Market events significantly impact financial markets through price movements, volume changes, and market microstructure alterations. These events can be planned (like regulatory announcements) or sudden (like natural disasters), each requiring different algorithmic trading responses.

Algorithmic traders must adapt their strategies to handle various types of market events, from predictable White Swan events to unpredictable Black Swan events, each presenting unique challenges and opportunities for automated trading systems.

Understanding event classification and impact assessment is crucial for developing robust algorithmic trading strategies that can maintain performance across different market conditions and event scenarios.