使用量子计算机进行信用风险分析
Credit Risk Analysis using Quantum Computers
摘要：
我们提出并分析了一个量子算法，以估计信用风险更有效地比蒙特卡罗模拟可以在经典的计算机上。更准确地说，我们估计经济资本要求，即风险价值与给定损失分布的期望值之间的差异。经济资本要求是一个重要的风险指标，因为它总结了在给定的置信水平下保持偿付能力所需的资本金额。我们实现这个问题的一个现实的损失分布，并分析其缩放到一个现实的问题大小。特别是，我们提供了所需量子位总数的估计，预期的电路深度，以及在未来容错量子硬件的合理假设下，这如何转化为预期的运行时间。
英文摘要：
We present and analyze a quantum algorithm to estimate credit risk more efficiently than Monte Carlo simulations can do on classical computers. More precisely, we estimate the economic capital requirement, i.e. the difference between the Value at Risk and the expected value of a given loss distribution. The economic capital requirement is an important risk metric because it summarizes the amount of capital required to remain solvent at a given confidence level. We implement this problem for a realistic loss distribution and analyze its scaling to a realistic problem size. In particular, we provide estimates of the total number of required qubits, the expected circuit depth, and how this translates into an expected runtime under reasonable assumptions on future fault-tolerant quantum hardware.
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