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This paper investigates co-movements among the Chinese stock market, Shanghai International Energy Exchange (INE) crude oil futures and West Texas Intermediate (WTI) crude oil futures. We use Copula models to capture tail dependencies and employ the VAR-BEKK-GARCH model to examine the direction of volatility spillovers. We find that there are positively time-varying dependency relationships among the three markets. Compared with the corresponding upper-tail dependencies, the lower-tail dependencies were larger before the COVID-19 pandemic while relatively weaker after the breakout of the pandemic. Before the COVID-19 pandemic, there was only a statistically significant volatility spillover from WTI crude oil future market to the INE crude oil future market. After the breakout of the COVID-19 pandemic, there were statistically significant volatility spillovers in the two pairs of markets, namely, the WTI–INE and Chinese stock–WTI. However, we only find statistically significant evidence of unidirectional volatility spillover from the Chinese crude oil future market to the Chinese stock market during the pandemic.

We investigate the impact of the global economic policy uncertainty (GEPU) on stock volatility for nine emerging economies (Brazil, Russia, India, China, South Africa, Mexico, Indonesia, South Korea, and Turkey). We employ an expanded GARCH-MIDAS approach to connect low-frequency GEPU data and high-frequency stock data, assuming that GEPU affects stock volatility via the long-run component of total volatility. We not only use DM and SPA tests to statically evaluate the out-of-sample forecasting ability of the extended model, taking traditional GARCH model and GARCH-MIDAS model as benchmarks, but also use the Fluctuation test to examine the time-varyingly relative forecasting performance in the presence of potential instability. From the in-sample estimation results, we find that GEPU has empirically significant impact on stock volatility for the nine emerging economies. The out-of-sample forecasting results show that the GEPU-based model can improve forecasting performance of stock volatility for emerging markets, especially in unstable environments.

Proposing a new scoring method to evaluate the environmental, social, and corporate governance (ESG) performance of Chinese A-share listed companies over the period 2010–2019, this study investigates the impact of ESG on firm value, by taking Tobin’s Q, Return on Assets (ROA) and Market-to-Book ratio (MB) as proxy variables for firm value. We find a significantly positive relationship between ESG composite performance and firm value, which supports the stakeholder theory. This result can hold when we carry out robustness checks, i.e., changing dependent variable, instrument variable (IV) regression, and Heckman’s two-stage estimation. When an existing social responsibility rating (Hexun’s CSR scores) is taken as the proxy of ESG performance, the main conclusion also keeps in line. For the three sub-dimensions, the positive impact of environmental (E) and social (S) performance on firm value can hold, while that of corporate governance (G) cannot pass all the robustness tests. In terms of heterogeneity, there is evidence that the enhancement effect of ESG on firm value for state-owned companies is stronger than that for non-state-owned companies. Besides, the enhancement effect is significant for the non-key pollution-monitored firms but insignificant for the key pollution-monitored firms.

In this study, we constructed two pandemic anxiety indexes based on an assumption that people's emotions fluctuate with the COVID-19 reported cases and deaths, to examine the dynamic co-movements between these anxiety indexes and the stock markets in the BRICS and G7 countries. We found that the anxiety indexes are volatile over time but have an overall downtown trend. The correlations between stock market returns and the epidemic anxiety indexes are time varying. We found a common feature across the countries studied, namely that the correlation becomes weaker and has smaller fluctuations after the announcement of the mRNA-based COVID-19 vaccine.