Building a trading system from scratch, documented step by step.
So this should have been the first post. I got a little excited with Module 4 — the Zone Manager was producing support and resistance lines that I would actually draw myself, and I had to write about it while it was fresh in my head. If you haven't
The Challenge This post follows on from the Zone Manager development story. Now that we have a working Zone Manager, let's put it through testing to see if it's really production-ready. I wasn't 100% sure how to test the Zone Manager. It's
I wanted to interact with Spirit — to be able to ask questions, explore ideas, and give others an assistant that helps them understand more than static blog posts ever could. When I say “Spirit has a voice”, I don’t mean the trading engine, no that is still driven by
Well… not the trading engine itself, but the assistant that looks after the TradeBOT knowledge base. There’s a new chat button in the bottom-right corner of the site. Click it, ask a question, and Spirit will answer. The assistant pulls from the same documentation, research notes, source code and
Every trader draws support and resistance lines. But teaching an algorithm to identify which ones actually matter—and track their strength as price interacts with them—that's the real challenge. This is the story of building a system that treats S/R zones like magnets: the more price
I spent a couple of weeks training an XGBoost model to predict trade whipsaws, achieving excellent results on an 80/20 train/test split. However, when I tested the model on walk-forward data, it failed spectacularly: 92% performance drop from training to live testing. The model was memorising noise, not
Famous last words. It's March 2025. I fire up Visual Studio for the first time in over a decade. GitHub Copilot is open in another tab. Claude is standing by. I've got a plan: build a machine learning trading bot. Learn ML the way I learn