sjufan84/esg_risk_parity

Constructing a portfolio of crypto and stock assets utlizing ESG scores as well as machine learning models to predict buy / sell signals after establishing asset weights using hierarchical risk parity models.

36
/ 100
Emerging

This project helps individual investors or financial analysts construct investment portfolios that combine traditional stocks with cryptocurrencies. It takes ESG scores and historical market data as inputs to determine initial asset weights using hierarchical risk parity. The output is a dashboard that provides predicted buy/sell signals from machine learning models and visualizes potential returns through Monte Carlo simulations.

No commits in the last 6 months.

Use this if you are an investor interested in diversifying your portfolio with both stocks and cryptocurrencies, while also considering ESG factors and using machine learning for trading signals.

Not ideal if you are looking for ready-made financial advice or a fully automated trading system without understanding the underlying models.

portfolio-management ESG-investing cryptocurrency-investing asset-allocation quantitative-finance
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

8

Forks

6

Language

Jupyter Notebook

License

MIT

Last pushed

Jan 16, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sjufan84/esg_risk_parity"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.