I built an AI trading experiment in which four local LLMs argue bull and bear cases on stocks, and a host model grades the debate and decides BUY, SELL, or HOLD. Most days it holds. Sometimes it loses in hilariously dumb ways, so I do a postmortem on which model became overconfident, which bias showed up, and where the reasoning broke down. It runs on local inference, uses Alpaca paper trading, and pulls from 50+ free data sources. No real money yet, no paid APIs, no course/newsletter/Patreon etc… The fun part is watching the debate transcripts, agreement heatmaps, and bad takes unfold live. Stack: • Mac Studio M3 Ultra running four different LLL model families locally, which are MoE’s. • FastAPI on a Mac Mini, pushing snapshots to the web app so the bot can crash without taking the site down • ThinkStation PGX for generating the photos, videos and podcasts, etc. It also transcribes YouTube videos to use as data. • Alpaca paper accounts for now. No real money yet; the goal is real money once it stops losing on dumb stuff • 50+ free data sources, no paid APIs whatsoever. • Built with Claude Code. Site: https://moefolio.ai/ submitted by /u/Covert-Agenda
Originally posted by u/Covert-Agenda on r/ArtificialInteligence