LLM-Trading-Lab
This repo powers my experiment where ChatGPT manages a real-money micro-cap stock portfolio.
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Download Latest Version (.zip)- Starting Research Summary.md
- Week 1 Summary.md
- Week 10 Summary.md
- Week 11 Summary.md
- Week 12 Summary.md
- Week 13 Summary.md
- Week 14 Summary.md
- Week 15 Summary.md
- Week 16 Summary.md
- Week 17 Summary.md
- Week 18 Summary.md
- Week 19 Summary.md
- Week 2 Summary.md
- Week 20 Summary.md
- Week 21 Summary.md
- Week 22 Summary.md
- Week 23 Summary.md
- Week 24 Summary.md
- Week 25 Summary.md
- Week 26 Summary.md
- Week 3 Summary.md
- Week 4 Summary.md
- Week 5 Summary.md
- Week 6 Summary.md
- Week 7 Summary.md
- Week 8 Summary.md
- Week 9 Summary.md
- Starting Research.pdf
- Week 1.pdf
- Week 10.pdf
- Week 11.pdf
- Week 12.pdf
- Week 13.pdf
- Week 14.pdf
- Week 15.pdf
- Week 16.pdf
- Week 17.pdf
- Week 18.pdf
- Week 19.pdf
- Week 2.pdf
- Week 20.pdf
- Week 21.pdf
- Week 22.pdf
- Week 23.pdf
- Week 24.pdf
- Week 25.pdf
- Week 26.pdf
- Week 3.pdf
- Week 4.pdf
- Week 5.pdf
- Week 6.pdf
- Week 7.pdf
- Week 8.pdf
- Week 9.pdf
- chats.md
- deep_research_index.md
- README.md
- Daily Updates.csv
- Trade Log.csv
- evaluation_report.md
- paper.pdf
- daily_returns.py
- data_helper.py
- drawdown.py
- episode_pcr_scatter.py
- equity_vs_baseline.py
- highest_pnl_by_ticker.py
- holding_chart.py
- holding_distribution.py
- max_drawdown_vs_largest_run.py
- repeated_ticker_exposure.py
- returns_by_trades.py
- top_losses_vs_wins.py
- daily_returns.png
- drawdown.png
- episode_pcr_scatter.png
- equity_vs_baseline.png
- equity_with_annotations.png
- highest_ticker_pnl.png
- holding_distribution.png
- repeated_exposure.png
- return_by_trades.png
- top_losses_vs_wins.png
- total_logged_days_by_ticker.png
- episode_pcr.py
- load_dataV3.py
- ProcessPortfolio.py
- trading_script.py
- metrics.txt
- csv_conversion.py
- order_verification.py
- __init__.py
- config.py
- fetching.py
- utilities.py
- __init__.py
- main_functions.py
- prompt_models.py
- __init__.py
- daily_prompt.py
- deep_research_prompt.py
- prompt_assembly.py
- starting_prompt.py
- __init__.py
- workflow.py
- AUTOMATION_README.md
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- ignore_list.gitignore
- License.txt
- .gitignore
- Makefile
- README.md
- requirements.txt
# Installation Guide
1. Get the code
git clone https://github.com/LuckyOne7777/LLM-Trading-Lab
Downloads the entire project code from GitHub to your computer.
cd LLM-Trading-Lab
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
pip install -r requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
python <μ€νν νμΌλͺ
>.py # READMEμμ μ νν μ€ν νμΌλͺ
μ νμΈνμΈμ
Runs the Python script (or module).
If it runs without errors and prints output in the terminal, it worked.
3. Make
MediumPrerequisites
- Git Needed to download the project code from GitHub.
- Make Usually pre-installed on Linux/macOS. On Windows, install separately (e.g. via MSYS2 or WSL).
make
Compiles the code based on the generated build configuration to produce an executable.
If it finishes without errors, it worked. Try running the generated executable directly.
// repository documentation
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