Algo trading is a method of trading where decisions are made by software instead of human traders. The system follows a set of rules that define when to enter or exit a trade. These rules can be based on market data, technical indicators, price movements, or statistical models.
The goal of algorithmic trading is to execute trades quickly, consistently, and based on logic rather than human judgment. Developers and analysts design the algorithm, test it against historical data, and deploy it in real markets. Once active, the algorithm monitors conditions and places trades whenever the rules are met.
Algo trading is used in many areas of the market. Some strategies operate on long-term signals, while others react to short-term data. Institutions, hedge funds, and ATFunds rely on automation to handle large volumes of data, reduce manual errors, and maintain systematic trading processes.
Algo trading improves speed, accuracy, and consistency in financial markets. It lets traders act on data instantly, remove emotional decision-making, and run strategies that would be difficult to execute manually.
Algo trading uses predefined rules built into software systems. The algorithm scans market data, checks the rules, and executes a trade automatically when the conditions are met.
No. Institutions use it at scale, but individual traders also use smaller algorithmic systems, automated bots, or rule-based trading tools to run their strategies.
A trader builds an algorithm that buys a stock when its price rises above a certain level and sells it when it drops below another level. The system monitors prices in real time and places orders automatically whenever those conditions occur.
Algo trading systems depend on reliable data. FinFeedAPI’s Stock API, Currency API, SEC API, and Prediction Market API provide clean, fast market data that algorithms use to generate signals and execute trades. Developers use these feeds to support backtesting, trading, and automated decision-making.
