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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This repo powers my experiment where ChatGPT manages a real-money micro-cap stock portfolio.
| Date | Stars |
|---|---|
| 2026-07-31 | 7499 |
| 2026-08-02 | 7499 |
| 2026-08-04 | 7501 |
| 2026-08-06 | 7501 |
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# LLM Trading Lab This repository started as a **6-month live micro-cap trading experiment** in which a large language model (ChatGPT) manages a real-money portfolio under strict, predefined rules. What began as a single experiment has evolved into a **baseline framework** for studying how large language models behave as portfolio decision-makers. All historical data, research artifacts, and logs are preserved for transparency and auditability. **Full research evaluation out now: [Evaluating ChatGPT as a Portfolio Decision-Maker in Micro-Cap Equities](Experiments/chatgpt_micro-cap/evaluation/paper.pdf)** --- ## Running Your Own Experiment If you want to run your own AI-managed trading experiment, check out this framework I created for LLM research: [LLM Investor Behavior Benchmark - LIBB](https://github.com/LuckyOne7777/LLM-Investor-Behavior-Benchmark) ## Repository Purpose This repository serves two primary purposes: 1. A **complete, forward-only record** of a live AI-managed trading experiment 2. A **reusable foundation** for future AI-driven trading experiments built on the same structure Historical artifacts remain unchanged. New experiments, analyses, and methodologies are layered on top without rewriting past results. --- ```text ChatGPT-Micro-Cap-Experiment/ │ ├─ README.md ├─ requirements.txt ├─ Makefile │ ├─ experiments/ │ └─ chatgpt_micro_cap/ │ │ │ ├─ trading_script.py │ │ | ├─ graphing/ | │ ├─ daily_returns.py | │ ├─ drawdown.py | │ └─ ... | │ │ ├─ csv_files/ │ │ ├─ Daily_Updates.csv │ │ └─ Trade_Log.csv │ │ │ ├─ evaluation/ │ │ ├─ evaluation_report.md │ │ └─ paper.pdf │ │ │ ├─ collected_artifacts/ │ │ ├─ deep_research_index.md │ │ ├─ chats.md │ │ │ │ │ ├─ Weekly_Deep_Research_MD/ │ │ │ ├─ Week_01_Summary.md │ │ │ ├─ Week_02_Summary.md │ │ │ └─ ... │ │ │ │ │ └─ Weekly_Deep_Research_PDF/ │ │ ├─ Starting_Research.pdf │ │ ├─ Week_01.pdf │ │ ├─ Week_02.pdf │ │ └─ ... │ │ │ ├─ images/ │ │ ├─ equity_vs_baseline.png │ │ ├─ repeated_exposure.png │ │ └─ ... │ │ │ ├─ tables/ │ │ └─ metrics.txt │ │ │ ├─ metrics/ │ │ ├─ load_dataV3.py │ │ └─ episode_pcr.py │ │ │ └─ processing/ │ ├─ ProcessPortfolio.py | │ ├─ ``` --- ## The Concept Every day, I kept seeing the same ad about having some A.I. pick undervalued stocks. It was obvious it was trying to get me to subscribe to some garbage, so I just rolled my eyes. Then I started wondering, "How well would that actually work?" So, starting with just $100, I wanted to answer a simple but powerful question: **Can powerful large language models like ChatGPT actually generate alpha (or at least make smart trading decisions) using real-time data?** Today, this repo has evolved into so much more than simply chasing alpha. --- ## Why This Matters AI is being aggressively marketed as a replacement for human decision-making across industries. Trading is a domain where mistakes are measurable, irreversible, and costly. This platform tests those claims using: - Forward-only decisions - Full transparency - Publicly logged results --- ## Research & Documentation Here are the artifacts links for the Micro-Cap Experiment: - **Research Index:** [Deep Research Index](Experiments/chatgpt_micro-cap/collected_artifacts/deep_research_index.md) - **Decision Logs / Chats:** [Chats](Experiments/chatgpt_micro-cap/collected_artifacts/chats.md) --- ## Features of This Repository - 40 page PDF evaluation over results - Live trading engine used in production - LLM-driven trade selection under hard constraints - Daily CSV-based portfolio accounting - Automated stop-loss enforcement - Benchmark comparisons (S&P 500, Russell 2000) - CAPM, Sharpe, Sortino, and drawdown analytics - Full trade and decision logs --- ## Tech Stack - Python 3.11+
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Mauro · Scandit · Switzerland
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Oskar Stark · SensioLabs Deutschland · Germany
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:9abd9c1d176d5a7e, llm:description: 'This repo powers my experiment where ChatGPT manages a real-money micro-cap stock portfolio.' language: Python
matched fp:9abd9c1d176d5a7e, llm:description: 'This repo powers my experiment where ChatGPT manages a real-money micro-cap stock portfolio.' language: Python
matched fp:9abd9c1d176d5a7e, llm:description: 'This repo powers my experiment where ChatGPT manages a real-money micro-cap stock portfolio.' language: Python