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Proponents of Islamic banking believe that this banking model is relatively superior in times of financial crises. This study aims to examine whether Islamic banks were more resilient to the coronavirus 2019 (COVID-19) pandemic than their conventional peers, especially in terms of two of the most important banking risks, capital and liquidity risks.

The authors use a regression model to examine whether Islamic banks were more resilient to the recent health crisis, as compared to their conventional counterparts. The results are robust to alternative crisis time periods, the use of different model specifications and the inclusion of different control variables.

Unlike during the 2007–2008 global financial crisis (GFC), Islamic banks have not performed relatively well during the more recent crisis caused by the COVID-19 pandemic. The results show that Islamic banks experienced an increase in both capital and liquidity risks. The results also indicate a decrease in bank profitability, improved solvency and asset quality and a decrease in operational risk.

This study contributes to the literature on banking business model and resilience to economic crises. Contrary to some expectations and to their performance during the GFC of 2007–2008, Islamic banks were found to be more vulnerable during the COVID-19 pandemic than conventional banks.

This study aims to identify mutually exclusive risk categories and determine whether these categories effectively capture the potential impact of risk disclosures on the initial returns of initial public offerings (IPOs) in the financial and non-financial sectors.

Data were collected from 131 Indian IPO prospectuses (104 non-financial and 27 financial) issued between 2015 and 2021. Content analysis was performed to identify mutually exclusive risk categories, and the effects of these categories on initial IPO returns were assessed by regression analysis

The findings revealed that risk factor disclosures have a significant impact on underpricing, but not all risk factors are relevant. In the current study, in the financial sector, IPO underpricing was mostly driven by technological and competitive risk factors. In the non-financial sector, underpricing was predominantly influenced by operating risk and compliance risk factors.

The limitations of this study include the use of sentence-based context analysis, which does not assess the quality of risk disclosures. The statistical data reduction technique used to generate mutually exclusive risk categories may also be a limitation.

This research has the potential to assist companies in standardizing the disclosure of risks within IPO prospectuses. The insights gained can inform market regulators in designing policies aimed at aiding investors in formulating investment strategies, ultimately enhancing transparency and clarity regarding information disclosure. Moreover, the findings offer valuable guidance to investors in selecting IPOs aligned with their risk tolerance levels.

From a societal perspective, this study represents advancements by guiding regulators towards developing and regulating standardized, mutually exclusive risk factors. Such measures can aid investors in enhancing their decision-making perspectives regarding IPOs, promoting a more informed and confident investment environment.

This study is a pioneering attempt to address knowledge gaps by identifying distinct categories of risk disclosures in IPO prospectuses and examining their potential influence on IPO underpricing in the financial and non-financial sectors in India.

This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events, namely the subprime crisis of 2008, the political and social instability of 2011 and the COVID-19 pandemic.

Over the period 2004–2020, a log-periodic power law model (LPPL) has been employed which describes the price dynamics preceding the beginning dates of the crisis. In order to adjust the LPPL model, the Global Search algorithm was developed using the “fmincon” function.

By minimizing the sum of square errors between the observed logarithmic indices and the LPPL predicted values, the authors find that the estimated parameters satisfy all the constraints imposed in the literature. Moreover, the adjustment line of the LPPL models to the logarithms of the indices closely corresponds to the observed trend of the logarithms of the indices, which was overall bullish before the crashes. The most predicted dates correspond to the start dates of the stock market crashes identified by the CMAX approach. Therefore, the forecasted stock market crashes are the results of the bursting of speculative bubbles and, consequently, of the price deviation from their fundamental values.

The adoption of the LPPL model might be very beneficial for financial market participants in reducing their financial crash risk exposure and managing their equity portfolio risk.

This study differs from previous research in several ways. First of all, to the best of the authors' knowledge, the authors' paper is among the first to show stock market crises detection and prediction, specifically in African countries, since they generate recessionary economic and social dynamics on a large extent and on multiple regional and global scales. Second, in this manuscript, the authors employ the LPPL model, which can expect the most probable day of the beginning of the crash by analyzing excessive stock price volatility.

This study aims to examine the effect of CEO compensation risk, as measured by the proportion of equity-based pay (option and stock awards) relative to total compensation and pay sensitivity to stock volatility, on CEO pay for luck asymmetry. This paper also empirically examines CEO compensation risk as a mediating variable between the regulatory changes and CEO pay for luck asymmetry.

This paper test the proposed two hypothesis that CEO compensation risk is positively associated with the degree of CEO pay for luck asymmetry; and the pay related regulations implemented around 2006 could mitigate the degree of CEO pay for luck asymmetry using the fixed-effects regression models.

Consistent with the managerial talent retention hypothesis, this paper finds that CEO compensation risk, as measured by the equity-based pay as a proportion of CEO total compensation and CEO pay sensitivity to stock volatility, is positively associated with the degree of CEO pay for luck asymmetry. In addition, this paper find that CEO pay for luck asymmetry is significantly reduced by the major regulatory changes on executive compensation implemented around 2006.

This study is among the very few studies exploring the impact of CEO compensation risk on pay for luck asymmetry in the literature. While the major purpose of the widely used stock options is to align executive interests and shareholder values, it also tends to increase the risk level of CEO compensation. So, a well-designed CEO pay package should protect risk-averse CEOs from bad luck for the retention purpose, which is also beneficial to shareholder wealth maximization. Therefore, future research on executive compensation needs to examine the issue from various perspectives.

For board of directors who is responsible for the compensation of CEOs, it is necessary to consider a broad range of factors when designing an optimal CEO pay package.

The findings on the impact of regulations on CEO pay for luck asymmetry suggest that the executive-pay-related regulations around 2006 have indeed achieved some of their intended goals to significantly lower pay for nonperformance asymmetry, whereby CEO pay sensitivity to stock volatility has been identified as a major mediating variable.

This study contributes to the literature on executive pay for luck asymmetry in several perspectives. First, this paper finds that CEO compensation risk has a positive impact on the degree of CEO pay for luck asymmetry. Second, this paper finds that the CEO pay for luck asymmetry has been mitigated after 2006 when various regulatory changes on executive compensation began to be implemented in the USA. To the best of the authors’ knowledge, this study is among the very few studies investigating these issues in the literature.

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

This paper aims to investigate the impact of quality loss in transit on e-commerce supply chain pricing, production and financing decisions.

The authors consider a Stackelberg game model with a supplier, logistics firm and e-commerce platform. The logistics firm is capital-constrained and obtains funding from the e-commerce platform by debt financing or equity financing. Through backward induction, this paper first solves the equilibrium results under the two financing schemes and then reveals the financing preferences of all parties.

The results demonstrate that equity financing reduces financing costs and promotes production significantly. However, it may also lead to overproduction, particularly in markets with poor profitability and high cost factors. When the percentage of product quality loss is large, equity financing is preferable. With the increasing of transportation level, the benefits of debt finance are steadily growing. In addition, equity financing is the Pareto dominant scheme for all firms under certain circumstances. The extensions consider hybrid financing and another quality loss type.

The paper derives the equilibrium solutions and financing preferences, then specifies the threshold for applying financing schemes. Provide guidance for logistics firms’ finance model innovation and core enterprise involvement in the logistics industry.

The paper investigates how logistics firms’ financing strategies are impacted by product quality loss.

The authors examine the role of stock liquidity in CEO equity compensation design. For a sample of publicly traded firms from 2007 to 2020, the authors find that greater stock liquidity is associated with a higher proportion of stock awards relative to the proportion of options in CEO equity compensation. The results of this study suggest that stock price informativeness on the grant date has a differential effect on the preference for the type of equity compensation awarded to CEOs. The empirical results are supported by multivariate analyses using alternative measures of stock liquidity and a two-stage least squares (2SLS) specification that alleviates endogeneity concerns. Furthermore, the authors document that the firm-specific increase in the proportion of stock awards compared to the proportion of stock options is associated with a firm-specific increase in stock liquidity. Collectively, the analyses suggest that stock liquidity as a measure of stock price informativeness contributes to the choice of CEO equity compensation design.

The objective of the study is to shed light on the notion of quality investing in the Indian stock market. The study also attempts to combine the value and quality metrics to test their ability to generate a higher risk-adjusted return.

The paper employs asset pricing models to examine the excess risk-adjusted returns and panel regression model (random estimates) to determine the price of quality in the cross-section of Bombay Stock Exchange (BSE) listed stocks from 2003 to 2020.

The results indicate that the quality-only strategy failed to produce substantial risk-adjusted returns in the Indian stock market. The returns to long/short hedging strategy quality-minus-junk (QMJ) are significantly positive with the majority of the returns attributable to the short leg of the stock portfolio. The findings further discovered that the explanatory effect of quality on prices is limited. In particular, a strategy that combines value and quality investing generated positive and significant alphas as well as a higher Sharpe ratio.

The study provides investors and portfolio managers with valuable insights for navigating undervalued high-quality equities in the Indian stock market.

This is the first research of its kind to examine the performance of quality (Q score indicator) combined with value investing in the Indian stock market. As majority of research have concentrated on developed economies, this study offers out-of-sample evidence to validate the strategy’s success in an emerging market.

With the rise of mandating climate-related disclosures (CRD), this paper aims to investigate how energy and agriculture markets are exposed to climate disclosure risk.

Using the multivariable simultaneous quantile regression and data from 1 January 2017 to 29 February 2024, the authors examine daily and monthly responses of energy and agriculture markets to climate disclosure risk, energy risk, market sentiment, geopolitical risk and economic policy risk. The sample covers the global market, Australia, Canada, European Union (EU), Hong Kong, Japan, New Zealand, Singapore, the UK and the USA.

The results show that climate disclosure risk creates both positive and negative shocks in the energy and agriculture markets, and the impacts are asymmetric across quantiles in different economies. The higher the climate disclosure risk, the greater impact of crude oil future on the energy sector in North America (Canada and the USA) and Europe (EU and the UK), but no greater effects in Asia Pacific (Australia, New Zealand and Singapore). The agriculture sector can hedge against economic policy and geopolitical risks, but it is highly exposed to climate disclosure and energy risks.

This study timely contributes to the modest literature on the asymmetric effects of climate disclosure risk on the energy and agriculture markets at the global and national levels. The findings offer practical implications for policymakers and investment practitioners in understanding financial effects of mandating CRD to diversify risks depending upon market conditions and policy uncertainty.