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PurposeThis study aims to determine the factors affecting the merger and acquisition (M&A) process in the United Arab Emirates (UAE) banking sector. It distinguishes between internal and external factors that may motivate M&A activities in the banking sector.Design/methodology/approachThis study adopts quantitative research and a survey strategy for data collection. A model was developed using a survey e-mailed to 500 bankers to gather data on the factors affecting the banking sector’s M&A.FindingsThis study’s findings provide strong empirical evidence for factors extracted by the factor analysis (Income, Growth, Costs, Survival, Diversifications, Security and Risk and Legal), which are important in determining the consolidation process leading to successful M&A in the banking industry. This study also contributes to the business combinations and consolidation literature by explaining the important factors in measuring the bank’s performance during the M&A process.Research limitations/implicationsFuture studies could be directed in many directions. First, the authors extend the study to other GCC countries and examine whether the determinants of banks’ M&A are similar across markets. Second, the authors examine additional nonfinancial bank-specific characteristics, such as management incentives and corporate governance or additional market characteristics. Third, the authors examine the motives for acquisitions of foreign banks by UAE banks and vice versa. There may be much to learn about how acquisition motives are likely to differ.Practical implicationsThe findings can help bank managers know if their banks have developed the same profile or factors similar to typical target banks. The theoretical understanding of the importance of this study in creating an environment of trust that governs the behavior of bankers for both banks will reduce the agency issue. Regarding general management, this study indicates that opportunistic behaviors could interest banks, bankers’ associations, central banks, governments, other financial authorities and policymakers. Therefore, this study paves the way for further investigation of mergers, agency theory and ethics issues. These banks’ owners, managers and regulators were also advised to consider these factors in formulating their policies and processes, given their influence on performance and their ability to manage the relationship between banks and improve the efficiency of the UAE banking sector.Originality/valueThis study provides new perspectives concerning motives leading financial institutions to M&A owing to banks’ decisions to improve their financial positions, coupled with the need to obey pressures of macro factors such as economic, legal and political systems, government and technology.

Prior research document a positive association between analyst coverage and R&D. However, they do not investigate what particular attribute of R&D leads to this positive association. In this study we aim to fill the gap in the extant literature and explore the cross-sectional determinants of the association between R&D and analyst coverage. We investigate four cross-sectional determinants: reporting biases arising from expensing of R&D compared to capitalization of R&D, uncertainty associated with R&D, investors’ attention, and scale effects of R&D. We find that while reporting biases and uncertainty decrease analyst coverage for R&D firms, investors’ attention and scale effects of R&D increase analyst coverage. Furthermore, we find that the positive association between R&D and analyst coverage documented by Barth et al. is fully explained by scale effects of R&D.

The financial models used in the literature to investigate the performance of banks show mixed results and a low R² in many of the studies. Therefore, Agency theory can be used in addition to the financial models to give investors enough information about banking industry performance. The sample used in this study consist of accounting information (bank specifics) and market information (macroeconomic variables) for a group of national and foreign banks located in the GCC countries during the period 2002 to 2013. The final sample consists of 115 banks with completed data collected from Bankscope database for financial data. The macroeconomic data were collected from sources such as the International Monetary Fund, International Financial Statistics, National Statistics, and the World Bank. Regression models have been developed to examine the factors that may determine banks performance in the GCC. The results of the study provide evidence that the models used in this paper are significant, indicating that all models containing the above financial and macroeconomics factors are important and statistically significant in determining and explaining bank performance. Even though our results indicate that the above factors are important in measuring bank performance, we believe that the agency theory could be used to shed some lights and provide insights on factors affecting bank performance in the GCC countries. There appears to be a need for a common understanding, a balancing of risks with financial rewards, and a building of long-term relationships. The findings enhance our theoretical understanding of the importance of these factors in creating an environment of trust that governs the behavior of the owners and managers, and hence reduces the agency problem. As for general management, the results indicate that opportunistic behavior can be lessened by managing the relationship between the two parties through a contract that clearly specify these factors. Therefore, this paper paves the way for further research in this area.

Prior research document a positive association between analyst coverage and R&D. However, they do not investigate what particular attribute of R&D leads to this positive association. In this study we aim to fill the gap in the extant literature and explore the cross-sectional determinants of the association between R&D and analyst coverage. We investigate four cross-sectional determinants: reporting biases arising from expensing of R&D compared to capitalization of R&D, uncertainty associated with R&D, investors’ attention, and scale effects of R&D. We find that while reporting biases and uncertainty decrease analyst coverage for R&D firms, investors’ attention and scale effects of R&D increase analyst coverage. Furthermore, we find that the positive association between R&D and analyst coverage documented by Barth et al. is fully explained by scale effects of R&D.

The objective of this study is to determine the factors that affect the finance students’ performance in Intermediate Accounting I and to generate a model that will be able to predict an early student success and failure rates in Intermediate Accounting I. This study used logit analysis as a statistical methodology to develop the model and then to test its predictive value on two groups of students—those taking the Intermediate Accounting I at the American University in the United Arab Emirates and those taking the same course at a regional campus of a major American university. A proper foundation in basic accounting knowledge and an overall level of academic ability proved to be important variables. The model correctly predicted performance with an overall accuracy rate of at least 85%, for both the American and international groups of finance students.

Accounting data has been given more consideration recently because of its usefulness in investment decisions. Annual and quarterly accounting data are used by investors in forming their future expectations. The results of this study indicate that the quarterly financial data may not be as accurate as the annual data or in using the data they have.

This paper uses annual accounting data to show that the frequency of occurrence of the first and second digits contained in the income numbers of companies, listed in the Istanbul Stock Exchange, does not deviate significantly from expectations.

The analysis in this paper is twofold: a) we use the Vector Autoregressive (VAR) methodology to briefly study predictability of bond and stock returns, and b) we investigate the efficiency of  stock and bond markets  by exploring a buy and sell strategy made up of a hypothetical portfolio which consists of bonds and stocks.  Our strategy indicates that unexploited profit opportunities exist in the U.S. security markets.  The trading strategy used to identify profitability is based on return predictability.  More specifically, we estimate risk-adjusted cumulative twelve-month and quarterly compounded returns on the Dow Jones Industrial Average and the 30-year U.S. Treasury bonds using a state of the art forecasting model.  We construct our portfolio which consists of bonds and stocks based on the highest forecast given by the model as follows.  Buy stocks when the forecast shows returns are higher in the stock market.  Switch your portfolio into bonds every time the forecast model shows higher returns in the bond market.

In this paper we attempt to determine whether the per capita real incomes of GCC countries are trend or difference stationary. The distinction is crucial for at least three reasons: first pertains to forecasting; while a trend stationary series tends to return to its long run steady state following a shock, a difference stationary series would tend to carry the impact of such a shock forever. The second has econometric implications because even minor divergences from difference stationarity would lead to non-robust cointegration estimations. The third is about economic theory where the distinction between the neoclassical and endogenous growth models can be settled via empirics of difference or trend stationarity. As the GCC countries strive for more economic integration, correct identification of trends becomes vital in policy making. Our research shows that there is evidence that the per capita real GDP of GCC countries is difference stationary.

In this paper we attempt to determine whether the per capita real incomes of GCC countries are trend or difference stationary. The distinction is crucial for at least three reasons: first pertains to forecasting; while a trend stationary series tends to return to its long run steady state following a shock, a difference stationary series would tend to carry the impact of such a shock forever. The second has econometric implications because even minor divergences from difference stationarity would lead to non-robust cointegration estimations. The third is about economic theory where the distinction between the neoclassical and endogenous growth models can be settled via empirics of difference or trend stationarity. As the GCC countries strive for more economic integration, correct identification of trends becomes vital in policy making. Our research shows that there is evidence that the per capita real GDP of GCC countries is difference stationary.