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AI and data-driven quantitative portfolio management for risk and performance analytics

Project description

By Investors, For Investors.











Binder



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:

report


return


creturn


heatmap


drawdonw


top


rolling

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

Project details


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This version

1.3.6

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