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The purpose of this study is to investigate the relationship between the stock return volatility, the outside and the independent directors.

The volatility, as the dependent variable in the model, is measured by the standard deviation of annual stock returns. Concerning the independent variable is as follows: The chief executive officer (CEO) is a dummy variable denoting whether or not the chairman of the board holds the position of CEO. The INDD, which represents the independent directors, is measured according to whether the firm appoints independent directors, or by the ratio of independent directors. The FD, which represents the outside directors, is measured according to whether the firm appoints outside directors, or by the ratio of outside directors. In addition, the authors also add the following five control variables to the regression model: the certified public accountant refers to the auditor-related variables including the audit opinion and whether the firm has previously switched accounting firms. The performance (PER) represents the firm performance in terms of the relative return on assets (ROA). The turnover (TURN) is measured by the natural log of the total liabilities. The SIZE is measured by the natural log of the market value of equity, and the leverage ratio (LEV) is the firm’s debt ratio measured by the ratio of total. The TURN is measured by the natural log of the total liabilities. The SIZE is measured by the natural log of the market value of equity and the LEV is the firm’s debt ratio measured by the ratio of total debt to total assets. The sample comprises 89 firms listed on the SBF 120 index over 2006-2012.

Results reveal that the outside directors have a positive and significant effect on the stock return volatility. Moreover, the firm’s size and ROA have a negative effect on the stock return volatility, which is clearly evidenced in all the regressions. On the other hand, the CEO, audit size and debt ratio have statically significant and positive effects on the stock return volatility.

This study indicates the importance of corporate governance and helps investors and financial economists understand the behavior of the stock prices during a financial crisis. Although the existing studies refer to the influence of corporate governance on the stock prices during a crisis, none of these has ever discussed whether better corporate governance can help reduce the stock price volatility in such a situation.

This study aims to explore the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19.

This research analyzes the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19, using the quantile regression approach for the 2016–2020 period. In addition, to catch long- and short-run asymmetries of cryptocurrencies on aforementioned dependent variables, an asymmetric nonlinear co-integration (nonlinear autoregressive distributed lag [NARDL]) approach is applied.

The result of the quantile regression shows that in a high market, which corresponds to the 90th quantile, the FTSE MIB, CAC40, SSE, BSE 30, and BVSP stock market showed a statistically insignificant negative coefficient, on the Bitcoin price. In a middle and low markets, which correspond to the 0.2, 0.3 and 0.5th quantiles, the BVSP, FTSE MIB, S&P/TSX, SSE and Nikkei stock markets show statistically significant and positive on Bitcoin. Evidence from the NARDL shows a statistically significant positive impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS indices before and during COVID-19 pandemic.

These results can provide investors with valuable analysis and information and help them make the best decisions and adopt the best strategies. Therefore, future investigations may concentrate and examine the monetary and governmental policies to be adapted to face the COVID-19 pandemic’s dangerous effects on both the society and the economy. For this reason, investors should take this into account when making their asset allocation decisions. Moreover, the portfolio managers, such as index funds, may consider few eligible cryptocurrencies for their inclusion into the portfolio. However, the speculators present in both stock and crypto markets may opt for a spread strategy to improve their portfolio returns.

The purpose of this paper is to study the impact of some corporate governance mechanisms on the market risk (stock price return and volatility, exchange rate) and on the exchange rate and Treasury Bill during the financial crisis. In order to better clarify the firms’ resistance to financial crises, the effect of exchange rate, Treasury Bill and the market risk are also considered.

The study uses a sample data of the SBF 120 on a panel of 99 French firms over the period between 2006 and 2015 divided into three sub-periods: the first sub-period, which covers the period between December 31, 2006 and December 31, 2009, was characterized by the outbreak of the subprime crisis. The second sub-period considers the sovereign debt crisis in Europe between December 31, 2010 and December 31, 2012. The last sub-period includes the post-crisis period (December 31, 2013 to December 31, 2015). The GARCH and BEKK models are used to capture the effect of volatility and conditional heteroskedasticity of both corporate governance and market risk.

The paper found that during the financial crisis (first sub-period, the sovereign crisis period), the high shareholders’ protection had a positive and significant impact on the stock market returns. Furthermore, the shareholders’ protection, the Treasury Bill, the institutional investors, the board’s size, had a negative and significant effect on the stock returns volatility. During the post-crisis period, the high protection and the board’s size had a negative and significant effect on the volatility of the stock returns.

This result implies that during the financial crisis, the high shareholders’ protection played a role in increases the stock market return and minimized the stock return volatility.

This study helps in improving the legal protection of investors and helps managers, shareholders and investors to evaluate their investments. This study also provides implications for policymakers and legal environment in order to evaluate the importance of the current corporate governance frameworks in place.

This result implies that the institutional investors, as the results suggest, should follow the shareholders’ protection in all the countries to make decisions about their investments since the high shareholders’ protection increases the firm’s stock returns and decreases the stock return volatility.

The purpose of this study is to examine the impact of domestic ownership on the stock return volatility. The authors use a detailed panel data set of 89 French companies listed on the SBF 120 over the period 2006-2013. The empirical results show that the domestic institutional investors have low stock price volatility in the French stock market. This result implies the stabilizing factor of domestic investors in France stock markets, which can be considered as one of the potential favor of growing the exhibition of domestic stock markets to institutional investors. This study employs a variety of econometric models, including feedbacks, to test the robustness of our empirical results.

To explain the relation between stock return volatility and domestic institutional investors (DIIs), the authors used two complementary methods: two-step generalized method of moments analysis as well as panel vector autoregressive framework and two-stage least squares (2SLS) method.

The authors’ empirical results show that the proportion of DIIs with advanced local degrees stabilizes the stock price volatility. However, firm’s size and the turnover have a positive effect on the volatility of the stock returns. This result is consistent with the hypothesis that the firm’s size and the turnover will increase price volatility during a financial crisis as a result of the deterioration of the monitoring mechanism and the reduction of the investors’ confidence in firms.

This result also indicates that the variables (the firm’s size, total sales and debt ratio) are poor corporate governance and have a role in the increased the stock return volatility.

The aim of this study was to investigate the dynamic network connectedness between stock markets and commodity futures and its implications on hedging strategies. Specifically, the authors studied the impact of the 2014 oil price drop and coronavirus disease 2019 (COVID-19) pandemic on risk spillovers and portfolio allocation among stock markets (United States (SP500), China (SSEC), Japan (Nikkei 225), France (CAC40) and Germany (DAX)) and commodities (oil and gold).

In this study, the authors used the Baba, Engle, Kraft and Kroner–generalized autoregressive conditional heteroskedasticity (BEKK–GARCH) model to estimate shock transmission among the five financial markets and the two commodities. The authors rely on Diebold and Yılmaz (2014, 2015) methodology to construct network-associated measures.

Relying on the BEKK–GARCH, the authors found that the recent health crisis of COVID-19 intensified the volatility spillovers among stock markets and commodities. Using the dynamic network connectedness, the authors showed that at the 2014 oil price drop and the COVID-19 pandemic shock, the Nikkei225 moderated the transmission of volatility to the majority of markets. During the COVID-19 pandemic, the commodity markets are a net receiver of volatility shocks from stock markets. In addition, the SP500 stock market dominates the network connectedness dynamic during the COVID-19 pandemic, while DAX index is the weakest risk transmitter. Regarding the portfolio allocation and hedging strategies, the study showed that the oil market is the most vulnerable and risky as it was heavily affected by the two crises. The results show that gold is a hedging tool during turmoil periods.

This study contributes to knowledge in this area by improving our understanding of the influence of fluctuations in oil prices on the dynamics of the volatility connection between stock markets and commodities during the COVID-19 pandemic shock. The study’s findings provide more implications regarding portfolio management and hedging strategies that could help investors optimize their portfolios.

The purpose of this paper is to explore the relationship between Dow Jones Islamic Market World Index, Islamic gold-backed cryptocurrencies and halal chain in the presence of state (regime) dynamics.

The authors have used the Markov-switching model to identify bull and bear market regimes. Moreover, the dynamic conditional correlation, the Baba, Engle, Kraft and Kroner- generalized autoregressive conditional heteroskedasticity and the wavelet coherence models are applied to detect the presence of spillover and contagion effects.

The findings indicate various patterns of spillover between halal chain, Dow Jones Islamic Market World Index and Islamic gold-backed cryptocurrencies in high and low volatility regimes, especially during the COVID-19 pandemic. Indeed, the contagion dynamics depend on the bull or bear periods of markets.

These present empirical findings are important for current and potential traders in gold-backed cryptocurrencies in that they facilitate a better understanding of this new type of assets. Indeed, halal chain is a safe haven asset that should be combined with Islamic gold-backed cryptocurrencies for better performance in portfolio optimization and hedging, mainly during the COVID-19 period.

To the best of the authors’ knowledge, this paper is the first research on the impact of the halal chain on the Dow Jones Islamic Market World Index return, Islamic gold-backed cryptocurrencies returns in the bear and bull markets around the global crisis caused by the COVID-19 pandemic.

This study aims to investigate the transmission of shock between the oil market and the Islamic and conventional stock markets of the Gulf Cooperation Council (GCC) countries during the oil shocks of 2008 and 2014.

This study uses two models. First, the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic model has been used to capture the fundamental contagion effects between the oil market and the Islamic and conventional stock markets during the tranquil and turmoil-crisis periods of 2008-2014. Second, the filter of Kalman has been used to capture the effects of pure contagion between the oil market and the GCC Islamic and conventional stock markets. The authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices.

The main findings of this investigation are: first, the estimation of the dynamic conditional correlation– generalized autoregressive conditionally heteroskedastic model for oil market and the Islamic and conventional stock markets proves that the Islamic and conventional stock markets and oil market displayed a significant increase in the dynamic correlation during the turmoil period, from mid-2008 and mid-2014. This proves the existence of contagion between the markets studied. Second, the authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices. They show a strong increase in the correlation coefficients between the oil market and the conventional GCC stock markets, and between the conventional and Islamic GCC stock markets during the oil crisis of 2014. However, there is no change in regime in the figure of the correlation coefficient between the oil market and the GCC Islamic stock markets during the 2008 financial crisis. This pure contagion is mainly attributed to the herding bias in 2014 oil crisis.

This study contributes to identifying the contribution of herding bias on the volatility transmission between the oil markets, and the GCC Islamic and conventional stock market, especially during two controversial shocks: the 2008 oil-price increase and the 2014 oil drop.

This study aims to test the presence of herding behavior in commodity markets, including energy, metals and agriculture. Additionally, the authors investigate the possible asymmetric effect of oil price changes on the herding behavior in these markets.

The authors examine herding based on the cross-sectional absolute deviation (CSAD) model in a static and time-varying perspective.

By using daily data over the period 2003–2017, the authors’ findings firstly support the dynamic nature of investor behavior in commodity markets, which oscillates between antiherding during the normal period and herding during and after the global financial crisis of 2008. Furthermore, results highlight that the asymmetric impact of oil shocks on herding differs across commodity sectors and periods. Additionally, herding seems to be more pronounced when the oil market declines, which may be due to the pessimistic investors' sentiments.

This study provides insight into what factors influence herd behavior in commodity markets. The understanding of factors driving herding aids investors to avoid the impact of this behavior and its consequences

To the authors’ knowledge, this study is the first to examine whether the level of herding depends on the oil price fluctuations, as well as the asymmetric effect of the oil price on herding behavior in commodity markets.

This paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock market index and cryptocurrencies. It investigates the relevant impact of RavenPack COVID sentiment on the dynamic of stock market indices and conventional cryptocurrencies as well as their Islamic counterparts during the onset of the COVID-19 crisis.

The authors rely on the methodology of Diebold and Yilmaz (2012, 2014) to construct network-associated measures. Then, the wavelet coherence model was applied to explore co-movements between GCC stock markets, cryptocurrencies and RavenPack COVID sentiment. As a robustness check, the authors used the time-frequency connectedness developed by Barunik and Krehlik (2018) to verify the direction and scale connectedness among these markets.

The results illustrate the effect of COVID-19 on all cryptocurrency markets. The time variations of stock returns display stylized fact tails and volatility clustering for all return series. This stressful period increased investor pessimism and fears and generated negative emotions. The findings also highlight a high spillover of shocks between RavenPack COVID sentiment, Islamic and conventional stock return indices and cryptocurrencies. In addition, we find that RavenPack COVID sentiment is the main net transmitter of shocks for all conventional market indices and that most Islamic indices and cryptocurrencies are net receivers.

This study provides two main types of implications: On the one hand, it helps fund managers adjust the risk exposure of their portfolio by including stocks that significantly respond to COVID-19 sentiment and those that do not. On the other hand, the volatility mechanism and investor sentiment can be interesting for investors as it allows them to consider the dynamics of each market and thus optimize the asset portfolio allocation.

This finding suggests that the RavenPack COVID sentiment is a net transmitter of shocks. It is considered a prominent channel of shock spillovers during the health crisis, which confirms the behavioral contagion. This study also identifies the contribution of particular interest to fund managers and investors. In fact, it helps them design their portfolio strategy accordingly.

This article unveils first the lead–lag structure between the confirmed cases of COVID-19 and financial markets, including the stock (DJI), cryptocurrency (Bitcoin) and commodities (crude oil, gold, copper and brent oil) compared to the financial stress index. Second, this paper assesses the role of Bitcoin as a hedge or diversifier by determining the efficient frontier with and without including Bitcoin before and during the COVID-19 pandemic.

The authors examine the lead–lag relationship between COVID-19 and financial market returns compared to the financial stress index and between all markets returns using the thermal optimal path model. Moreover, the authors estimate the efficient frontier of the portfolio with and without Bitcoin using the Bayesian approach.

Employing thermal optimal path model, the authors find that COVID-19 confirmed cases are leading returns prices of DJI, Bitcoin and crude oil, gold, copper and brent oil. Moreover, the authors find a strong lead–lag relationship between all financial market returns. By relying on the Bayesian approach, findings show when Bitcoin was included in the portfolio optimization before or during COVID-19 period; the Bayesian efficient frontier shifts to the left giving the investor a better risk return trade-off. Consequently, Bitcoin serves as a safe haven asset for the two sub-periods: pre-COVID-19 period and COVID-19 period.

Based on the above research conclusions, investors can use the number of COVID-19 confirmed cases to predict financial market dynamics. Similarly, the work is helpful for decision-makers who search for portfolio diversification opportunities, especially during health crisis. In addition, the results support the fact that Bitcoin is a safe haven asset that should be combined with commodities and stocks for better performance in portfolio optimization and hedging before and during COVID-19 periods.

This research thus adds value to the existing literature along four directions. First, the novelty of this study lies in the analysis of several financial markets (stock, cryptocurrencies and commodities)’ response to different pandemics and epidemics events, financial crises and natural disasters (Correia et al., 2020; Ma et al., 2020). Second, to the best of the authors' knowledge, this is the first study that examine the lead–lag relationship between COVID-19 and financial markets compared to financial stress index by employing the Thermal Optimal Path method. Third, it is a first endeavor to analyze the lead–lag interplay between the financial markets within a thermal optimal path method that can provide useful insights for the spillover effect studies in all countries and regions around the world. To check the robustness of our findings, the authors have employed financial stress index compared to COVID-19 confirmed cases. Fourth, this study tests whether Bitcoin is a hedge or diversifier given this current pandemic situation using the Bayesian approach.