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SystemsBackendFinTechReal-Timecompleted

NanoTrade

Real-time paper trading platform with custom matching engine.

01 · The Problem & Hypothesis

Why this needed to be built

Most trading demos are simple database dashboards that fail to simulate realistic order-book mechanics, execution latency, queue matching, and portfolio state reconciliation.

The Core Idea

Understand what happens underneath a real trading interface by building an event-driven paper trading platform powered by a custom matching engine.

02 · Technical Implementation

How the system was architected

Engineered to explore low-latency systems programming, asynchronous job queues, and real-time client communication. The architecture pairs a high-performance matching engine with FastAPI web services, Redis task queues, and WebSockets for live price and execution streaming.

C++ Matching Engine
Python
FastAPI
Redis
Celery
Supabase / PostgreSQL
WebSockets
TypeScript

03 · Key Takeaways Earned

Takeaway 01
Deterministic event ordering and idempotent queues prevent race conditions in financial state machines.
Takeaway 02
Low-level systems understanding gives clarity on where web backend bottlenecks truly originate.