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.
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