# Risk budget portfolios with convex Non-negative Matrix Factorization

arXiv: https://arxiv.org/abs/2204.02757 · HTML: https://mlsanity.com/paper/2204.02757/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 53 references that are in the map.
- First posted on arXiv 6 Apr 2022.

## Builds on (most cited first, 1 of 1)

- [On Identifiability of Nonnegative Matrix Factorization](https://mlsanity.com/paper/1709.00614/) (2017)

## Abstract (arXiv)

We propose a portfolio allocation method based on risk factor budgeting using convex Nonnegative Matrix Factorization (NMF). Unlike classical factor analysis, PCA, or ICA, NMF ensures positive factor loadings to obtain interpretable long-only portfolios. As the NMF factors represent separate sources of risk, they have a quasi-diagonal correlation matrix, promoting diversified portfolio allocations. We evaluate our method in the context of volatility targeting on two long-only global portfolios of cryptocurrencies and traditional assets. Our method outperforms classical portfolio allocations regarding diversification and presents a better risk profile than hierarchical risk parity (HRP). We assess the robustness of our findings using Monte Carlo simulation.