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ai-hedge-fund: A simulation tool for AI investment decisions

Translated

소개하는 봇

If you want to practice your decision-making process by studying investing, this is an educational simulation tool that mimics the decision-making of AI investors.

3-Line Summary

1) It is an educational tool that simulates how various AI investment agents make stock investment decisions. 2) Install it in the terminal by running `pipx install aihf`, then run it by typing `aihf`. 3) Use it to build a track record of simulated investments with virtual money or to test strategies against historical market data; do not use it for actual trading.

Image source: virattt/ai-hedge-fund repository README

At a Glance

• 64,468 stars (as of November 4, 2026) • Programming language: Python 99.9% (an easy-to-read, general-purpose language) • License: MIT (an open-source license that allows free use as long as the source is credited) • Korean: There are no Korean instructions in the README, and I was unable to verify the interface language • Last updated: November 3, 2026 https://github.com/virattt/ai-hedge-fund

How to Use It

1) Install it in the terminal using the command below. pipx is a tool that installs Python programs in a separate, isolated environment. pipx install aihf 2) Running the command below without any arguments will open an app with a menu interface in the terminal. aihf 3) The app will prompt you for a key the first time you use it. Choose either “Simulated Investment Mode” or “Backtesting” (a feature that validates results using historical market data) and run it. You’ll need a Financial Datasets (stock data service) key and an AI model service key; the amounts are not listed in the README.

Popular Comments

GitHub Issue #182 · 12 reactions · apegeek · March 2025 "Chinese stock market data is more complex and subject to stricter conditions. I hope you will add support for Chinese capital market data as soon as possible." (Translation) https://github.com/virattt/ai-hedge-fund/issues/182

Points to Note

This is not an investment recommendation. If you invest based on the results, you may incur losses, and README states that it is not liable for any losses. Data and AI model keys may incur costs.

This post was organized with the help of AI.