Metadata-Version: 2.1
Name: empyrial
Version: 1.4.4
Summary: AI and data-driven quantitative portfolio management for risk and performance analytics
Home-page: https://github.com/ssantoshp/Empyrial
Author: Santosh Passoubady
Author-email: santoshpassoubady@gmail.com
License: MIT
Platform: UNKNOWN
Description-Content-Type: text/markdown
License-File: license.txt

# By Investors, For Investors.

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<img src="https://i.ibb.co/RjLg9VV/logo.png"/>
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![](https://img.shields.io/badge/Downloads-6.3k-brightgreen)
![](https://img.shields.io/badge/license-MIT-orange)
![](https://img.shields.io/badge/version-1.4.0-blueviolet)
![](https://img.shields.io/badge/language-python🐍-blue)
![](https://img.shields.io/badge/activity-8.8/10-ff69b4)
![](https://img.shields.io/badge/Open%20source-💜-white)	
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/ssantoshp/GetStartedEmpyrial/main?filepath=get_started_with_empyrial.ipynb)
  
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Empyrial is a Python-based **open-source quantitative investment** library dedicated to **financial institutions** and **retail investors**, officially released in Mars 2021. Already used by **thousands of people working in the finance industry**, Empyrial aims to become an all-in-one platform for **portfolio management**, **analysis**, and **optimization**.

Empyrial **empowers portfolio management** by bringing different financial approaches such as **risk analysis**, **quantitative analysis**, **fundamental analysis**, **factor analysis** and **prediction making**.

With Empyrial, you can easily analyze security or a portfolio with these different approaches and **get the best insights from it**.

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Full documentation : https://github.com/ssantoshp/Empyrial


