CryptoPortfolioOpt
An exploration of the latest models for portfolio optimization applied to cryptocurrencies.
Project Description
This Jupyter notebook project explores cryptocurrency portfolio optimization using modern portfolio theory and machine learning techniques. The analysis combines traditional financial concepts with the unique characteristics of crypto markets to create more efficient portfolio allocation strategies. The notebook demonstrates how to:
- Fetch and analyze crypto portfolio data across multiple blockchain networks using the 1inch API Implement advanced portfolio optimization algorithms like Hierarchical Risk Parity (HRP)
- Compare different risk measures and their impact on portfolio allocation
- Visualize portfolio composition and risk metrics
How it's Made
It was built using a jupyter notebook on google colab, using python. I used 1inch API to get the latest portfolio allocation for some addresses as their historical balance. I used risk folio package to optimize the portfolio using machine learning. I was expecting to get a more risker portfolio optimization but I got a very conservative one, where suggest to allocate almost everything in stablecoins. The algorithm was able to cluster stablecoin and other assets.
