BookTrading
Run trading strategies on paper before a single dollar is at risk.
Testing DCA, grid, and prediction-market strategies with real capital meant no proof they worked before money was on the line.
A public prototype demonstrates the interaction; scope and data are intentionally limited.
Case Study
Before
Needed a production-grade trading system that could run multiple strategies (DCA, grid, prediction markets) with real-time market data while keeping capital safe through paper-trading validation.
After
Running multi-symbol grid bots with ATR-based adaptive spacing. Paper trading evidence loop generates statistical proof before any real capital is risked.
How it's solved
Built a Docker Compose stack with Go microservices for order execution, Python for signal analysis, and PostgreSQL for trade history. Implemented a kill-switch protocol and paper-only execution constraint until evidence loop validates profitability.
Trade-offs
Paper-trading only for now — no real capital has validated these strategies yet.
Related Articles
Further reading on related topics from the blog
The Solopreneur Tech Stack: Tools and Systems for One-Person Operations
A deep dive into the tools, automations, and systems I use to run 100+ projects as a solo operator — from MCP servers and AI agents to deployment pipelines and analytics.
Building 100 Micro-Frontends: Lessons from a Solopreneur Journey
How I built and deployed 100 independently deployed micro-frontends on Vercel, the architecture decisions, trade-offs, and what I learned about scaling a one-person dev operation.
AI Integration Patterns for Web Developers: A Practical Guide
Practical patterns for integrating AI into web applications — from prompt engineering and streaming responses to building AI-powered tools that solve real user problems.
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