What Is Algorithmic Trading?

Algorithmic trading is a cutting-edge trading strategy that leverages computational algorithms to make trading decisions in electronic financial markets. This approach is widely used in both buy-side and sell-side institutions and serves as the foundation for high-frequency trading, FOREX trading, and associated risk and execution analytics.

Key Components of Algorithmic Trading

1. Strategy Development: Utilize technical time-series, machine learning, and nonlinear time-series methods to create robust trading strategies.
2. Backtesting: Employ parallel and GPU computing to backtest strategies efficiently, identifying optimal parameters for algorithmic trading.
3. Risk Analysis: Calculate profit and loss metrics while conducting comprehensive risk assessments.
4. Execution Analytics: Perform market impact modeling through transaction cost analysis to optimize trade execution.
5. Production Deployment: Seamlessly integrate trading strategies and analytics into production trading environments.

For a deeper dive into algorithmic trading, see MATLAB^® and Datafeed Toolbox™.