Research and Application of Quantum Computing Algorithm for Asset Portfolio Optimization

Portfolio optimization is a critical problem in the field of finance, and quantum computing offers a new approach to address this problem. The author explains the development process of the quantum computing model, including quantum bits, quantum entanglement, quantum gates, quantum circuits, while specifically focusing on quantum state preparation, problem coding, quantum gate operation and quantum measurement in the design of quantum algorithms. Furthermore, the author also introduces the mathematical model of portfolio optimization, including expected return, risk analysis, and mathematical constraints, and illustrates the performance evaluation results of quantum algorithms in portfolio optimization from the perspective of speed and optimization accuracy. With respect to traditional methods, quantum algorithms offer both speed and optimization accuracy advantages, and the optimization accuracy reaches 100%, which illustrates that the quantum algorithm has shown good performance in asset portfolio optimization.