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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.
An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎
| Date | Stars |
|---|---|
| 2026-07-24 | 1074 |
| 2026-07-25 | 1074 |
| 2026-07-28 | 1074 |
| 2026-07-30 | 1074 |
| 2026-08-06 | 1074 |
Today
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#### 📢 Announcement
Good news! You can now use a patched version of the library [empyrical](https://github.com/quantopian/empyrical) through EigenLedger! 🎉
<br>
👉 Learn [how to use it here](https://eigenledger.gitbook.io/eigenledger/using-empyrical/using-empyrical) and read more in [this announcement post](https://github.com/santoshlite/EigenLedger/discussions/128).
<br>
# By Investors, For Investors.
<br>
<div align="center">
<img src="https://github.com/user-attachments/assets/470f1d59-09c6-4b95-af7e-f142764d8195"/>
<br><br><br><br>
[](https://colab.research.google.com/drive/1TyNgudyFcsgob7o49PwfDJHLaHvluxaU?usp=sharing)
</div>
<br>
Want to read this in **Mandarin 🇨🇳**? Click [**here**](README_CN.md)
EigenLedger (prev. "Empyrial") is a Python-based **open-source quantitative investment** library dedicated to **financial institutions** and **retail investors**, officially released in 2021. Already used by **thousands of people working in the finance industry**, EigenLedger aims to become an all-in-one platform for **portfolio management**, **analysis**, and **optimization**.
EigenLedger **empowers portfolio management** by bringing the best of **performance and risk analysis** in an **easy-to-understand**, **flexible** and **powerful framework**.
With EigenLedger, you can easily analyze security or a portfolio in order to **get the best insights from it**. This is mainly a **wrapper** of financial analysis libraries such as **Quantstats** and **PyPortfolioOpt**.
<br>
<br>
<div align="center">
| Table of Contents 📖 |
| --
| 1. [Installation](#installation) |
| 2. [Documentation](#documentation) |
| 3. [Quickstart](#quickstart) |
| 4. [Contribution and Issues](#contribution-and-issues) |
| 5. [Contributors](#contributors) |
| 6. [Contact](#contact) |
| 7. [License](#license) |
</div>
## Installation
You can install EigenLedger using pip:
```
pip install EigenLedger
```
For a better experience, **we advise you to use EigenLedger on a notebook** (e.g., Jupyter, Google Colab)
_Note: macOS users will need to install [Xcode Command Line Tools](https://osxdaily.com/2014/02/12/install-command-line-tools-mac-os-x/)._
_Note: Windows users will need to install C++. ([download](https://visualstudio.microsoft.com/thank-you-downloading-visual-studio/?sku=BuildTools&rel=16), [install instructions](https://drive.google.com/file/d/0B4GsMXCRaSSIOWpYQkstajlYZ0tPVkNQSElmTWh1dXFaYkJr/view))_
## Documentation
Here is our full [documentation](https://eigenledger.gitbook.io/documentation)! Check it out our full documentation for detailed guides, all features, and tips on getting the most out of this library.
## Quickstart
```py
from EigenLedger import portfolio_analysis, Engine
portfolio = Engine(
start_date = "2018-08-01",
portfolio = ["BABA", "PDD", "KO", "AMD","^IXIC"],
weights = [0.2, 0.2, 0.2, 0.2, 0.2], # equal weighting is set by default
benchmark = ["SPY"] # SPY is set by default
)
portfolio_analysis(portfolio)
```
<div align="center">
santosh
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Ikko Eltociear Ashimine · Japan
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:780e84ba144a72bb, topic:finance, topic:quantitative-finance, readme:financial