标题： 向现实和可解释的市场模拟迈进：使用最优传输分解金融幂律 显示英文标题

标题： Towards Realistic and Interpretable Market Simulations: Factorizing Financial Power Law using Optimal Transport

摘要： 我们使用人工市场模拟研究股票收益幂律分布的机制。 虽然传统金融理论假设价格波动呈高斯分布，但实证研究一致表明，收益分布的尾部遵循幂律。 先前的研究提出了这一现象的假说——一些归因于投资者行为，另一些则归因于机构需求的不平衡。 然而，这些因素很少被同时建模以评估它们的单独和联合贡献。 现实金融市场的复杂性使得利用现有数据隔离单一组件的贡献变得困难。 为了解决这个问题，我们构建了人工市场，并使用最优传输（OT）作为定量相似性度量进行受控实验。 我们提出的框架逐步将行为成分引入代理模型，使我们能够通过OT距离将每个模拟结果与实证数据进行比较。 结果表明，价格的信息效应在再现幂律行为中起主导作用，而多个组件协同作用以增强这种效应。 显示英文摘要

摘要： We investigate the mechanisms behind the power-law distribution of stock returns using artificial market simulations. While traditional financial theory assumes Gaussian price fluctuations, empirical studies consistently show that the tails of return distributions follow a power law. Previous research has proposed hypotheses for this phenomenon -- some attributing it to investor behavior, others to institutional demand imbalances. However, these factors have rarely been modeled together to assess their individual and joint contributions. The complexity of real financial markets complicates the isolation of the contribution of a single component using existing data. To address this, we construct artificial markets and conduct controlled experiments using optimal transport (OT) as a quantitative similarity measure. Our proposed framework incrementally introduces behavioral components into the agent models, allowing us to compare each simulation output with empirical data via OT distances. The results highlight that informational effect of prices plays a dominant role in reproducing power-law behavior and that multiple components interact synergistically to amplify this effect.