feeds. Furthermore, Algo Trading is subject to various regulatory requirements and oversight to ensure the integrity of a market is maintained. For example, mandatory testing and certification of Algo-Trading systems, strict risk controls, transparency to promote pre-trade and post-trade transparency, etc.

As technology develops and is integrated into the functioning of every industry, it is inevitable for technology to be incorporated into the finance industry, specifically for trading. It is up to us, as humans, to keep a balance. Now, with the rise in AI and its rapid development, it is exciting to see how AI would be used in the finance industry.