+1 Added to my documents.
Please be aware your selection is temporary depending on your cookies policy.
Remove this selection here

Constrained Risk Budgeting Portfolios

 

WP-Image page

Abstract

This article develops the theory of risk budgeting portfolios, when we would like to impose weight constraints. It appears that the mathematical problem is more complex than the traditional risk budgeting problem. The formulation of the optimization program is particularly critical in order to determine the right risk budgeting portfolio. We also show that numerical solutions can be found using methods that are used in large-scale machine learning problems. Indeed, we develop an algorithm that mixes the method of cyclical coordinate descent (CCD), alternating direction method of multipliers (ADMM), proximal operators and Dykstra’s algorithm.

This theoretical body is then applied to some investment problems. In particular, we show how to dynamically control the turnover of a risk parity portfolio and how to build smart beta portfolios based on the ERC approach by improving the liquidity of the portfolio or reducing the small cap bias. Finally, we highlight the importance of the homogeneity property of risk measures and discuss the related scaling puzzle.

RONCALLI Thierry , Head of Quantitative Research
RICHARD Jean-Charles , Quantitative Research Eisler Capital

Download this article in PDF format

Send by e-mail
Constrained Risk Budgeting Portfolios
Was this article helpful?YES
Thank you for your participation.
0 user(s) have answered Yes.