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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.

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.

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.

This study is a crucial topic for policymakers and portfolio risk managers.

This study aims to explore empirically the determinants of stock return in a comparative context between Islamic and conventional banks.

The analysis of the determinants of stock returns is carried out through a panel data model. This study covers 14 Islamic banks and 30 conventional banks in the MENA countries (Bahrain, Egypt, Kuwait, Malaysia, Qatar, Saudi Arabia and United Arab Emirates) during 10 years, from 2004 to 2014.

The empirical results show that the market risk has a positive impact on market profitability of banks except for the small-medium (SM) and big-high (BH) portfolio for the capital asset pricing model and Fama and French models. The risk associated with the size (Small [market capitalization] Minus Big: SMB) has a positive impact on small banks and a negative impact on banks of big sizes. Finally, the risk related to the market value (High [book-to-market ratio] Minus Low: HML) has a positive impact on both small and large banks.

The answer to the question of explanatory factors for stock market returns allows managers to measure the cost of capital and thus choose the most appropriate form of financing and therefore evaluate the possibility of investing in a particular bank.