Introduction
The structure of the stock market is a crucial aspect for listed firms, particularly during times of stock market volatility. This article examines the relationship between stock market volatility and capital structure decisions, focusing on the Shanghai Stock Exchange. Additionally, it explores the impact of COVID-19 on global stock markets and analyzes risk spillovers in the context of foreign exchange rates and stock markets. Furthermore, it investigates the system risk in the oil and G20 stock markets through a multilayer information spillover network. The article concludes with an exploration of the price discovery and risk spillover effects of CSI 300 index futures on the Chinese stock market.
Stock Market Volatility and Capital Structure Decisions
Listed firms’ capital structure decisions are directly impacted by stock market volatility. Shanghai Stock Exchange panel data (2008-2018) demonstrates that volatility immediately boosts total and short-term market leverage, but hampers long-term leverage. To counter volatility, Chinese firms increase bank debts and decrease trade credit, as confirmed by robust tests, establishing a connection between emerging markets, stock market volatility, and capital structure choices.
The Impact of COVID-19 on Global Stock Markets
COVID-19 has had a significant impact on global stock markets, with the effects evolving over time. Dynamic network analysis approaches are employed to evaluate the changing co-movements among stock market indices during the pandemic. It is observed that on the 100th day from the reporting of the first cluster of cases, the co-movement among stock markets becomes 100% positively correlated. Despite this correlation, international investors can still achieve better portfolio performance by managing risk or pursuing profits. The importance of authoritative nodes in the network changes multiple times with the shift of epicenters. The COVID-19 crisis leads to substantial clustering and a less stable network structure in global stock markets.
Risk Spillovers between Foreign Exchange Rates and Stock Markets
We propose a GARCH copula quantile regression (CQR) model to examine risk spillovers between foreign exchange rates (FX) and stock markets. Involving ten economies, our study reveals that the 90- and 270-degree rotated Gumbel copula best captures the upside and downside tail dependence structures between FX and stock markets. Brazilian and Russian markets demonstrate the largest upside and downside risk spillovers, respectively. Notably, downside spillovers surpass upside spillovers, reflecting the flight-to-quality trend. These findings hold significance for portfolio managers and international supervisory authorities.
Multilayer Information Spillover Network in the Oil and G20 Stock Markets
We construct a multilayer information spillover network to analyze system risk in the oil and G20 stock markets. The network consists of return, volatility, and extreme risk spillover layers. At the system level, the volatility spillover layer dominates risk transmission. During crises, inter-layer spillover intensifies, aiding early risk detection. Developed markets emit more risk, while developing markets receive it. Homogeneous economic structures are susceptible to shocks. In the Chinese stock market, we focus on the CSI 300 index futures’ impact on volatility. Our study reveals a two-way linear mechanism between the spot and futures markets, influencing volatility. Additionally, a nonlinear guiding relationship exists between these markets, emphasizing the role of futures in price movements and volatility.
Our study addresses the gap by focusing on the impact of CSI 300 index futures on Chinese stock market volatility. Using daily closing prices from 2005 to 2021, we examine price discovery and risk spillover effects.
The findings reveal a two-way linear mechanism of volatility spillover between CSI 300 index spot and futures markets. Changes in futures market significantly impact spot market volatility and vice versa. We also observe a two-way guiding relationship in the nonlinear mechanism between these markets, indicating the crucial role of CSI 300 index futures in influencing price movements and volatility.
Introduction of stock index futures in the Chinese
The introduction of stock index futures in the Chinese market has brought about several advantages, such as improved market structure and enhanced pricing efficiency. It has also provided investors with opportunities for hedging, speculation, and arbitrage. However, the presence of stock index futures also poses risks to the stability of the stock market.
Numerous studies have explored the impact of stock index futures on stock market volatility in different markets worldwide. Hasbrouck (2003) found that futures play a leading role in price formation in the S&P 500 and NASDAQ 100 markets. Bohl et al. (2011) examined the price transmission relationship between the spot and futures markets under various investor structures and highlighted the increasing correlation between the two markets when institutional investors are involved. Hou and Li (2013) and Wang et al. (2017) provided evidence of the price guiding role of stock index futures in the Chinese market. Ahn et al. (2019) discovered that even after the implementation of trading restrictions, stock index futures still dominate in price discovery.
Relationship between stock index futures and stock market volatility
The literature has debated the relationship between stock index futures and stock market volatility. Some studies suggest that stock index futures increase volatility due to speculation (Harris, 1989; Bae et al., 2004). However, others argue that futures enhance efficiency and reduce volatility (Adnan & Kasman, 2008). Additionally, some research finds no deterministic impact (Antoniou et al., 1998; Bohl et al., 2015).
Our study adds to the literature by empirically examining the price discovery and risk spillover effects of the CSI 300 index futures in the Chinese stock market. We discover a bidirectional relationship between the spot and futures markets, where changes in one market affect the volatility of the other.
Understanding the dynamics between stock index futures and stock market volatility is crucial for market participants, regulators, and policymakers. The insights gained from this study can help investors make informed decisions and manage their risks more effectively. Regulators can also use these findings to assess the impact of stock index futures on market stability and develop appropriate measures to mitigate potential risks.
Conclusion
In conclusion, our study contributes to the understanding of the structure of the stock market, specifically focusing on the impact of stock market volatility, capital structure decisions, the impact of COVID-19, risk spillovers, and the multilayer information spillover network. By analyzing panel data from the Shanghai Stock Exchange, we observe that stock market volatility has stabalized.