This study aims to investigate the impact of a wide range of economic and non-economic events on stock market spillover effects in a group of 16 major developed and emerging countries over the 2000–2020 period. We analyse the size and structure of contagion to verify how different events spread contagion across borders and sectors. We applied the methodology proposed by Diebold and Yilmaz (2009, 2012, 2014) to a wide range of stock market indices using a quantile regression framework. Our findings show that the sectoral and country-specific indices usually range below the overall market contagion levels, while their density functions differ structurally from those of overall market contagion. Among non-economic events, viruses – notably, the COVID-19 pandemic – are the most widespread sources of contagion, while terrorism events affect the widest range of sectors with the greatest magnitude. Among economic events, the strongest negative impact is found for prudential ones. Quantitative easing (QE) and liquidity support reduce overall market contagion, while QE unwinding has a more substantial role than its introduction or expansion, exemplifying its asymmetric impact. We also investigate how investors may benefit from using contagion information in developing trading strategies, highlighting the positive impact of spillover-based weightings on portfolio returns.

本研究旨在调查 2000 年至 2020 年期间一系列 16 个主要发达国家和新兴国家的广泛经济和非经济事件对股市溢出效应的影响。我们分析了传染的规模和结构，以验证不同事件如何跨越国界和部门传播传染。我们使用分位数回归框架将 Diebold 和 Yilmaz（2009、2012、2014）提出的方法应用于广泛的股票市场指数。我们的研究结果表明，部门和国家特定指数的范围通常低于整体市场传染水平，而它们的密度函数在结构上不同于整体市场传染的密度函数。在非经济事件中，病毒——尤其是 COVID-19 大流行——是最广泛的传染源，而恐怖主义事件影响范围最广、影响最大的部门。在经济事件中，审慎事件的负面影响最大。量化宽松 (QE) 和流动性支持降低了整体市场的传染性，而退出量化宽松的作用比其引入或扩张更为重要，体现了其不对称影响。我们还调查了投资者如何从使用传染性信息制定交易策略中受益，强调基于溢出的权重对投资组合回报的积极影响。举例说明其不对称的影响。我们还调查了投资者如何从使用传染性信息制定交易策略中受益，强调基于溢出的权重对投资组合回报的积极影响。举例说明其不对称的影响。我们还调查了投资者如何从使用传染性信息制定交易策略中受益，强调基于溢出的权重对投资组合回报的积极影响。