Primary interaction
Order book
186.90146
186.65199
186.40123
186.1579
185.90194
185.6556
spread 0.50
185.15172
184.9082
184.65167
184.40132
184.1546
183.9036
Execution result
Pick a scenario above.
Time and sales
No trades yet.
Skip to primary interaction
Finance
Order Matching Simulator
Run prepared order scenarios against a browser-simulated limit order book, then inspect fills, resting quantity, and price levels.
- Matches orders by price then time against a live book
- Demonstrates real order-type semantics, not a mock form
- Shows the matching model that mirrors a Python engine
Matching model
Resting orders are sorted by price, then arrival. Incoming orders take the best available price before moving to the next level.
Watch the order consequence before configuring the order form.
Matching
Price-time priority
Best available price first, then resting position.
Under the hood
Capability proof
Capability proof
Order matching engine
Service model
Interactive browser-simulated limit order book.
Intelligence layer
Applies price-time matching to prepared and custom orders.
Operational state
Maintains book levels and a trade tape within the browser session.
Human control
Every order is initiated by the visitor and remains inside the sandbox.
Business value
Shows the systems behavior beneath a financial-product interface.
Architecture
FastAPI auto-loads routers from app/routers/ via pkgutil. New endpoints register by file placement, no manual wiring.
The exchange engine runs as a pure Python in-process matching engine with price-time priority. No database, no broker. The FRED and Polygon clients are thin async wrappers. All AI overlays call GPT-4o-mini with structured prompts that return JSON, not narrative prose.
Deployed on Docker and uvicorn. The shape that matters is the surface, not the deployment.