exposure-coach

You can compute market exposure by fusing breadth, regime, flow, and institutional data into a weighted composite model that outputs a unified posture recommendation and capital allocation ceiling.

A unified market posture model synthesizes diverse market signals into a single decision framework to determine how much capital to allocate, bias direction, and whether new entries are appropriate.

Yes, you can automate risk posture adjustments when signals converge or diverge by running the exposure calculation workflow to generate JSON posture reports suitable for automation pipelines.

You can generate a trade exposure report with partial market data by supplying available breadth, regime, top risk, and uptrend inputs, applying a built-in haircut penalty for missing critical signals.

Apply a weighted composite model for trade exposure at the start of trading periods to determine capital allocation, assess participation breadth, and adjust risk posture based on signal convergence.

Limitations of a composite exposure model include requiring critical signal inputs for accurate calculations, as missing breadth, regime, or flow data triggers a built-in haircut that reduces the exposure ceiling.