ASYMMETRIC INFORMATION AND SHOCK AS PORTFOLIO SELECTION CRITERIA: CASE OF THE DJIM 50 US PORTFOLIO

Volatility is an important variable in portfolio management. Generally, it is the level of risk in the market. The purpose of this article is to measure the impact of good and bad news on the evolution and risk associated with these securities in the financial market. To do so, we proceeded to use the EGARCH model (generalized autoregressive heteroskedasticity condition model), the data used in this study correspond to the portfolio Dow Jones Islamic Market 50 US. The results show that good and bad news has different impacts on assets.  Article visualizations

BLOCKCHAIN, CRYPTOCURRENCY AND THE STATE OF FINANCIAL INCLUSION IN MOROCCO

The immense potential of Blockchain and crypto-currencies is no longer a matter of doubt. These technologies have the power to revolutionize and change the landscape of many sectors, primarily finance. The advent of blockchain technologies provides a potential solution to the first three challenges of financial inclusion. In a few years, blockchain and its applications have the potential to become the "beating heart" of the global financial system as predicted by the WEF (World Economic Forum) in its report "The Future of Financial Infrastructure". All over the world, these technologies are currently considered as the new great technological revolution that could change our lifestyles and impact our economy as the internet did in the 80s and 90s and ideally give birth to a direct economy without intermediation. In Morocco, crypto-currencies are erasing borders and gaining popularity. However, the general opinion on this new innovation is not clear. JEL: F65; G21; O32  Article visualizations

THE IMPACT OF THE AUTOMOTIVE INDUSTRY ON THE MOROCCAN ECONOMY

This study explains the relationship between the Moroccan automotive industry, employment and gross domestic product GDP, for this reason, a literature review on the subject was conducted, which allowed us to understand the relationship between all variables. After the analysis, the results show that the variables integration order allowed us to apply the error correction model (ECM), in fact, this model confirmed the relationships between the variables, and showed that the automotive industry in Morocco has a significant positive impact on employment and GDP. JEL: L60; L62 Article visualizations

Adoption of Islamic finance for SMEs and very small enterprises in Morocco

Abstract. The factors that influence the adoption of Islamic finance in SMEs are the subject of many studies. In Morocco, no study has attempted to develop a model of adoption of Islamic finance in very small businesses. Our interest is to gain a better understanding of the internal and external determinants that influence the adoption of Islamic finance in microenterprises. Based on the model developed and previous studies, we have operationalized the different constructs, developing a research questionnaire for the leaders of TPE in Morocco. Subsequently, we conducted an exploratory and confirmatory factor analysis, based on a sample of 164 SME leaders. These different analyzes gave birth to a new model explaining the path through which the leaders of the VSEs can opt for Islamic financing in the Moroccan context.Keywords. Islamic finance, Islamic financial products, Theory of reasoned action.JEL. G21, F65, C25

New evidence from NARDL model on CO2 emissions: Case of Morocco

The main objective of this study is to examine the effect of sickle energy consumption, renewable energy, and forest area on the emission of carbon dioxide (CO2) in Morocco. Many studies have abord this subject using a different approachs, most of which have used econometric models such as Vector Autoregressive (VAR) Error Correction Model (ECM) and Autoregressive Distributed Lag (ARDL). In this study, we opted for the Non-linear Autoregressive Distributed Lag (NARDL) model. The data used covers the period from 1990 to 2018 (annual data). The results of our model are significant and prove the asymmetric effects of the explanatory variables on CO2 emissions