发表机构
University of Vermont; BunnyQuant Capital（佛蒙特大学; BunnyQuant资本）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文将Kuramoto式相干测量应用于五大资产类别的61种金融工具，发现其能检测到经典随机游走方差比测试无法察觉的市场结构，且两种诊断结果统计独立，为跨学科工具应用提供了方法论启示。
AI 中文摘要
耦合振子间的同步现象——从放电神经元、发光萤火虫到电网——是复杂系统中集体行为的普遍特征，经典上通过Kuramoto序参数测量。金融市场被认为是另一类此类系统，交易时间尺度上的价格动态被视为耦合振子；然而，此前应用该测量的研究仅局限于单一资产类别，且从未与该学科自身的经典结构诊断工具——随机游走假说——进行比对。本文中，我们将Kuramoto式相干测量方法统一应用于五大资产类别及61种金融工具（加密货币、外汇、金属、股票指数和单名股票），检测到了经校准、异方差稳健的随机游走方差比测试所无法检测的结构：即使基于相同价格历史在相同时间窗口计算，两种诊断方法在统计上相互独立。该相干测量可在五大资产类别中普遍追踪近期价格走势的方向纯净度，并能提供适度的、依赖资产类别的未来走势幅度预测——在连续交易、易产生动量的市场中预测效果最强——而方差比测试在绝大多数情况下发现该样本面板与随机游走无统计差异。这种独立性表明，源自物理学的同步诊断工具可获取该学科自身统计测试无法触及的结构层面，我们认为这一方法论经验可推广至其他将物理学引入的工具与该领域自身经典零假设测试进行比对的复杂系统。
英文摘要
Synchronization among coupled oscillators -- from firing neurons to flashing fireflies to power grids -- is a universal signature of collective behavior in complex systems, and is classically measured by the Kuramoto order parameter. Financial markets have been proposed as another such system, with price dynamics across trading timescales treated as coupled oscillators; prior work applying this measure, however, has been confined to a single asset class, and has never been checked against the discipline's own classical diagnostic for structure, the random-walk hypothesis. Here we show that a Kuramoto-style coherence measure, applied identically across five asset classes and 61 financial instruments -- cryptocurrency, foreign exchange, metals, equity indices, and single-name equities -- detects structure that a calibrated, heteroskedasticity-robust variance-ratio test of the random-walk hypothesis does not: the two diagnostics are statistically independent of one another even when computed from the same price history on the same time windows. The coherence measure tracks the directional cleanliness of recent price moves universally across all five asset classes, and offers a modest, asset-class-dependent forecast of future move magnitude -- strongest in continuously-traded, momentum-prone markets -- while the variance-ratio test finds the same panel statistically indistinguishable from a random walk in the large majority of cases. This independence indicates that a physics-derived synchronization diagnostic accesses a layer of structure that a discipline-native statistical test cannot, a methodological lesson we expect generalizes to other complex systems where tools imported from physics are compared against a field's own classical null-hypothesis tests.
