I already code daily in Python, but I want to pair that skill with your proven edge in the stock market to create an algorithm that actually turns a profit. The project is entirely stock-focused, so you should be comfortable translating equity-market concepts—technical, fundamental or quantitative—into clean, testable code. I am also interested in profitable crypto trading. Here’s how I picture the workflow: • Strategy design: we agree on entry, exit and position-sizing rules backed by real trading logic and historical evidence. • Back-testing & walk-forward analysis: robust tests with slippage, commissions and survivorship-bias-free data. • Live integration: connect to a mainstream brokerage API (e.g., Interactive Brokers, Alpaca or similar) for seamless order execution. • Monitoring & reporting: runtime dashboards or logs that track positions, P&L, drawdown and other key metrics. • Documentation: concise README and inline comments so I can extend or tweak the bot independently. Acceptance criteria 1. Back-test shows risk-adjusted outperformance versus the S&P 500 over at least five years. 2. Live paper trading replicates back-test behaviour for two consecutive weeks. 3. Codebase passes linting and unit tests and runs from a single command or Docker image. If you’ve turned trading ideas into consistent results before—and can point to verifiable data or prior bots—let’s talk.