Abstract :
Abstract Portfolio optimization is a critical problem in finance, aiming to maximize returns while minimizing risks. Traditional approaches have limitations in handling large-scale portfolios efficiently. Quantum computing offers a promising avenue to address this challenge. This article explores the application of quantum algorithms in portfolio optimization, providing insights into their potential advantages and current limitations. We discuss quantum-inspired classical algorithms and quantum algorithms, such as quantum annealing and the quantum approximate optimization algorithm (QAOA). Additionally, we evaluate the current state of quantum hardware and its readiness for practical portfolio optimization. Finally, we highlight key considerations and future directions in leveraging quantum computing for portfolio management.
Keyword :
Keywords: Quantum computing, Portfolio optimization, Quantum algorithms, Quantum-inspired algorithms, Quantum annealing, QAOA, Financial risk management, Quantum hardware, Quantum finance, Portfolio management