The development of modern information and communication technologies enabled banks to rely on mobile banking as an important distribution channel in their businesses. Given that investments in the development of mobile banking systems are extremely high, knowledge of which factors affect the intentions of individuals to use mobile banking services can be of great importance. For this purpose, empirical research was conducted and 313 respondents were surveyed in the territory of Sumadija, Central Serbia. The collected primary data were analyzed using the statistical software SPSS v. 20. To examine the factors in the work, the UTAUT model (Unified Theory of Acceptance and Use of Technology) was used. The results of empirical research indicate that all components of the UTAUT model have statistically significant influence on intention to use mobile banking, with performance expectancy singled out as the most important antecedent, while effort expectancy has the weakest impact. The paper confirms the success of the UTAUT model for testing mobile banking antecedents, and gains new insights regarding the intention of using mobile banking in Serbia that can serve for managerial purposes.

Intellectual capital in the knowledge economy is recognized as a key driver of value creation in the banking sector, which affects the business results of banks and the success of realization of business activities. The efficiency of the use of intellectual capital depends on the employees, which points out the need to analyse the relationship between intellectual capital and the efficiency of employees. The aim of the research in this paper is to identify the relationship between intellectual capital and indicators of work results of employees in the banking sector of the Republic of Serbia. The sample consists of all banks which, according to the data of the National Bank of Serbia, operated in 2018. In order to test the research hypotheses, correlation and regression analysis is used. The results of the research clearly show that intellectual capital affects employee productivity. The coefficient of capital employed efficiency has the most significant impact on employee productivity.

The emergence of new information technologies, such as the Internet of Things, the fifth generation of mobile Internet, artificial intelligence, Big Data, machine learning and blockchain, has led to significant changes in the social and business environment. The potential for exponential growth in such conditions is also recognized in the field of electronic payment systems. The development of the Internet of Things, as a global technical infrastructure that connects objects by adding microprocessors and communications software to them, has become an important basis for the further progress of electronic payment systems. In the process of further improvements, the system faces the great challenge of protection against the unauthorized use, modification or destruction of data. An even greater challenge is the potential abuse of users' personal data by business entities or government agencies. The paper focuses on the challenges of protecting the privacy of users of electronic payment systems in a smart environment.

The way in which financial markets operate has substantially been changed by the development of information technology. Automation of trading systems in financial markets represents the last phase of depersonalizing activities previously done by traders. Algorithmic trading development enabled computers to determine the moment and the way of executing sales orders. Computers still do not make autonomous decisions regarding the choice of instruments to be traded or trading criteria. They implement the strategy a trader has decided on, choosing a favorable moment. This reduces the impact of human emotions on decision making and enables overcoming possible problems which arise due to neglecting or lack of concentration. High-frequency trading enables the execution of algorithmic operations at a high speed. The main goal of the paper is to determine advantages and dangers produced by algorithmic stock trading.

Predmet rada je utvrđivanje efekata rezultata referenduma u Velikoj Britaniji o ostanku u Evropskoj uniji na kretanje cena akcija na Londonskoj berzi. Za kvantifikovanje efekata i utvrđivanje statističke značajnosti testa korišćena je metodologija studije događaja. Istraživanje je sprovedeno na primeru 167 akcija listiranih na Londonskoj berzi, grupisanih u 5 uzoraka prema sektoru poslovanja kompanije. Imajući u vidu visok stepen integrisanosti privreda zemalja Evropske unije, očekivan je negativan efekat ishoda referenduma. Generalni zaključak je da su testovi pokazali opravdanost pretpostavki u vezi sa očekivanim efektima. Konzistentni rezultati parametarskih i neparametarskih testova u tri od pet posmatranih sektora (finansijskom, tehnološom i prehrambenom) potvrda su relevantnosti dobijenih rezultata. Parametarski testovi su pokazali statističku značajnost negativnih efekata na kompanije energetskog sektora, ali neparametarski testovi nisu potvrdili ove rezultate. Nije utvrđena statistička značajnost ishoda referenduma na kretanje prinosa kompanija sektora medicinskih usluga.