论文标题
混合量子投资优化，持有周期最少
Hybrid Quantum Investment Optimization with Minimal Holding Period
论文作者
论文摘要
在本文中，我们提出了一种用于动态投资组合优化的混合量子古典算法，并且保持最少。我们的算法基于在每个交易步骤中使用量子处理器在每个交易步骤中对近乎最佳的投资组合进行采样，并有效地进行选择以满足最小的持有约束。我们在使用D-WAVE 2000Q处理器的50个资产的数据集中发现了最佳投资轨迹。我们的方法非常有效，并且与典型投资组合相比，产生的结果更接近有效的边界。此外，我们还展示了我们的方法如何轻松地产生适合不同风险概况的轨迹，这通常是金融产品中提供的。我们的结果是一个明确的例子，说明了如何在当前NISQ量子处理器中提供量子和古典技术的组合如何提供新颖的有价值的工具来处理现实生活中的问题，除了简单的玩具模型。
In this paper we propose a hybrid quantum-classical algorithm for dynamic portfolio optimization with minimal holding period. Our algorithm is based on sampling the near-optimal portfolios at each trading step using a quantum processor, and efficiently post-selecting to meet the minimal holding constraint. We found the optimal investment trajectory in a dataset of 50 assets spanning a one year trading period using the D-Wave 2000Q processor. Our method is remarkably efficient, and produces results much closer to the efficient frontier than typical portfolios. Moreover, we also show how our approach can easily produce trajectories adapted to different risk profiles, as typically offered in financial products. Our results are a clear example of how the combination of quantum and classical techniques can offer novel valuable tools to deal with real-life problems, beyond simple toy models, in current NISQ quantum processors.
