Deciphering asymmetric spillovers in US industries: Insights from higher-order moments

Abstract

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.