exposure-coach

Portfolio exposure synthesis combines breadth, macro regime, and institutional flow signals into one composite score. The engine applies predefined weights to upstream JSON inputs, resolving conflicting signals to output a unified market posture with a specific equity exposure ceiling.

Sizing equity positions under conflicting signals requires a composite scoring engine that applies predefined weights to breadth, uptrend, and risk outputs. This resolves the conflict by generating a single exposure ceiling and a NEW_ENTRY_ALLOWED or REDUCE_ONLY recommendation.

Yes, market posture can be computed with partial upstream JSON inputs. The engine accepts missing files, applies haircut logic to the composite score, and reduces the overall confidence level to reflect the lack of critical institutional flow or breadth data.

Setting a growth versus value bias is handled by a signal posture engine that scores upstream macro regime and sector leadership inputs. It synthesizes these analytics to output a directional bias alongside an equity exposure ceiling and participation breadth recommendation.

Signal synthesis models are best used at the start of each trading week or before initiating new positions. They automate risk management by processing multiple JSON analytics files, preventing human error in calculating exposure ceilings and confidence levels across complex institutional flow data.