Incorporating higher-order moments, like realized volatility, skewness, and kurtosis, is crucial for understanding asymmetric asset pricing trends. Our research rigorously calculates static and dynamic higher-order moment spillovers across nine distinct US industries, using ultra-high-frequency data. We dive into the complex factors driving these spillovers, examining micro and macro-level factors. Our findings illuminate how higher-order moments are transmitted among these industries, particularly during disruptive global events with time-varying patterns. Notably, we discover that crash risk's persistence surpasses that of volatility risk, highlighting a significant divergence in market agents' asset pricing mechanisms. Importantly, firm-level risk factors significantly influence crash risk, showing an inverse relationship with industry-specific uncertainty. On the other hand, external macro-level risk factors directly impact the realized volatility of these industries. Our study's insights have substantial implications for various stakeholders, including investors, fund managers, policymakers, and financial regulators.

中文翻译：

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解读美国工业的不对称溢出效应：来自高阶时刻的见解

结合高阶矩，如已实现波动率、偏度和峰度，对于理解非对称资产定价趋势至关重要。我们的研究使用超高频数据严格计算美国九个不同行业的静态和动态高阶矩溢出。我们深入研究驱动这些溢出效应的复杂因素，研究微观和宏观层面的因素。我们的研究结果阐明了高阶矩如何在这些行业之间传播，特别是在具有时变模式的颠覆性全球事件期间。值得注意的是，我们发现崩盘风险的持续性超过了波动风险，凸显了市场主体资产定价机制的显着差异。重要的是，公司层面的风险因素显着影响崩盘风险，与行业特定的不确定性呈反比关系。另一方面，外部宏观风险因素直接影响这些行业的实际波动。我们的研究见解对包括投资者、基金经理、政策制定者和金融监管机构在内的各个利益相关者具有重大影响。