Double Asymmetric Impacts, Dynamic Correlations, and Risk Management Amidst Market Risks: A Comparative Study between the US and China

Abstract

Extreme shocks, including climate change, economic sanctions, geopolitical conflicts, etc., are significant and complex issues currently confronting the global world. From the US–China perspective, this paper employs the DCC-DAGM model to investigate how diverse market risks asymmetrically affect return volatility, and extract correlations between stock indices and hedging assets. Then, diversified and hedging portfolios, constructed by optimal weight and hedge ratio, are investigated using multiple risk reduction measures. The empirical results highlight that, first, diverse risks exhibit an asymmetric effect on the return volatility in the long term, while in the short term, the US stock market is more sensitive to negative return shocks than the Chinese market. Second, risks impact correlations differently across time horizons and countries. Short-term correlations are stronger than long-term ones for the US market, with the Chinese stock market displaying more stable correlations. Third, the hedging strategy is more effective in reducing volatility and risk for US stocks, while the diversification strategy proves more effective for Chinese stocks. These findings have implications for market participants striving to make their portfolios robust during turbulent times.

Can ESG Integration Enhance the Stability of Disruptive Technology Stock Investments? Evidence from Copula-Based Approaches

“…The literature identifies two primary approaches for investigating financial market dependence: (1) multivariate GARCH models like DCC (Ding et al 2022;Dong et al 2023;Yu et al 2024) or BEKK (Ashfaq et al 2023), and (2) copula theory, noted for its ability, as highlighted by Ning (2010), to detect nonlinear and asymmetric dependencies. Traditional correlation-based approaches are criticized for their limited performance in capturing complex dependence dynamics.…”