Financial Portfolio Optimization: A QAOA and VQE Formulation for Sharpe Ratio Maximization
Naman Kaushik, Aryan Raj, Milind Srivastava, Md Sajidullah Ansari, M. Pushpalatha, Malavika Krishnamoorthy Gayathri, L. Kavisankar, Sangram Deshpande, Raghavendra Venkatraman · 2023
A quantum approach for portfolio optimization involves using quantum computing to solve complex optimization problems related to portfolio selection. The approach involves constructing a mathematical model of the portfolio optimization problem using various algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) or the Variational Quantum Eigensolver (VQE). This approach has the potential to provide more accurate and efficient solutions than classical approaches, particularly for large and complex portfolio optimization problems. Moreover, this paper also dives into discussing and comparing the results obtained from both these approaches. Our work is under the assumptions required for the proposed formulation deriving meaningful considerations about the solution quality found, measured as the value of Sharpe Ratio.