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The purpose of the paper is to assess the systemic risk in the new energy stock markets of China.

This paper first uses the VaR method to study individual stock market risks. It then introduces the DCC model to capture the dynamic conditional correlation among the new energy stock markets.

The paper shows a generally upward trend of the stock market risk over time in the recent decade. Among all the markets considered, the solar power market demonstrates the highest risk, closely followed by the wind power market, while the hydropower market exhibits the lowest risk. Furthermore, the average dynamic conditional correlations among the new energy markets stay high during the period under investigation though daily correlations vary and significantly declined in 2020.

To the best of the authors’ knowledge, this paper is the first of its kind to study the systemic risk within the new energy stock market context. In addition, it not only investigates individual new energy stock market risks but also examines the dynamic linkages among those markets, thus providing comprehensive and unprecedented evidence of systemic risk in China new energy markets, which have useful implications for both regulators and investors.

The purpose of this paper is to construct an index for systemic risk in China.

This paper develops a systemic risk index for China (SRIC) using textual information from 26 leading newspapers in China. Our index measures the systematic risk from 21 topics relating to China’s economy and provides narratives of the sources of systemic risk.

SRIC effectively predicts changes in GDP, aggregate financing to the real economy and the purchasing managers’ index. Moreover, SRIC explains several other commonly used macroeconomic indicators. Our risk measure provides a helpful monitoring tool for policymakers to manage systemic risk.

The paper construct an index of systemic risk based on the information extracted from newspaper articles. This approach is new to the literature.

The study measures the total systemic risks and connectedness across commodities, stocks, exchange rates and bond markets in Africa during the Covid-19 pandemic.

The study uses the Diebold-Yilmaz spillover and connectedness measures in a generalized VAR framework. The author calculates the net transmitters or receivers of shocks between two assets and visualizes their strength using a network analysis tool.

The study found low systemic risks across all assets and countries. However, we found higher systemic risks in the forex market than in the stock and bond markets, and in South Africa than in other countries. The dynamic analysis found time-varying connectedness return shocks, which increased during the peak periods of the first and second waves of the pandemic. We found both gold and oil as net receivers of shocks. Overall, over half of all assets were net receivers, and others were net transmitters of return shocks. The network connectedness plot shows high net pairwise connectedness from Morocco to South Africa stock market.

The study has implications for policymakers to develop the capacities of local investors and markets to limit portfolio outflows during a crisis.

Previous studies have analyzed spillovers across asset classes in a single country or a single asset across countries. This paper contributes to the literature on network connectedness across assets and countries.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

The first objective is to investigate and determine the social capital development of students in online education. The second objective is to analyze the influence of social capital on students’ academic success and educational satisfaction. The third objective is to generate recommendations to foster social capital development.

A quantitative research approach is employed, with 264 respondents comprising students from colleges and universities in Malaysia. The data gathering instrument is an online questionnaire administered with the informed consent of participants. Data analysis is performed using structural equation modeling (SEM).

The results show that the faculty capital and peer capital components of social capital have not been compromised in online education, but the family capital component has declined. As such, it is concluded that there is a general decline in overall social capital in online education. These findings form the basis for recommendations on promoting social capital development among students in colleges and universities internationally.

This study focused on study periods during the COVID-19 pandemic where online learning and communication were strictly enforced, providing a unique opportunity to explore how students adapted their social capital development. However, this is not meant to be a representation of scenarios where students are given the option of either physical or online education or a combination of both.

Academic and institutional management implications are evident, and recommendations are made based on the findings.

The findings and subsequent recommendations have considerable social implications in terms of social sustainability of education practices and policies.

The COVID-19 pandemic that started in March 2020 and subsequent prolonged periods of physical lockdowns in many countries have forced colleges and universities that customarily practice classroom education to shift to online education temporarily. This situation created a novel “natural experiment” when classes or programs from the same college or university that are customarily conducted in classrooms (in person) were conducted online during the pandemic, thus contributing to the originality of the findings.

This study aims to examine the triple relationship between capital regulation, banking lending and economic growth in a dual markets. Specifically, the author seeks to explore how changes in capital regulation can impact banking lending practices and subsequently influence economic growth, while also investigating the reciprocal effects of banking lending on economic growth.

The author follows several previous studies such as Shrieves and Dahl (1992), Beck and Levine (2002), Altunbas et al. (2007), Saeed et al. (2020) and Stewart et al. (2021) to identify a system of three equations, regarding economic growth, capital and banking financing growth, respectively. The author estimates the parameters of all equations simultaneously using the seemingly unrelated regression method (Zellner, 1962) for a sample of 46 Islamic banks and 113 conventional banks during 2002–2022. These banks operate in 13 Muslim countries from Middle East and North Africa and Southeast Asia.

The author’s findings demonstrate that in the case of Islamic banking, an increase in loan growth stimulates economic growth, while an increasing capital ratio positively influences economic growth but is accompanied by a reduction in loan growth. This result corroborates the findings of Stewart et al. (2021), which indicate that regulatory capital reduces unstable credit while improving gross domestic product growth. However, in the case of conventional banks, the response to an increase in loan growth on Gross Domestic Product Per Capita Growth (GDPCG) is ambiguous, while the capital ratio improves GDPCG and promotes LOANG, which, in turn, increases risk.

The Islamic banks can continue to significantly contribute to economic growth by effectively directing their available capital toward viable investment opportunities and supporting sustainable financial practices, even in the presence of potential constraints on loan growth. As for conventional banks, they are invited to increase their capital levels to ensure a strong and resilient financial system that can support lending and facilitate economic growth.

To the best of the author’s knowledge, this paper is the first to explore the triple relationship between capital requirements, Islamic bank lending and economic growth.

The authors study the effect of an exogenous shock in the form of Coronavirus lockdowns on individual default and on default contagion within the microfinance (MF) sector in India. The authors rely on proprietary data obtained from an MF institution for the period from Nov 2019 to Dec 2020. The authors show that default increased to 95.29% in the month of April 2020, when Covid lockdowns were fully in place. However, borrowers bounced back thereafter, either making full or partial payments, so that defaults had fallen to 5.92% by December 2020. Static features of the group lending model like peer monitoring and joint liability help explain 90% of the monthly deficit during Covid lockdowns among uneducated borrowers. Dynamic features such as contingent renewal help explain why defaults were cured quickly through timely repayments. Finally, there is an absence of default contagion at the district level. Indeed, lagged own default explains 96.6% of variation in individual default, rather than contagion through group, village or district-level defaults. The authors conclude that the MF sector is resilient to exogenous shocks like the pandemic.

The authors use time series panel regressions, as well as cross-sectional regressions.

The authors find that borrower defaults increased significantly to 95.29% during the month of April 2020, when Covid lockdowns were fully in place. However, borrowers bounced back almost immediately, either making full or partial payments, such that defaults had fallen to 5.92% by December 2020. The group lending model does remarkably well in explaining defaults even during Covid lockdowns. Among the majority (92%) of borrowers who are residents of rural districts, the group lending model appears to blunt the impact of the exogenous shock on rates of default. Indeed, panel regressions demonstrate that the group lending model helps explain 90% of the monthly deficit among uneducated borrowers. Logistic regressions indicate that the group lending model is less persuasive among relatively affluent borrowers residing in semi-urban or urban areas who have some formal schooling. Contingent renewal is shown to be an effective disciplining mechanism when a group does default due to the Covid lockdowns. The authors find that groups who defaulted in April 2020 but repaid the outstanding balance within the next two months were more likely to receive subsequent loans from the lender. On the other hand, groups who defaulted in April 2020 and did not repay the outstanding balance until December 2020 did not receive follow-on financing. Finally, the authors find that lagged individual default is the primary source of individual default, rather than contagion through group, village or district-level defaults.

The limitation of the study is that it is confined to a single MF institution in India.

The authors conclude that the social capital that is the foundation of the group lending model succeeds in limiting both the risk and contagion of default from an exogenous shock, such as the Covid pandemic.

To the best of the authors’ knowledge, the authors are the first to examine defaults in the Indian MF sector during the Covid lockdowns in April 2020.

This paper aims to better jointly estimate Value at Risk (VaR) and expected shortfall (ES) by using the joint regression combined forecasting (JRCF) model.

Combining different forecasting models in financial risk measurement can improve their prediction accuracy by integrating the individual models’ information. This paper applies the JRCF model to measure VaR and ES at 5%, 2.5% and 1% probability levels in the Chinese stock market. While ES is not elicitable on its own, the joint elicitability property of VaR and ES is established by the joint consistent scoring functions, which further refines the ES’s backtest. In addition, a variety of backtesting and evaluation methods are used to analyze and compare the alternative risk measurement models.

The empirical results show that the JRCF model outperforms the competing models. Based on the evaluation results of the joint scoring functions, the proposed model obtains the minimum scoring function value compared to the individual forecasting models and the average combined forecasting model overall. Moreover, Murphy diagrams’ results further reveal that this model has consistent comparative advantages among all considered models.

The JRCF model of risk measures is proposed, and the application of the joint scoring functions of VaR and ES is expanded. Additionally, this paper comprehensively backtests and evaluates the competing risk models and examines the characteristics of Chinese financial market risks.

The purpose of this empirical investigation was to explore the interrelationship between psychological capital (PsyCaP) and impostor phenomenon (IP) experienced by entrepreneurs.

The researchers performed exploratory data analysis, using a correlation matrix that included the composite score of all PsyCap dimensions (psychological capital questionnaire [PCQ-24]) and the factor scores of hope, self-efficacy, resilience and optimism. The data analysis was conducted in relation to participants’ IP scores.

The study results demonstrated that a negative relationship was present between entrepreneurs’ Clance impostor phenomenon scale (CIPS) factor scores (consisting of hope, self-efficacy, resilience and optimism) and PsyCap dimensions (PCQ-24) composite subscales. This indicated that higher levels of PsyCaP were associated with lower levels of IP experience by entrepreneurs.

Theoretically, it must be noted that, based upon these study results, both “impostor phenomenon” and entrepreneurial identity formation occurred among entrepreneurs. It was known to be associated with external environmental, situational and societal factors. The researchers established the relationship between entrepreneurs’ “impostor phenomenon” and “psychological capital (PsyCap)”.

Entrepreneurs and executives associated with business accelerators and incubators should comprehend the link between IP and PsyCap in entrepreneurs. This would enhance the well-being of entrepreneurs in their challenging context. Entrepreneurs and executives associated with business accelerators and incubators might explore the effectiveness of PsyCap-based interventions, along with IP-related considerations.

This was one of the first empirical studies investigating and establishing the relationship between entrepreneurs’ “impostor phenomenon” and “psychological capital (PsyCap)”.