Evaluating Portfolio Allocation Strategies of Sovereign Wealth Funds: A Comparative Analysis of Alternative Optimization Techniques

Purpose: This paper applies portfolio optimization techniques to the asset allocations of Sovereign Wealth Funds (SWFs). Methodology: Using a dataset of assets under management (AUM) values from 21 major SWFs during the period 2010–2024, we evaluate the effectiveness of four optimization strategies: minimum variance portfolio (MVP), maximum Sharpe ratio (MSR), risk parity (RP), and conditional value-at-risk (CVaR). Each model incorporates allocations to long-term average AUM weights, thereby reflecting institutional inertia and capital constraints. Findings: The findings demonstrate that MSR and CVaR strategies outperform the others based on risk-adjusted returns, while MVP ensures portfolio stability and RP facilitate risk diversification. Unique Contribution to Theory, Practice and Policy: These results have significant implications for the construction of robust SWF asset allocation frameworks and contribute to the broader debate on optimal portfolio design under institutional constraints.