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This study aims to examine information (stock return, volatility and extreme risk) spillovers and interconnectedness within dual-banking systems.

Using multilayer information spillover networks, this paper conduct a deep analysis of contagion dynamics among 24 Islamic and 46 conventional banks from 2006 to 2022.

The findings show the network’s rapid response to financial shocks. Through cross-sector analysis, this paper identify information spillovers between and within Islamic and conventional banking systems. Furthermore, this research illustrates distinct roles played by Islamic and conventional banks within the multilayer network structure, contingent upon the nature of the financial shock.

Understanding the differential roles of Islamic and conventional banks in information transmission can aid policymakers and financial institutions in devising more effective risk management strategies, thereby enhancing financial stability within dual-banking systems.

This study contributes to the literature by emphasizing the necessity of examining contagion mechanisms beyond traditional single-layer network structures, shedding light on the shadow dynamics of information transmission in dual-banking systems.

This paper proposes a framework to identify a pattern in the relationship between firms’ cost structure (i.e. fixed versus variable) and their volatility in stock returns.

Our empirical analysis is based on a panel data regression where we use an extended sample period and a time-series regression-based elasticity measure of operating leverage.

We document significantly higher systematic risk among firms with large fixed costs, a conclusion which confirms theoretical predictions of earlier studies. In new findings, we document high firm-specific risk and high stock return volatility among firms with a fixed cost structure.

The paper fills a gap in the literature by examining the effect of cost structure using various operating leverage measures and other control measures for firm characteristics on idiosyncratic risk. Studies that seek to explain firms’ systematic risks are numerous; conversely, there are relatively fewer studies on the determinants of firms’ specific risks.

This paper examines the impact of macroeconomic volatility on stock volatility, both under normal conditions and during the COVID-19 pandemic in Vietnam.

We extend the existing Exponential Generalized Autoregressive Conditional Heteroskedasticity model by adding a new component: the thresholds – the levels of macroeconomic volatility at which the market may respond differently. These thresholds are estimated for both positive and negative volatility.

The impact of macroeconomic volatility on stock volatility is asymmetric: there are thresholds of macroeconomic volatility at which its pattern changes. These thresholds are higher in the case of positive volatility compared with negative volatility. The thresholds were also higher during the COVID-19 pandemic. Macroeconomic variables influence stock volatility differently depending on market conditions. While GDP is more significant in normal periods, interest rates affect it in both normal and unstable phases.

Our models consider only two variables representing macroeconomic variables: interest rate and GDP. Furthermore, only one lag period of the variables is included in the analysis. In the future, more macrovariables and longer lags could be included when computational techniques advance.

Policymakers should consider the impact of macroeconomic volatility on the stock market when designing policies, especially at thresholds. Similarly, investors should pay more attention to macroeconomic volatility when constructing and managing their portfolios, particularly when such volatility is close to thresholds.

The inclusion of thresholds as parameters to be estimated into the model provides more insights into the impact of macroeconomic variables on stock volatility.

This study investigates the reasons behind the very high net interest margins in the Greek banking industry compared to the euro-area, focussing on the association between bank competition and recapitalisations.

The author conducts a dynamic panel analysis covering the period from the early 2000s to 2021, that controls for possible endogeneity and treats for heterogeneity. The author also employs local projections impulse response functions that control for structural changes in Greek banking.

The author finds that low bank competition has contributed to high net interest margins in Greece. Interestingly, the impact of recapitalisations conditional to low bank competition has had a significant further impact on increasing net interest margins, which is a noteworthy case due to several Greek bank recapitalisations in the last ten years. The author’s findings are supported by local projections impulse response functions.

To mitigate distortions in bank competition, the author argues to accelerate steps toward the direction of the banking union and a common bank regulation framework in the euro-area.

This study aimed to explore the determining factors for green bond markets in ASEAN plus three countries. In contrast to previous publications that primarily examined the incentives for green bonds and institutional differences among economies, the analysis focused on the role of competition among sub-financial sectors in fostering the growth of green bond markets.

This study adopted Driscoll and Kraay fixed effect panel methods to account for country-level heterogeneity and enhance efficiency, using quarterly data from 2016 to 2022.

The findings showed that healthy competition among sub-financial sectors was crucial for the growth of green bond markets. Growth in specific sub-financial sectors such as brown corporate bond and stock markets as well as banks contributed positively to these markets. Variables related to market microstructure also had no significant impact on green bonds but macroeconomic factors did.

The findings suggested that governments should promote healthy competition among sub-financial sectors and implement diverse policies to ensure the sustainable growth of green bond markets.

This study further pioneered the importance of competition among sub-financial sectors for the development of green bond markets.

We examined the dynamic volatility connectedness and diversification strategies among US real estate investment trusts (REITs) and green finance indices.

The DCC-GARCH dynamic connectedness framework and he DCC-GARCH t-copula model were employed in this study.

Using daily data from 2,206 observations spanning from 2 January 2015 to 31 January 2023 this paper presents the following findings: (1) cross-market spillovers exhibited a high correlation and significant fluctuations, particularly during extreme events; (2) our analysis confirmed that REIT acted as net receivers from other green indices, with the S&P North America Large-MidCap Carbon Efficient Index dominating the in-network volatility spillover; (3) this observation suggests asymmetric spillovers between the two markets and (4) a portfolio analysis was conducted using the DCC-GARCH t-copula framework to estimate hedging ratios and portfolio weights for these indices. When REIT and the Dow Jones US Select ESG REIT Index were simultaneously added to a risk-hedged portfolio, our findings indicated that no risk-hedging effect could be achieved. Moreover, the cost and performance of hedging green assets using REIT were found to be comparable.

We first examined the dynamic volatility connectedness and diversification strategies among US REITs and green finance indices. The outcomes of this study carry practical implications for market participants.

This paper investigates potential safe haven assets for Middle East and North Africa (MENA) stock markets during the uncertainty period of the COVID-19 pandemic.

This study applies the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic (DCC-GARCH) model and the Diebold–Yilmaz spillover index for ten MENA stock markets, three precious metals and Bitcoin for the period 2013–2021.

Empirical results show, on the one hand, that the COVID-19 crisis risk has been transmitted to MENA stock markets through volatility spillover across markets. This has increased the conditional volatility for all markets. On the other hand, findings point out that the dynamic correlation between the precious metals/Bitcoin and stock markets is not stable and switches between low positive and negative values during the period under studies. Extending analysis to portfolio management, results reveal that investors should include precious metals/Bitcoin in their portfolio of stocks in order to reduce the risk of the portfolio. Finally, for the period of COVID-19, the analysis concludes that gold preserves its traditional role as a safe haven for MENA stock markets during the pandemic, while Bitcoin fails to provide this property.

These results have several implications for international investors, risk managers and financial analysts in terms of portfolio diversifications and hedging strategies. Indeed, the exploration of the volatility connectedness between financial, commodity and cryptocurrency markets becomes an essential task for all market participants during the COVID-19 outbreak. Such analysis can help investors and portfolio managers to evaluate the risk of investments in the MENA stock markets during the crisis period and to achieve the optimal diversification strategy and hedging instruments.

The paper interests MENA stock markets that experienced the last decade a substantial development in terms of market capitalization and number of listed firms. To the author’s knowledge, this is the first study that investigates the dynamic correlation between MENA stock markets and four potential safe haven assets, including three precious metals and Bitcoin. In addition, the paper employs two types of models, namely the DCC-GARCH model and the Diebold-Yilmaz spillover index.

This paper investigates the relationship between institutional ownership and idiosyncratic volatility in Chinese and the USA stock markets and explores the potential explanations.

In this paper, the authors use the panel data regressions and the dynamic tests of two-way Granger causality in the panel VAR model to examine the relationship between institutional ownership and idiosyncratic volatility in Chinese and the USA stock markets.

The authors find that the institutional ownership in the Chinese (the USA) stock market is significantly and positively (negatively) related to idiosyncratic volatility through various tests. This paper indicates that institutional investors in the USA are more prudent and risk-averse, while the Chinese institutional investors are not because of high risk-bearing capacity.

This paper deepens the authors’ understanding on the relationship between institutional ownership and idiosyncratic volatility and in the USA and the Chinese stock markets. This paper explains the opposite relationships between institutional ownership and idiosyncratic volatility in the stock markets in China and USA.

This paper seeks to investigate whether women exhibit greater risk-aversion behavior than men in investments by estimating the influence of gender on portfolio volatility.

Data on the volatility observed in the portfolio in the last six months, last twelve months and since the individual became a client at one of the largest financial institutions in Brazil – and in Latin America – that operates in the capital markets are used. In addition to the gender explanatory variable, socioeconomic variables such as age, marital status, suitability, residence in capitals and declared assets are controlled, and multiple linear regression models are controlled.

The results show that gender is statistically significant in all models estimated to explain the volatility of investment portfolios, saying that women are more risk averse than men.

These findings are useful for the scientific literature that investigates behavioral finance by bringing empirical evidence for Brazil.

The study aims to investigate the risk transmission from COVID-19 to global agriculture, energy, natural resources/mining and environmentally/socially responsible investments. Additionally, it explores the connectedness of global energy indices with global agriculture, natural resources/mining and environmentally/socially responsible investments. The study develops a new COVID-19-based Global Fear Index (GFI) to achieve the objectives, thus contributing to the prevailing literature.

The data of Global indices are selected from January 2020 to December 2021. The study uses multivariate BEKK-GARCH and TVP-VAR models to explore COVID-19 risk transmission and connectedness between global indices.

Significant shock and volatility transmissions from COVID-19 to all global indices are observed. Results show that global agriculture, natural resource/mining markets and environmentally and socially responsible investments are safe havens during COVID-19. Furthermore, these global investment choices are barely connected with global energy indices.

Portfolio managers and investors should invest in global indices to gauge the risk-adjusted return during the pandemic and upcoming health-related risks. Investors in energy sectors are advised to diversify the risk by adding safe-haven assets to their portfolios.

The findings shed light on the importance of environmentally and socially responsible investments as a separate asset class where ecologically friendly and socially sentimental investors could invest in diversifying the risk of their portfolios.

The paper offers valuable insights to policymakers and investors regarding asset pricing, risk management and financial market stability during pandemic-type emergencies.