We introduce the Risk-Budgeted Mean-Variance (RBMV) portfolio, a novel framework that connects the classical Markowitz mean-variance problem and the risk budgeting approach. By modifying the risk budgeting optimization problem to include constraints on expected returns and volatility, RBMV offers a disciplined way to manage the trade-off between risk concentration and return maximization. The investor gains a lever to adjust how close the portfolio sits to either framework, depending on her preferences. We show that the optimization problem that defines the RBMV portfolio is convex, efficiently computable, and typically delivers competitive returns with reduced risk concentration in the context of long-only portfolios. We illustrate our methodology using daily equity returns from the U.S. and show that our methodology efficiently controls the volatility of returns while also delivering Sharpe ratios that are consistently higher than the traditional mean-variance approach.
Comissão Organizadora
Comissão Científica
Ferramenta completa de submissão, avaliação e publicação de anais para eventos científicos.
