Purpose: The economic and financial literature dealing with the subject of bank profitability has often been based in the measurement of banking results on three main indicators: ROA, ROE and MIN. This article aims to determine and analyze the different determinants that influence bank profitability and to identify the impact of these determinants on the profitability of Moroccan banks.Design/methodology/approach: For this purpose, a fixed individual effect model was adopted for the case of six Moroccan banks during the period of study from 1997 to 2018. The authors carried out their estimates at three levels according to three categories of profitability factors: bank factors, factors of the banking system and macroeconomic factors.Findings: The empirical findings show that Moroccan banks react on their size to boost their performance, which further explains the continued expansion of Moroccan banking networks. The authors confirm that Moroccan banks have not yet reached a level of size that will be detrimental to their performance. Therefore, the authors can conclude that the big Moroccan banks do not follow the concept of economy of scale. The effects of the variation in the level of economic growth as well as the evolution of the level of inflation on the performance of Moroccan banks are not significant.Originality/value: The authors’ findings and results have some important originality and value. Primarily, these results would consist of better helping the State, bankers, and bank managers to better understand the various determinants of bank profitability. The results may also help to better examine the effect of each factor, whether internal or external, on banks' bottom line.

The main purpose of this study is to investigate empirically the impact of energy consumption and economic growth on the environmental degradation as measured by CO₂ emissions. We utilize the cointegration test, the fully modified OLS, and the panel causality to examine the causality between environmental pollution and economic aggregates from a panel data of eight Asian countries during the period 1991–2013. We find that the cointegration tests confirm long run relationship among environmental degradation and energy consumption and economic growth along with financial development, trade openness, capital stocks, and urbanization as control variables. In addition, FMOLS results confirm that economic growth and energy consumption have a positive and significant impact on environmental degradation. Besides, panel causality through VECM verifies that bidirectional causal connection is found between energy consumption and economic growth and environmental degradation.

This study presents an important view to the predictive capacity of COVID-19 for the correlation between Chinese stock market and 9 international stock market in Asia, Europe, and North America regions. In this paper, we try to investigate the spillover impacts of China’s stock market on the selected stock markets using an econometric methodology based on DCC-GARCH models during the period from May 01, 2019 to May 30, 2020. Our results show a strong significant DCC among China’s stock market index and selected international stock market indices especially in the outbreak of COVID-19. We find that the results related to the degree of the persistence of volatility, are sensitive to the existence of the COVID-19 surprises into the DCC-GARCH (1) model. We remark that that COVID-19 has a short-term impact on international stock market indices volatilities. Finally, we can conclude that COVID-19 explain the spillover impacts of China’s stock market index on selected countries using DCC-GARCH models. This paper gives an important framework to the investors to choose their portfolios in the financial markets especially in the crisis period. This paper contributes to the literature on assessing the impact of COVID-19 confirmed cases surprises on the correlation between China’s stock market index and selected international stock market in Asia, Europe, and North America regions.

Purpose: This paper provides an important perspective to the predictive capacity of Fed and European Central Bank (ECB) meeting dates and production announcements for the dynamic conditional correlation (DCC) between Bitcoin and energy commodities returns and volatilities during the period from August 11, 2015 to March 31, 2018.Design/methodology/approach: To assess empirically the unanticipated component of the US and ECB monetary policy, the authors pursue the Kuttner's approach and use the federal funds futures and the ECB funds futures to assess the surprise component. The authors use the approach of DCC as introduced by Engle (2002) during the period from August 11, 2015 to March 31, 2018.Findings: The authors’ results suggest strong significant DCCs between Bitcoin and energy commodity markets if monetary policy surprises are incorporated in variance. These results confirmed the financialization of Bitcoin and commodity energy markets. Finally, the DCC between Bitcoin and energy commodity markets appears to respond considerably more in the case of Fed surprises than ECB surprises.Originality/value: This study is a crucial topic for policymakers and portfolio risk managers.