This repository contains the code for solving constrained risk budgeting with generalized standard deviation-based risk measure:
This formulation encompasses Gaussian value-at-risk and Gaussian expected shortfall and the volatility. The algorithm supports bounds constraints and inequality constraints. It is is efficient for large dimension and suitable for backtesting.
A description can be found in Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles by Jean-Charles Richard and Thierry Roncalli.
- Equally risk contribution
- Risk budgeting
- Risk parity with expected return
- Constrained Risk parity
Can be done using pip:
pip install git+https://github.com/jcrichard/pyrb
Or using uv (recommended for Python 3.12+):
uv add git+https://github.com/jcrichard/pyrb
from pyrb import EqualRiskContribution
ERC = EqualRiskContribution(cov)
ERC.solve()
ERC.get_risk_contributions()
ERC.get_volatility()
This project uses modern Python development tools:
- ruff: For linting and formatting
- pytest: For testing
# Clone the repository
git clone https://github.com/fchareyr/pyrb.git
cd pyrb
# Install in development mode
pip install -e .[dev]pytest# Format code
ruff format
# Lint code
ruff check
# Fix linting issues automatically
ruff check --fix- GitHub Actions workflow runs on every push and pull request
- Tests are run on Python 3.12 and 3.13
- Code must pass linting and formatting checks
- Dependabot automatically updates dependencies
Griveau-Billion, T., Richard, J-C., and Roncalli, T. (2013), A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios, SSRN.
Maillard, S., Roncalli, T. and Teiletche, J. (2010), The Properties of Equally Weighted Risk Contribution Portfolios, Journal of Portfolio Management, 36(4), pp. 60-70.
Richard, J-C., and Roncalli, T. (2015), Smart Beta: Managing Diversification of Minimum Variance Portfolios, in Jurczenko, E. (Ed.), Risk-based and Factor Investing, ISTE Press -- Elsevier.
Richard, J-C., and Roncalli, T. (2019), Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles, SSRN.
Roncalli, T. (2015), Introducing Expected Returns into Risk Parity Portfolios: A New Framework for Asset Allocation, Bankers, Markets & Investors, 138, pp. 18-28.