Quantitative trading—often called algorithmic trading—uses mathematical models and computer algorithms to analyze data and execute trades automatically, minimizing human emotion and maximizing efficiency.

While it started as a tool for large institutions and hedge funds to exploit arbitrage and other opportunities, it has evolved into a mainstream method for asset management companies to create and manage quant funds.

These funds use systematic, data-driven strategies to select and trade assets, often outperforming traditional approaches in certain market conditions.

Advancements in technology and user-friendly platforms have made quantitative and algorithmic trading accessible to retail investors as well.

Retail traders can now connect to brokerage APIs and use pre-built or custom algorithms to automate their trading, benefiting from the same speed, efficiency, and risk management tools as institutions.

This democratization of access allows individuals to participate in sophisticated trading strategies, including arbitrage, trend following, and market making, with lower capital and technical barriers than ever before.

In summary, quantitative trading is no longer exclusive to big players; it is now a powerful and accessible tool for both professional fund managers and retail investors seeking automated, data-driven trading solutions.