Automated Trading (Algorithmic Trading)

DEFINITION of Automated trading

Automated trading is the process of buying or selling security basing on some pre-described set of rules tested on historical data.


That’s when you use algorithms for making trade orders. The rules are based on indicators, charts, technical analysis, or stock fundamentals. To trade it, you need an automated trading system. You can set up the rules that you want the algorithmic trading system to follow.

Rules are based on common variables like price and volume or on technical indicators like moving averages or Bollinger bands. The trading strategy you set up can be as simple. Or complicated. But truly advanced strategies can require learning the programming language associated with your automated trading system. Traders use algorithmic trading because it removes emotion from the trading practice. Algorithmic trading systems need monitoring to provide that they are performing as wanted because of the presence of many problems. Technical failures can be problematic, the fault in set up. Anyway, automated trading can quickly become costly.

Algorithmic trading has grown dramatically in popularity over the past decade. In the US, about 70 percent of the overall trading volume is generated through algorithmic trading. The overall trading volume of algorithmic trading estimated in emerging economies like India is roughly 40 percent. A recent report estimated that the world market for algorithmic trading will grow by 10.3% CARG from 2016 to 2020. By now, most investors and regulators have gravitated toward algorithmic and High-Frequency Trading.


Algorithmic trading (automated trading, black-box trading, or simply algo-trading) is the process of using computers programmed to follow a defined set of instructions. Those instructions are called algorithm for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader.