Stonks Trading
User Owned Trading Platform
Project overview
Stonks Trading is User Owned Trading Platform. Stonks Trading simplifies money management and asset allocation. Built with high standards for performance, security, and intuitive user experiences, the platform is engineered to support mission-critical workflows and seamless scale.
What was the problem or pain point
Client Dilemma & Technical Bottleneck
Stonks Trading sought to build a high-performance, modern retail stock and options trading platform catering to active day traders who demand institutional-grade execution speeds, real-time Level 2 order books, and advanced options chain visualizers. Traditional retail brokerages offered clunky, slow-refreshing interfaces that lagged during periods of extreme market volatility (such as earnings announcements or market open rushes), causing costly slippage for active traders.
What we suggested to the client
Solid Sphere Architectural Recommendation
Solid Sphere proposed building a reactive, low-latency trading terminal. We recommended developing a high-throughput backend in Go (Golang) capable of processing tens of thousands of market price ticks per second over WebSockets, coupled with an optimized React frontend utilizing HTML5 Canvas rendering for 60fps charting, and direct FIX protocol integrations with clearing brokerages for sub-50ms trade execution.
What made this project challenging
Streaming real-time equity market quotes and candlestick charts with zero browser lag
Building a user-owned social trading ecosystem allowing investors to share and verify trades
Integrating SEC-compliant brokerage clearing APIs for instant order execution (market, limit, stop)
Ensuring fault-tolerant trade reconciliation under severe market volatility events
What was implemented and how it was implemented
Step-by-Step Technical Execution
We architected the trading terminal frontend in React with TypeScript, using custom HTML5 Canvas and WebGL rendering components to display interactive candlestick charts, technical indicators (MACD, RSI, Bollinger Bands), and real-time Level 2 depth-of-market ladders with zero UI stutter. We built the backend in Go, leveraging its concurrent goroutines to handle high-frequency WebSocket streams from market data feeds. Market ticks were normalized and broadcast to active client sessions with sub-10ms distribution latency. We integrated directly with clearing partner APIs and FIX protocol gateways, implementing automated pre-trade risk checks (margin verification, buying power checks) and instant order routing. TimescaleDB was utilized to store tick-by-tick market data, enabling traders to backtest custom technical strategies across historical price action.
How we delivered
Engineered high-throughput Go backend handling sub-millisecond WebSocket market data fanout
Developed interactive financial charting interface supporting technical indicators and volume profiles
Integrated regulatory brokerage execution endpoints with automated order confirmation loops
Implemented community social feed with cryptographically verified trade cards to prevent fake performance
What did we use to implement it
Technology Stack & Technical Rationale
React with TypeScript and HTML5 Canvas delivered institutional-grade charting and 60fps rendering of high-frequency price changes. Go (Golang) provided the ultra-low-latency backend order routing and WebSocket data distribution engine. TimescaleDB and PostgreSQL stored real-time tick histories, order books, and user portfolio states. FIX Protocol and Brokerage APIs enabled sub-50ms order execution. Docker and Kubernetes provided resilient, auto-scaling deployment on AWS.
Key outcomes
Processed over $100M in retail trading volume
Sub-50ms quote streaming latency to mobile and web clients
Zero execution discrepancies or trade failures during market spikes
4.8★ community rating on platform transparency
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