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The purpose of this paper is to examine alternative six- and seven-factor equity pricing models directed at capturing a new factor, aggregate volatility, in addition to market, size, book to market, profitability, investment premiums of the Fama and French (2015) and Fama and French’s (2018) aggregate volatility augmented model.

The models are tested using a time series regression and Fama and Macbeth’s (1973) methodology.

The authors show that both six- and seven-factor models best explain average excess returns on the French stock market. In fact, the authors outperform Fama and French’s (2018) model. The authors use sensitivity of aggregate volatility of a stock VCAC as a proxy to construct the aggregate volatility risk factor. The spanning tests suggest that Fama and French’s (1993, 2015, 2018) and Carhart’s (1997) models do not explain the aggregate volatility risk factor FVCAC. The results show that the FVCAC factor earns significant αs across the different multifactor models and even after controlling for the exposure to all the other in Fama and French’s (2018) model. The asset pricing tests show that it is systematically priced. In fact, the authors find a significant and negative (positive) relation between the aggregate volatility risk factor and the excess returns in the French stock market when it is rising (falling), in addition, periods with downward market movements tend to coincide with high volatility.

The authors contribute to the related literature in several ways. First, the authors test two new empirical six- and seven-factor model and the authors compare them to Fama and French’s (2018) model. Second, the authors give new evidence about the VCAC, using it for the first time to the authors’ knowledge, to construct a volatility risk premium.

This paper proposes a new multi-dimensional financial inclusion index.

The authors employ two-stage principal component analysis (PCA) and aggregating indicators of availability, access and use. The paper first assesses the cross-country variations in the index and analyses trends over time for a sample of countries members of the Union for the Mediterranean (UfM) from 2010–2018. Second, it investigates factors that could explain the level of financial inclusion across countries.

The financial inclusion index shows a downward trend for the full sample over the period under investigation; however when splitting the sample by income group, it appears that high- and middle–income countries did not register the same trend. When examining the determinants of financial inclusion for the UfM countries, the authors find that macroeconomic, social and governance factors, as well as banking conditions, matter. Policy-makers in low- and middle-income economies should consider the importance of digital financial inclusion, which is substituting the role to traditional banking system, to close the gap and accelerate its development.

First, the authors provide a new measure of financial inclusion using a three-dimensional index: availability, access and use, for which weights are assigned using PCA. It uses data available for the UfM sample by combining data from different databases in order to include most indicators considered in the literature, as the majority of studies only use single measures (number of bank branches, ownership of a bank account, ratio of credits or deposits to gross domestic product [GDP], etc.). Second, by focussing on UfM countries, the study covers a region that includes both large developed and small developing economies that are connected via financial and trade ties, whilst previous studies generally give global evidence from an international sample with little or no economic ties. Third, splitting the sample by country income groups, the paper presents a more comprehensive representation of the cross-country variation in financial inclusion levels between high- and middle-income economies for this region.

The purpose of this paper is to study the volatility spillover among 33 worldwide sovereign Credit Default Swap (CDS) markets and their underlying bond markets.

In contrast to prior studies, the authors incorporate heteroscedasticity, asymmetric leverage effects and long-memory features of sovereign credit spreads simultaneously through a bivariate FIEGARCH model and a Bayesian cointegrated vector autoregressive model.

Similar to the literature, the findings confirm that strong evidence of credit risk spillover between credit markets is accentuated during two recent crisis periods. However, the country-by-country analysis indicates that countries exhibit different sensitivity levels and divergent reactions to financial shocks. Further, the authors show that the bidirectional interrelationship evolves over time and across countries emphasizing the necessity of time-varying national regulatory policies and trading positions.

Based on a large data set that covers the recent two financial crises and using complex methods, the work focuses on sovereign tensions that have repercussions on banks’ solvency and refinancing conditions. Yet, the study is a hot topic since that during crisis periods in the financial markets, direct and indirect interconnections increase between sovereign risk and banking risk. Using new econometric approaches, the results show that each country exhibits a different behavior toward the credit risk which is relevant to both portfolio managers and policy makers. The time-varying spillover effects detected between markets are an accurate indicator of financial stability, allowing policy makers to put in place personalized economic policies. On the other hand, markets’ participants could take advantages of the results by adjusting their trading and hedging positions on the dynamic co-movements. The findings reveal, as well, that the sovereign crisis has more weakened the global financial and banking system than the subprime crisis. The authors previously tackled the cross-country contagion phenomenon in the CDS markets, and this manuscript builds on the prior study to enhance the obtained results.

The purpose of this paper is to investigate the informational opacity of Tunisian banks versus non‐banking firms taking into account information environment changes.

This research uses the synchronicity of stock returns as a proxy of informational opacity. It also examines bank crash risk relying on the skewness of residual returns. Finally, the study addresses the effects of mandatory disclosure requirements on firm opacity and market volatility.

The results suggest that bank stock prices incorporate less specific information than non‐banks. Moreover, banks are more likely to experience stock price crashes. However, the authors find a significant decrease of informational opacity for both banking and non‐banking firms since 2006 which supports substantial improvements in the corporate disclosure environment.

The findings are interesting for regulators. Banks with high stock returns synchronicity and negative residual returns skewness are more opaque and are significantly exposed to crash risk. Consequently, they deserve greater regulatory scrutiny. Thus, the opacity measures derived from the asset pricing model could be a useful tool for monitoring disclosure policies in the banking sector.

The paper extends the empirical literature on the determinants of bank stock returns synchronicity and skewness for an emerging economy, Tunisia. The information environment offers an empirical opportunity to examine the dynamics of opacity as well as the desirability of mandatory disclosure requirements in the banking system.

This study examines the five-factor model of Fama and French (2015) on the French stock market by comparing it to the Fama and French (1993)’s base model. The new Fama and French five-factor model directed at capturing two new factors, profitability and investment in addition to the market, size and book to market premiums. The pricing models are tested using a time-series regression and the Fama and Macbeth (1973) methodology. The regularities in the factor’s behavior related to market conditions and to the sovereign debt crisis in Europe are also examined. The findings of Fama and French (2015) for the US market are confirmed on the Paris Bourse. The results show that both models help to explain some of the stock returns. However, the five-factor model is better since it has a marginal improvement over the widely used three-factor model of Fama and French (1993). In addition, the investment risk premium seems to be better priced in the French stock market than the profitability factor. The results are robust to the Fama and Macbeth (1973) methodology. Moreover, profitability and investment premiums are not affected by market conditions and the European sovereign debt crisis.