Algorithmic Reaction Time

Algorithmic reaction time is the duration required for a computer program to analyze incoming market data and trigger a trading action. It includes the time taken for data parsing, strategy calculation, and signal generation.

This is distinct from network latency, focusing instead on the computational overhead of the strategy logic itself. In competitive environments, even minor improvements in code efficiency can significantly reduce reaction time.

This is critical for strategies that rely on capturing fleeting price discrepancies. Developers must balance the complexity of the model with the need for rapid execution.

Minimizing this time is a core objective in high-frequency trading design.