AI and data-driven quantitative portfolio management library for portfolio risk and performance analysis 投资组合管理
Project description
By Investors, For Investors.
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.
Features
| Feature 📰 | Status |
|---|---|
| Empyrial (backtesting + performance analysis) | Released on May 30, 2021 |
| Oracle (prediction lens using several ML models) | Beta on Jun 1, 2021 |
| Fundamental lens | In development... |
| Risk lens | In development... |
| Alpha lens | In development... |
| Sentiment lens | In development... |
Here are the functions available with Empyrial:
-
empyrial: quantitative and performance analysis of your portfolio | Quickstart | Documentation -
oracle: prediction generation on your portfolio using several prediction models (Prophet, Auto-ARIMA, Fast Fourier Transform...) | Quickstart| Documentation
Usage
from empyrial import empyrial, Engine
portfolio = Engine(
start_date= "2020-06-09",
portfolio= ["BABA", "RELIANCE.NS", "KO", "^DJI","^IXIC"],
weights = [0.2, 0.2, 0.2, 0.2, 0.2],
benchmark = ["SPY"]
)
empyrial(portfolio)
Output:
Full documentation : https://github.com/ssantoshp/Empyrial
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