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Constructing Optimal Portfolios under Risk Budgeting

Asimit, V. ORCID: 0000-0002-7706-0066, Peng, L., Tunaru, R. & Zhou, F. ORCID: 0000-0002-9851-8312 (2023). Constructing Optimal Portfolios under Risk Budgeting.


We provide a mathematical characterization for risk parity/budgeting portfolio construction problems for general risk preferences. For the general problem when distribution of returns is not known, we demonstrate the existence of a solution to the risk budgeting problem for any convex and homogeneous risk preferences. Statistical inferences are determined for those portfolios when risk preferences are ordered by variance or Conditional Value-at-Risk. A novel Conditional Value-at-Risk estimator is proposed, which is shown to perform very well on non i.i.d observations, based on simulated and real-life data, especially during periods of bull market and irrational exuberance. Our numerical results show superior performance of risk parity portfolios in terms of various measure of performance such as Sharpe ratio and diversification when comparing with other benchmark portfolios including the equally weighted portfolio. We also found that the risk parity portfolios with an opportunity set selected via socially responsible investment attributes have good performance.

Publication Type: Other (Preprint)
Additional Information: Copyright the authors, 2023.
Publisher Keywords: Risk budgeting/parity; Portfolio selection; Non-parametric estimation; Social responsible investment
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
H Social Sciences > HF Commerce
Departments: Bayes Business School > Actuarial Science & Insurance
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