Are the stylized features of stock returns the same in market downturns and upturns?

IF 2.4 2区 经济学 Q2 BUSINESS, FINANCE
Journal of Empirical Finance Pub Date : 2026-06-01 Epub Date: 2026-02-02 DOI:10.1016/j.jempfin.2026.101695
Bowen Cheng , Wanling Huang , Cathy Ning , Dinghai Xu
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引用次数: 0

Abstract

This study investigates key features of stock returns – including the leverage effect, contemporaneous leverage effect, volatility clustering, and feedback effect – using a vine copula framework. Unlike traditional copula models, our approach enables the joint examination of these features simultaneously, particularly under extreme market conditions when they are most critical for risk management. Based on high-frequency data from major global stock markets and large-cap U.S. firms, we find strong evidence of volatility clustering, characterized by nonlinearity and marked asymmetry: the clusters of high volatility occur more frequently than those of low volatility, with the effect more pronounced for indices than for individual firms. We also identify significant asymmetric leverage and contemporaneous leverage effects, both of which occur only at market downturn. At extremes, the contemporaneous leverage effect is slightly stronger than the leverage effect, suggesting both immediate and persistent volatility responses to adverse news. Moreover, these stylized features intensified during the 2008 financial crisis and the COVID-19 pandemic. Our Value at Risk (VaR) analysis and backtesting further demonstrate the superior performance of the vine copula model relative to linear dependence models and pair copula alternatives. These findings provide important insights for enhancing risk management practices and improving option pricing.
股票收益的风格化特征在市场下跌和上涨时是相同的吗?
本文采用藤copula框架研究股票收益的关键特征,包括杠杆效应、同期杠杆效应、波动聚类和反馈效应。与传统的联结模型不同,我们的方法可以同时对这些特征进行联合检查,特别是在极端市场条件下,当它们对风险管理最关键的时候。基于来自全球主要股票市场和美国大盘股公司的高频数据,我们发现了波动率聚类的有力证据,其特征是非线性和明显的不对称:高波动率的聚类比低波动率的聚类发生得更频繁,对指数的影响比对单个公司的影响更明显。我们还发现了显著的不对称杠杆和同期杠杆效应,这两种效应都只发生在市场低迷时期。在极端情况下,同期杠杆效应略强于杠杆效应,表明对不利消息的即时和持续波动都有反应。此外,在2008年金融危机和2019冠状病毒病大流行期间,这些程式化特征进一步加剧。我们的风险值(VaR)分析和回溯测试进一步证明了藤联结模型相对于线性依赖模型和对联结模型的优越性。这些发现为加强风险管理实践和改进期权定价提供了重要的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.40
自引率
3.80%
发文量
59
期刊介绍: The Journal of Empirical Finance is a financial economics journal whose aim is to publish high quality articles in empirical finance. Empirical finance is interpreted broadly to include any type of empirical work in financial economics, financial econometrics, and also theoretical work with clear empirical implications, even when there is no empirical analysis. The Journal welcomes articles in all fields of finance, such as asset pricing, corporate finance, financial econometrics, banking, international finance, microstructure, behavioural finance, etc. The Editorial Team is willing to take risks on innovative research, controversial papers, and unusual approaches. We are also particularly interested in work produced by young scholars. The composition of the editorial board reflects such goals.
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