用量子计算机求解外汇储备的最优币种构成
Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer
摘要：
投资组合优化是捷克国家银行战略资产配置不可分割的一部分。量子计算是一种新技术，为这个问题提供了算法。因此，应该研究量子计算机在投资组合优化方面的能力和局限性。在本文中，我们专注于应用量子算法的动态投资组合优化的Markowitz模型的基础上。特别是，我们比较通用的基于门的量子计算机（QAOA，VQE和Grover自适应搜索），单用途量子退火，经典的精确分支定界求解器和经典的启发式算法（模拟退火和遗传优化）的算法。为了运行量子算法，我们使用基于IBM Quantum \textsuperscript{TM}门的量子计算机。我们还采用D-Wave提供的量子退火机。我们展示了投资组合优化，找到最佳的币种构成的CNB的外汇储备。论文的第二个目标是为中央银行和其他金融市场监管机构的工作人员提供有关量子优化算法的文献，因为金融公司正在积极寻找量子计算的可能应用。
英文摘要：
Portfolio optimization is an inseparable part of strategic asset allocation at the Czech National Bank. Quantum computing is a new technology offering algorithms for that problem. The capabilities and limitations of quantum computers with regard to portfolio optimization should therefore be investigated. In this paper, we focus on applications of quantum algorithms to dynamic portfolio optimization based on the Markowitz model. In particular, we compare algorithms for universal gate-based quantum computers (the QAOA, the VQE and Grover adaptive search), single-purpose quantum annealers, the classical exact branch and bound solver and classical heuristic algorithms (simulated annealing and genetic optimization). To run the quantum algorithms we use the IBM Quantum\textsuperscript{TM} gate-based quantum computer. We also employ the quantum annealer offered by D-Wave. We demonstrate portfolio optimization on finding the optimal currency composition of the CNB's FX reserves. A secondary goal of the paper is to provide staff of central banks and other financial market regulators with literature on quantum optimization algorithms, because financial firms are active in finding possible applications of quantum computing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
