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This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.

The study makes use of the Tobias and Brunnermeier (2016) estimator to quantify the systemic risk (ΔCoVaR) that banks contribute to the system. The methodology addresses a classification problem based on the probability that a particular bank will emit high systemic risk or moderate systemic risk. The study applies machine learning models such as logistic regression, random forest (RF), neural networks and gradient boosting machine (GBM) and addresses the issue of imbalanced data sets to investigate bank’s balance sheet features and bank’s stock features which may potentially determine the factors of systemic risk emission.

The study reports that across various performance matrices, the authors find that two specifications are preferred: RF and GBM. The study identifies lag of the estimator of systemic risk, stock beta, stock volatility and return on equity as important features to explain emission of systemic risk.

The findings will help banks and regulators with the key features that can be used to formulate the policy decisions.

This study contributes to the existing literature by suggesting classification algorithms that can be used to model the probability of systemic risk emission in a classification problem setting. Further, the study identifies the features responsible for the likelihood of systemic risk.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.

This study aims to examine the effect of corporate social responsibility (CSR) on banks’ capital, value and risk by investigating its impact on capital inflows and asset quality. The authors aim to investigate the value-protective characteristics of socially responsible performance.

This study uses a two-stage least squares approach with instrumental variables, with bank and year fixed effects to address concerns regarding endogeneity, specifically reverse causality and unobservable factors.

The results confirm a positive association of CSR with capital adequacy, including higher quality Tier 1 Capital. The authors find strong evidence that banks with higher CSR scores are associated with greater bank value and lower risk. The extended analyses find that the improvement in capital is from annual growth in capital and lower risky assets.

The research advances the field by providing new empirical evidence of a positive association between CSR and capital, including high-quality Tier 1 Capital. This study complements the prior research by simultaneously examining the dynamic links between CSR and capital, bank risk and bank value. The findings are consistent with the view that there is a dynamic link in which CSR affects the operations of banks.

The purpose of this paper is to investigate how bank-specific factors affect the riskiness of conventional and Islamic banks in response to shocks in major financial indices as market conditions change.

The authors use a multivariate quantile model using daily equity returns data to analyze financial risk spillovers in the values at risk that may occur between major financial indices and the equity prices of conventional and Islamic banks worldwide. Then, using both quantile and quantile-on-quantile models, the authors examine the effects of bank-specific variables such as leverage ratio, bank size, return on equity and capital adequacy ratio on the initial impact of shocks in major global financial indices on bank equity price returns at different quantiles of shocks and bank-specific variables.

The findings reveal that major financial indices can predict bank stock returns. Moreover, the authors find that the effect of bank-specific factors on the riskiness of banks is heterogeneous in that it depends on the bank type (Islamic vs conventional), the level of banking variable (high vs low) and, more importantly, market conditions.

To the best of the authors’ knowledge, this is the first study that compares the dual banking system with stock market performance while considering bank-specific variables as market conditions change. The results of this study reveal that the effect of bank-specific variables on bank performance varies according to different quantiles of shocks and bank-specific variables. Islamic banks may echo or differ from conventional banks depending on the specific factor under investigation.

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.

This study investigates the influence of corporate income tax on two corporate financial decisions — dividend and capital structure policies, particularly for Shariah compliant companies in Malaysia.

The study considered data from a sample of 529 Malaysian listed companies from four industrial sectors from 2007–2021 (6,746 company-year observations, before eliminating outliers). Panel models such as Fixed Effect and Random effect models were used. The study specifically tested the effect of corporate income tax on dividend and capital structure policies for Shariah compliant companies (3,148 observations) and controlled for industrial sectors.

(1) Firms are mostly Shariah-compliant, less liquid, less profitable and smaller in size, (2) Broadly when analysed together, tax has no impact on debt-equity ratio while it has an impact on dividend per share, (3) However, when tested separately for Shariah compliant companies, the influence of effective tax on capital structure is very evident but not for dividend and (4) influence of industrial sector on the relationship between corporate tax and capital structure and dividend policy is significant. Results indicate that Shariah firms might be raising debt to gain tax advantage. Companies in general pay dividends to avoid reputational damage.

This study assumes that leverage and dividend policy decisions are the main outcomes of the changing tax policies, while it seems that there could be other important outcomes that can be tested in future research. The study also shows the changing tax regimes of different ASEAN countries but they have not been tested to see the differences between countries. It will be indeed interesting for future researchers to focus on this aspect.

The findings contribute to the literature on tax planning of the Shariah-compliant firms, a high growth business segment in the Asian context. The study discussed potential tax-based Islamic market product development.

The purpose of the study is to explore the association of disclosures for the performance of banks in India.

Panel data analysis (utilising static and dynamic models) is applied on the data of 34 Indian banks (for time-frame 2015–2019) to explore the association of disclosures (as transparency and disclosure index) with the performance of banks (as profitability, risk-taking and technical efficiency (TE)). The regulation, competition and ownership concentration variables are taken as control variables.

None of the banks' performance measures applied in the study is significantly associated with the disclosures. This situation implies that disclosures do not impact the performance of the banks in India. The reason is that disclosures and performance are two different activities that aim at different purposes.

This study does not provide output for the association between disclosures and the value of the banks and confines itself to explore the association between disclosures and performance of the banks only. This limitation can be the future scope of the study.

There is no other study that solely focuses on exploring the association of disclosures with the performance of the banks. Disclosure has more significant importance in banks because of the inherent nature of opaqueness in banking operations. Therefore, the current study's findings have substantial implications for policymakers, managers and investors of the banks.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

The purpose of this paper is to assess the effects of prompt corrective action on bank risk and returns in an empirical framework.

The paper uses a difference-in-difference specification to analyse whether and how PCA affects bank risk and returns. As part of robustness, the analysis also uses a fixed effects specification with Driscoll–Kraay standard errors to account for serial correlation and cross-sectional dependence.

The findings reveal that banks under PCA framework contribute less to systemic risk and exhibit higher market valuation. These findings differ across recapitalised versus non-recapitalised banks and for banks with differing asset quality, capital and profitability. The overall price impact is a decline in lending rates and deposit costs.

To the best of the author’s understanding, this is one of the early studies in the Indian context to carefully examine the linkage between PCA and bank behaviour.

This paper sheds light on the impact of market risk measures on systemic risk. Market risk, which is captured by the volatility of stock market returns, is also decomposed into systematic and idiosyncratic risks.

The author uses the five-factor asset pricing model and systemic risk methodologies to derive market and systemic risk measures, respectively. Using a sample of 2,667 US banks for over 30 years and employing panel data estimation techniques, the author tests the said relationship.

It is shown that idiosyncratic risk can surge systemic risk, while systematic risk plays a less important role. Results survive a battery of tests, including different systemic risk measures, controlling causality and interacting with bank size, market fear and crisis periods.

These findings call for regulatory intervention, especially for large banks with high idiosyncratic risk.

This is the first paper that provides a more granular picture of the relationship between market and systemic risk from the US banking industry for more than 30 years.