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This study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.

The authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.

The empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.

The results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.

The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

The purpose of this paper is to investigate investor herding behaviour and the effect of presidential elections on investor herding behaviour in African stock markets at the sector level.

The study segregates listed firms into financial, consumer goods, consumer services and basic materials sectors and uses the cross-sectional absolute deviation approach as a metric of detecting herding in each of the sectors. The authors extend the model to tease out the effect of presidential elections on investor herding behaviour.

The study reveals that sectoral differences are fundamental to the evolution of herding. Herding is prominent in a financial services sector dominated by banks. The phenomenon also prevails in markets with smaller consumer goods and services sectors. A post-presidential election effect on investor herding is found for the consumer goods and services sectors of Ghana and a pre-presidential election effect is documented in Nigeria's consumer services sector. The authors conclude that post-presidential election effect is as a result of political connections whilst a pre-presidential election effect is attributable to political business cycles.

The study is based on four African countries due to data constraints. Nonetheless, the study is the first in Africa to the best of the authors' knowledge, and the results are very solid and have a lot of practical and policy implications.

The study has implications for investors as it guides investment behaviour in pre- and post-presidential election periods.

Past studies on investor herding behaviour in African stock markets have largely concentrated on the aggregate market. Knowledge on sectoral differences in investor herding is almost non-existent for African stock markets. Furthermore, premised on the fact that stock markets react to presidential elections, there is no known study that have attempted to examine the effect of presidential elections on investor herding behaviour. This paper contributes to the literature by providing evidence on sectoral differences in investor herding behaviour and the effect of presidential elections on sectoral herding behaviour.

This paper examines the extreme dependence and asymmetric risk spillovers between crude oil futures and ten US stock sector indices (consumer discretionary, consumer staples, energy, financials, health care, industrials, information technology, materials, telecommunication and utilities) before and during COVID-19 outbreak. This study is based on the rationale that stock sectors exhibit heterogeneity in their response to oil prices depending on whether they are classified as oil-intensive or non-oil-intensive sectors and the possible time variation in the dependence and risk spillover effects.

The authors employ static and dynamic symmetric and asymmetric copula models as well as Conditional Value at Risk (VaR) (CoVaR). Finally, they use robustness tests to validate their results.

Before the COVID-19 pandemic, crude oil returns showed an asymmetric tail dependence with all stock sector returns, except health care and industrials (materials), where an average (symmetric tail) dependence is identified. During the COVID-19 pandemic, crude oil returns exhibit a lower tail dependency with the returns of all stock sectors, except financials and consumer discretionary. Furthermore, there is evidence of downside and upside risk asymmetric spillovers from crude oil to stock sectors and vice versa. Finally, the risk spillovers from stock sectors to crude oil are higher than those from crude oil to stock sectors, and they significantly increase during the pandemic.

There is heterogeneity in the linkages and the asymmetric bidirectional systemic risk between crude oil and US economic sectors during bearish and bullish market conditions; this study is the first to investigate the average and extreme tail dependence and asymmetric spillovers between crude oil and US stock sectors.

This study examines the risk spillovers between Indonesian sectorial stocks (Energy, Basic Materials, Industrials, Consumer Cyclicals, Consumer Non-cyclical and Financials), the aggregate index (IDX) and two commodities (gold and West Texas Intermediate Crude Oil [WTI] futures).

The study uses two methodologies: the TVP-VAR model of Antonakakis and Gabauer (2017) and the quantile connectedness approach of Ando et al. (2022). The data cover the period from October 04, 2010, to April 5, 2022.

The results show that the IDX, industrials and materials are net transmitters, while the financials, consumer noncyclical and energy sectors are the dominant shock receivers. Using the quantile connectedness approach, the role of each sector is heterogeneous and asymmetric, and the return spillover is stronger at lower and higher quantiles. Furthermore, the portfolio hedging results show that oil offers more diversification gains than gold, and hedging oil is more effective during the pandemic.

This study provides valuable insights for investors to diversify their portfolios and for policymakers to develop policies, regulations and risk management tools to promote stability in the Indonesian stock market. The results can inform the design of market regulations and the development of risk management tools to ensure the stability and resilience of the market.

This study is the first to examine the spillovers between commodities and Indonesian sectors, recognizing the presence of heterogeneity in the relationship under different market conditions. It provides important portfolio diversification insights for equity investors interested in the Indonesian stock market and policymakers.

This study attempts to examine the relationship between the banking sector and stock market development in India.

To analyze the relationship between banks and stock market development, the ratio of stock market capitalization to GDP is proxied by stock market development. The determinants of the stock market development are used for analysis namely domestic credit to the private sector as a ratio of GDP is used as a proxy for the development of banks, saving rate, per capita real GDP, and inflation. The autoregressive distributed lag (ARDL)-Bounds testing approach is used for the analysis. The paper also used the unrestricted error correction model and CUSUM and CUSUM square test to check the stability of the model.

The ARDL bounds test found that there is a long-run relationship between stock market development and bank-centered financial development. The results also revealed that the stock market is positively influenced by the development of banks, savings, and per capita real GDP in the short-run as well as long-run.

This paper suggests that improvement of banking sector plays an important role to increase liquidity of the capital market development in India. This paper also suggests that the economic growth and savings rate have positive impact to induce the capital market growth in both short run and long run.

The study has investigated the empirical relationship between the banking sector and the stock market development in a different methodological approach by using an ARDL model which is appropriate for a small sample size. There are few studies related to bank-centered financial development and stock market development in the context of India.

Stock market performance is paramount to every country, as it signifies economic growth, business performance, wealth maximization, savings deployment and consumer confidence. This study investigates the disparities in the market performance of listed firms in Romania. This study also examines whether the COVID-19 crisis affected market performance.

The data were collected from 69 firms listed on the Bucharest Stock Exchange (BSE) from 2018 to 2022, belonging to 11 sectors. This study used several methods to achieve its objectives. Difference tests were considered to analyze the performance of Romanian companies before and during the COVID-19 crisis, as well as across sectors. Regression analysis was also conducted to estimate the effect of the COVID-19 crisis and classification type on Romanian companies' performance. Additional analyses were performed to verify the findings of the present study.

The study’s findings indicate a clear difference in market performance between the pre-crisis and crisis periods. The COVID-19 pandemic had an adverse and significant impact on market performance. However, after the market contraction in the early stage of the COVID-19 pandemic outbreak, the stock market outperformed the pre-pandemic capitalization levels and the regional and global indices evolution. Furthermore, there was a difference in market performance across sectors. In particular, the communication services sector has specifically demonstrated accelerated growth.

This research examines the variation in the market performance of companies before and during the COVID-19 pandemic and across different sectors. It also provides evidence of the potential impact of COVID-19 on firms' market performance. This research contributes to a better understanding of how sectors perform during times of crisis.

This study examines the extreme quantile connectedness and spillovers between West Texas Intermediate (WTI) crude oil futures and ten Vietnamese stock market sectors. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors employ the extreme quantile connectedness methodology of Ando et al. (2022).

Initial results show that the size of spillovers is higher during bearish markets than bullish markets and under major financial, political, energy and pandemic events. The oil market is a net receiver of spillovers during downward markets and net contributors during upward markets. The banking sector is a net contributor of spillovers, whereas consumer discretionary and consumer staples are net receivers for different quantiles. The role of the remaining sectors as net receivers/contributors is sensitive to the quantiles. Oil has a large spillover effect on the electricity sector for all quantiles. Comparing all crises, oil offers the best hedging effectiveness to the Vietnamese sector during the coronavirus disease 2019 (COVID-19) crisis. Moreover, oil was a cheap hedge asset during oil crises. Finally, oil provides the highest hedging effectiveness for healthcare during the global financial crisis (GFC) and consumer staples during the European debt crisis (EDC), oil crisis and COVID-19.

Acknowledging the presence of heterogeneity in the relation between oil and economic sectors under different market conditions, this study is the first to examine the extreme quantile connectedness between oil and Vietnamese sectors.

The purpose of this study is to examine the impacts of the Glasgow Climate Pact on global oil and gas sector stocks. Further, this study also examines if the nations' Climate Change Performance Index (CCPI) and World Energy Trilemma Index (WETI) drive the abnormal returns around the event.

The authors apply the event study analysis to 691 global oil and gas firms across 52 countries. Further, they apply the cross-sectional examination of cumulative abnormal returns (CARs) across 502 firms.

The emerging markets experienced significant negative abnormal returns on the event day. The CCPI negatively affects longer pre-event CARs, while WETI significantly negatively associates with CARs during longer pre- and post-event windows. Volatility is negatively related to pre- and post-event abnormal returns, while past returns positively drive pre-event period CARs but negatively drive post-event window CARs. This study finds an interesting association between liquidity (CACL) and CARs, as CACL positively drives pre-event CARs, but post-event CARs are negatively associated with CACL. The CARs do not significantly correlate with leverage, size and book-to-market ratio.

This study's findings on the impact of climate risks on financial markets have significant implications for global regulatory bodies. Policymakers should reduce stock volatility and enhance environmental disclosures by publicly traded companies to accurately price and assess the potential impacts of climate risks. Governments should examine the effects of environmental restrictions on investor behavior, especially in developing countries with limited access to capital. Therefore, policymakers need to consider the far-reaching impacts of environmental regulations while introducing them.

Climate risks are expected to impact the global financial market significantly. Prior studies provide limited evidence on how such climate pacts impact the oil and gas sector. Hence, this study, while bridging this gap, provides important implications for policymakers and stakeholders, particularly the emerging markets that are more sensitive.

This research empirically investigates the evidence of the financial development and economic growth nexus in sub-Saharan Africa from 1995 to 2022.

A series of preliminary tests are conducted before using the two-stage estimated generalized least squares and robust least squares methods for the analysis. Two indices are constructed to measure financial development: one for the banking sector indicators and another for the market-based indicators (Ustarz and Fanta, 2021).

The results indicate that the banking sector index significantly impacts the gross domestic product (GDP) per capita positively. The market sector index has a negatively significant effect on the GDP per capita. Government expenditure has a positive impact on the GDP per capita.

Policymakers in sub-Saharan Africa should improve and implement finance–growth inclusive strategies that promote financial reforms and development to efficiently impact all population sectors. Policymakers should take stringent measures to ensure that the banking sector's development is sustainable to lead economic growth. The governments should strategize and promote capital market development using favorable listing rules for companies in the stock markets. Global stock market integration should be encouraged to diversify risks, increase public awareness, raise investors' confidence level and reduce stock market impediments like high taxes and regulatory barriers.

Previous study findings on the financial development and economic growth nexus are inconclusive and debatable. This study employs the financial development index approach.