Quantum Ensemble Optimisation: Revolutionizing Investment Portfolio Management with QAOA and VQE Integration

Abstract

Quantum computing is presenting promising prospects for financial applications, specifically in the domain of investment portfolio management. The present study investigates the capabilities of Quantum Ensemble Optimisation (QEO), an approach that integrates the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimisation Algorithm (QAOA). Enhancing portfolio performance through a balance between diversification and risk-adjusted returns is our objective. A novel methodology has been devised to integrate the flexibility of VQE with the efficacy of QAOA, yielding an assortment of portfolio solutions. Our investigation into the performance of our model on empirical financial data has revealed that it surpasses conventional optimization techniques in terms of risk-adjusted returns and solution space exploration. The results of this study underscore the potential of our hybrid methodology, which capitalizes on the advantages of QAOA and VQE, to propel the field of quantum-based portfolio optimization forward. This may ultimately result in investors reaching more informed investment decisions and experiencing enhanced financial outcomes.