First semester

Selected Chapters of Financial Mathematics3Igor Jemrić, MSc, ZSEM, Croatia
Stochastic Processes in Financial Markets3Hrvoje Štefančić, PhD, ZSEM, Croatia
Financial Management9Dario Silić, PhD, ZSEM, Croatia,
Andrej Grubišić, DBA, ZSEM, Croatia,
John A. Helmuth, PhD, University of Michigan-Flint, SAD
Financial Statement Analysis5Hrvoje Volarević, PhD, ZSEM, Croatia,
Zoran Bubaš, PhD, ZSEM, Croatia,
Mario Varović, MSc, ZSEM, Croatia

Second semester

Financial Derivatives5Iskra Kalođera Schmiedecke, PhD, ZSEM, Croatia,
Mladen Fruk MA, ZSEM, Croatia
Project Management5Siniša Krajnović, PhD, ZSEM Croatia
Quantitative Methods for Managers4Petra Posedel, PhD, ZSEM, Croatia
Applied Econometrics3Petra Posedel, PhD, ZSEM, Croatia
Portfolio Management and Investments9Denis Alajbeg, PhD, ZSEM, Croatia
Business Ethics, CSR and Sustainability3Kristijan Krkač, PhD, ZSEM Croatia,
Borna Jalšenjak, PhD, ZSEM, Croatia,
Igor Matutinović, PhD, ZSEM, Croatia
Risk Management 15Mladen Latković, MSc, ZSEM, Croatia

*ZSEM reserves the right to change the courses and the faculty

Course description


Financial intermediation, basic elements and physiognomic of financial systems: the concept and classification of financial instruments, basic physiognomics of financial intermediation system, mathemathical structure of financial instruments, time value of money, simple and compound interest calculation. Zero-coupon bonds: mathematical structure and zero-coupon bond pricing, zero-coupon bond duration and convexity. Coupon bonds: coupon bond current value and price, coupon bond duration and convexity, calculation of the coupon bond yield to maturity. Yield curves and hedging: hedging, empirical and modified yield curve, quotation example: US Treasury Pack. Forward prices and yields: repurchase agreements, forward prices and forward yields. Yield measurement: yield measurement of securities and portfolio, internal rate of return, total rate of return. Financial derivates: futures, swap- arrangements.


Markov processes and reconstruction processes. Simple Markov processes. Homogeneous Markov chains. Stationary conditions. Spectral decomposition. Application on stock price fluctuation. Classification of conditions. Preparation for assessment of students` knowledge. Brownian motion. Stochastic integrals and stochastic differential equations. Ito`s lemma. Geometric Brownian motion. Ornstein-Uhlenbeck process. Cox, Ingersoll-Ross model. Euler discretization. Binomial tree. Path simulations in a diffused process. Application of maximum likelihood method. Method of moments. Monte Carlo simulations. Monofactorial models. Rendeleman-Bartter model. Vasicek model. Hull White model. Application of trees on interest rates. Merton model. Cox Ross model. Models with stochastic volatility.


The primary function of the course is the adoption of basic concepts of financial report analysis which serves as the basis for managerial decision making. The course focuses on the valuation of debt instruments and capital and is based on internationally accepted standards.


The course is organized into few basic units of key importance for financial management, such as: basic theoretical concepts of modern finance; the return on and assessment of investing into securities; the risk of securities portfolio, efficient sets and the impacts of international diversification. The course provides students with an overview of risk management methods applied in financial institutions. After the introductory notes on the reasons for the usage of risk management methods in practice, the students will hear about theoretical postulates. The topics that will be discussed are: risk classification, methods of risk measurement and prediction, Value at Risk Method and learning other risks in the financial world.


This course will introduce students to an exciting area of financial derivatives. Topics that will be discussed are: derivatives markets, derivative valuation and derivative trading strategy. Forwards, futures, swaps and options will be examined in detail.


Efficientproject management ensures that the projects are done within deadlines and budgets, and have a good level of quality. The goal of the course is to introduce students to techniques needed for achieving these three goals. The basic issues and segments of project management that students will be dealing with in this course are the following: the qualities of efficient project manager, typical responsibilities of a manager and a choice of a project, providing and developing projects; development of a detailed work and time plan as well as budget, creating a project team and keeping it together, managing, controlling the quality of the work on the project and risk management; communication between members of a project team, investors and managers; forecasting and avoiding potential problems; specific roles of support services (finances, marketing, procurement, IT support). Project teams necessarily implement the company mission and its strategic goals, adjust to the needs, all of which results in decreasing the number of employees, outsourcing, and temporary termination of an employment contract. Students will use simulation to go through these situations.


The course is a continuation of the undergraduate courses of Statistics. It studies the role of statistical deduction when decreasing the uncertainty of business decision-making process. Students will be introduced to statistical instruments and methods, and also gain an insight into the methods of applying those instruments when interpreting statistical data and reports.


An overview of the most important statistical tests. Numerical generation of statistical distributions. Linear regression models (the assumptions of the classical model). Maximum likelihood method. Predictions. Durbin-Watson statistic. Singular Value Decomposition. Multiple regression models. Multiple determination coefficients. Akaike`s and Schwarz`s criterion. Classical assumptions and their empirical foundation. Multiple regression with qualitative data (dummy variables). F-test application. Predictions. Violation of classical assumptions (heteroscedasticity). Normality and heteroscedasticity testing. Jarque-Bera test. Goldfeld-Quandt test. White test. Linear restrictions on regressive parameters.: chi2 test, LR test, LM test and Wald test. F-test application. The adding and subtracting of explanatory variables. Parametric stability testing: Chow test, Durbin-Watson test. Ljung Box test. Violation of classical assumptions II (stochastic explanatory variable). Simultaneous equations. Non-ionospheric disturbances. Generalized least squares method. Autocorrelation testing. Durbin-Watson test. Dynamic distributed lag models. ADL models. Monte Carlo simulations. Heteroscedasticity and autocorrelation in the models of time sequences. Estimation with the instrumental variable method. Estimation with the maximum likelihood method. Simultaneous equation models. Estimation methods for panel data.


The course provides students with an overview of risk management methods applied in financial institutions. After the introductory notes on the reasons for the usage of risk management methods in practice, the students will hear about theoretical postulates. The topics that will be discussed are: risk classification, methods of risk measurement and prediction, Value at Risk Method and learning other risks in the financial world.


In the Business Ethics, CSR and Sustainability Course is not a clear and unambiguous area; it is exposed to numerous interpretations within the context of “what is the right thing to do”. The course comprises discussions on interrelations between economic, legal, political, social, cultural and ethical issues in the definition of the business policy, managerial decision making at the stage of the business policy implementation, and, finally, as an integral part of business activities.


The course consists of two parts: in the first part, students will acquire basic knowledge on the principles of investment. Types and features of securities available for the investment will be analyzed, as well as the financial markets where they are traded and the investment environment. The other part refers to the practical portfolio simulations when students professionally manage different categories/types of assets, bearing in mind the principles acquired at the previous lectures.


Upon the completion of the course, students write a thesis. The field of research within the thesis can be prompted by the institutions sponsoring the program which can indirectly benefit from such thesis when in the process of introducing or improving particular business areas and putting into practice certain projects.

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