Risk Management API & Infrastructure Overview
This page exists for technical due diligence.
Last updated: 2025-11-16
This project is commercially licensed for production use. See README for terms.
Coerentis is a modular execution and risk framework composed of independently testable subsystems. This strategy-agnostic trading infrastructure enforces deterministic execution constraints and capital protection rules, sitting between trading signal generators and market execution. Unlike alpha-seeking bots or signal sellers, this infrastructure provides transparent, testable safety rails for algorithmic trading systems.
| Subsystem | Description | Location | Maturity |
|---|---|---|---|
| API Service | FastAPI REST API with authentication, rate limiting, structured logging | app/ |
PRODUCTION |
| Safety Rails / Risk Gates | Deterministic hard limits (max drawdown, regime guard, health check) | app/core/safety_rails.py |
PRODUCTION |
| Simulation Engine | Historical simulation and validation tooling | live_sim/ |
BETA |
| Strategy Plug-in Interface | Plugin interface for external trading strategies | strategies/ |
PRODUCTION |
| Data Adapters | Market data fetching and normalization (CoinGecko) | data/ |
BETA |
| Monitoring / Metrics | Health checks, performance metrics, structured logging | app/routes/healthz.py, app/routes/metrics.py |
PRODUCTION |
| Dashboard | Web-based monitoring dashboard | dashboard/ |
BETA |
| Deployment Templates | Infrastructure deployment documentation and templates | infra/ |
UNVERIFIED |
boonmindx_capital_shield/ excluding tests, reports, and data files.
API endpoints counted from FastAPI route decorators in app/routes/.
Test count includes all test_*.py files in tests/ directory.
Safety rules counted from app/core/safety_rails.py: max drawdown check, health check, regime guard.
Plugin interface for external trading strategies. Includes one example strategy (demo only, not for production).
pytest - Python testing framework
In MOCK mode, the system produces deterministic outputs: same inputs produce same outputs. Safety rail decisions are deterministic and testable. Simulation engine uses deterministic algorithms for historical validation.