Risk Budgeting Portfolios from Simulations

Abstract

Risk budgeting is a portfolio strategy where each asset contributes a prespecified amount to the aggregate risk of the portfolio. In this work, we propose a numerical framework that uses only simulations of returns for estimating risk budgeting portfolios. Specifically, we provide a Sample Average Approximation (SAA) algorithm with cutting planes, and a Stochastic Gradient Decent algorithm, tailored to the risk budgeting portfolio for the Expected Shortfall. We illustrate different risk budgeting portfolios, constructed using a especially designed Julia package, on real financial data and compare it to classical portfolio strategies.

Rodrigo S. Targino

Assistant Professor of Statistics