Four distinct trading blocks, each evaluating opportunities from a different angle — rule logic, statistical scoring, market context, and execution risk.
A rules-based decision layer that evaluates every incoming trade signal against historically validated rule logic. It is designed to block weak setups before execution and keep capital focused on stronger conditions.
A machine-learning scoring layer that ranks trade signals by estimated statistical edge before execution. It converts live trade features into probability and score outputs, then applies policy thresholds to decide whether a setup is strong enough to proceed.
A context engine that evaluates the broader market environment around each signal and determines whether conditions support action, caution, or avoidance. It helps the system respond differently when the same setup appears in different market states.
A microstructure risk layer that evaluates execution quality at the moment of entry. It helps prevent trades from being placed when spread, entry premium, or short-term instability suggest poor execution conditions.