Robust portfolio optimization for banking foundations: a CVaR approach for asset allocation with mandatory...

Area of Science:

• Finance
• Investment Management
• Risk Management

Background:

• Endowments and Italian foundations of banking origin (FBOs) require specialized asset allocation strategies.
• Long-term investors face unique challenges including regulatory constraints and tail risk.
• Traditional Markowitz models may not fully address the needs of risk-averse, long-term investors.

Purpose of the Study:

• To develop and evaluate an innovative asset allocation strategy for long-term investors.
• To optimize portfolio choices for FBOs considering regulatory constraints.
• To compare the performance of a robust conditional value-at-risk (R-CVaR) approach against the Markowitz model.

Main Methods:

• Implementation of a robust conditional value-at-risk (R-CVaR) approach.
• Analysis of risk-adjusted performances under different risk profiles.
• Comparison with the Markowitz portfolio model using a buy and hold strategy.

Main Results:

• The R-CVaR approach demonstrates superior risk-adjusted returns compared to the Markowitz portfolio.
• The R-CVaR model effectively accounts for tail risk, a limitation in traditional models.
• Performance improvements were observed even when measured by the mean-variance metric.

Conclusions:

• The R-CVaR strategy offers a more effective asset allocation for long-term investors like FBOs.
• This approach enhances portfolio optimization by addressing tail risk and regulatory considerations.
• R-CVaR provides a robust alternative to traditional mean-variance optimization for specific investor types.