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Open in hackernews

Show HN: Multi-agent AI stock analyzer – 408% return trading Korean market

5•prism_insight•2mo ago
Hey HN! I built PRISM-INSIGHT, a multi-agent system where 13 specialized AI agents collaborate to analyze Korean stocks (KOSPI/KOSDAQ). It's completely open source and has been running live since March 2025.

[What it does] The system automatically detects surging stocks twice daily, generates analyst-level reports, and executes trading strategies. Each agent specializes in something different – technical analysis, trading flows, financials, news, market conditions, etc. They work together like a real research team.

[Why I built this] I wanted to see if GPT-4 and GPT-5 could genuinely replicate what human analysts do, but without the typical single-agent limitations. So I split the work across multiple specialized agents that collaborate. The trading simulation has been running for 8 months now with real Korean market data.

[How to try it]

Join the live Telegram channel! https://t.me/prism_insight_global_en (gets daily alerts and reports)

Check the real-time dashboard! https://analysis.stocksimulation.kr (all trades, performance, AI reasoning)

Clone and run it yourself! https://github.com/dragon1086/prism-insight

[The interesting parts] The system uses MCP (Model Context Protocol) servers to give agents access to live market data, web search, and financial APIs. I'm using GPT-4.1 for analysis, GPT-5 for trading decisions, and Claude Sonnet 4.5 for the conversational bot.

The first trading simulation (Season 1, Mar-Sep 2025) returned 408% across 51 trades. Current season(2) is at +11% realized returns vs KOSPI's +16%. Also running it with real money now ($10k account, up 9.35% since late September).

[Tech stack] Python 3.10+, async/await throughout, SQLite for trade history, Playwright for PDF reports, matplotlib for charts. The whole thing is about 8,400 lines of Python across 56 files.

[What makes it different] Most AI trading projects are either single-agent or black boxes. This one uses a multi-agent architecture where you can see exactly what each agent is analyzing and why. Everything is transparent – the dashboard shows every trade, every decision, and all the reasoning.

It's MIT licensed and runs entirely on your machine if you want. I'm covering the API costs (~$200/month) to keep the public Telegram channel free for 450+ users(Korean channel + Global channel).

Would love feedback on the multi-agent approach or questions about running AI agents in production!

Comments

KurSix•2mo ago
It's a very bold move to open-source a system that claims to generate alpha. In the world of quantitative finance, any real market edge disappears the moment enough people know about it
prism_insight•2mo ago
Thanks for the thoughtful comment! You're right that it's a bold move. However, PRISM isn't a static strategy—it's a dynamic multi-agent system that analyzes real-time data differently each time. The complexity of implementation and the non-deterministic nature of LLMs make it hard to replicate the exact edge. Plus, I believe open-source innovation in this space benefits everyone.
Saladin53•2mo ago
Even if a strategy is exposed and its market utility diminishes, developers don't stop there. Markets change, and systems evolve to adapt. Isn't the true advantage in that "speed" of change and response?
KurSix•2mo ago
Fair point but there's a nuance: by open-sourcing the code the author is democratizing that exact infrastructure for adaptation

Now hundreds of other developers have the same "fast" tool and everyone has to run (adapt) even faster just to stay in place. So publishing the tool still dilutes the edge, just at a meta-level