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Market Simulator: Simulated financial exchange with a full matching engine
Built a simulated exchange to explore how real trading systems work under the hood. A limit order book with price-time priority matching, supporting multiple instruments each with their own independent book. Implemented partial fill support in the matching engine and a configurable bot framework to stress-test it at scale, with PostgreSQL persisting every trade.
Exposed the whole thing through a REST API (FastAPI) for placing and cancelling orders, querying the live order book, and retrieving trade history; designed and tested like a real production system, not a script.
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Really enjoying using Claude x Framer. Its truly a superpower for building simulation engines like this.
800 rows of dummy data for a proto, madness
Title: Market Action Tracker — Real-Time Multi-Timeframe Breakout & Alert Dashboard
Summary:
A live market monitoring dashboard that tracks 20 forex and commodity pairs across multiple timeframes (3min / 5min / 15min) simultaneously, automatically detecting trend state — consolidating vs. breakout — and firing instant alerts the moment structure shifts.
What it does:
Continuously scans price action across each pair and timeframe in parallel, classifying every pair as consolidating or in an active breakout (bullish/bearish) in real time
Live-updating alert feed logs each breakout the instant it triggers — resistance/support breaks, timestamped to the second
Multi-timeframe view surfaces structure shifts as they cascade from short to longer windows, instead of flipping between charts
Auto-refresh with a visible "MARKET LIVE" status and last-updated timestamp, so there's no ambiguity about data freshness
Notification system surfaces new alerts without needing to babysit the screen
Clean, dark-mode trading-desk UI built for fast scanning — color-coded states (green breakout, orange consolidating, red breakdown) so you can read market posture at a glance
Why it matters:
Manually watching 20 pairs across 3 timeframes for structure breaks doesn't scale — this collapses that into a single glanceable view with alerting doing the watching for you, so you only look up when something's actually happening.
This dashboard sounds like a game-changer for traders—how does it handle false breakout alerts?
Behind the Scenes: Building High-Performance Desktop Applications with Electron.js
Electron has become one of my favorite technologies for creating powerful cross-platform desktop applications. It combines modern web development with native desktop capabilities, making it possible to build sophisticated software from a single codebase.
For one of my recent projects, I engineered a desktop application capable of processing live data, monitoring user interactions, and managing complex workflows in real time. Performance was a top priority, so every component from rendering to background processes was optimized to reduce memory usage and improve responsiveness.
Instead of focusing only on functionality, I prioritize clean architecture, reusable components, and maintainable code. This approach allows applications to scale while remaining easy to update as business requirements evolve.
Whether it's automation software, analytics dashboards, or enterprise desktop tools, I believe great software should feel fast, intuitive, and reliable. That's the standard I bring to every project I build.
