Starting April 27th, new courses will start within Master’s in Economic Analysis and Masters program in Business and Financial Economics.

This program is taught exclusively in English by faculty of western Ph.D. economists, professors with MBA degrees, and top business Practitioners.

The courses within the Masters program in Business and Financial Economics gives fundamental economic and financial knowledge and skills essential for a successful career in data-driven business analysis and focuses on fundamental economic and financial knowledge and skills essential for a successful career in data-driven business analysis.

Corporate Finance (Andriy Drobot)

In the modern corporation creating wealth for its shareholders is key to their operation and development.

Financial theory and models are closely linked with economic theory, because both are concerned with allocating resources. Accounting theory is concerned with the recording of the financial events of organizations and is therefore an important link between the financial and economic disciplines.

The aim of this teaching program is to provide opportunities to explore and develop an understanding of the financial principles and models which are fundamental to making informed decisions in organizations of different shapes, sizes and motives.

On completion of the course, students should be able to:

• understand key financial principles and models applied to decision making;
• identify and critically analyze the objectives of management of incorporated companies;
• be aware of, and apply techniques of, capital investment appraisal and the generation of
• relevant cash flows;
• use financial principles and models for managing working capital;
• critically evaluate the issues relevant to financing business activity.

Real Economy (Simone Raudino)

This course provides an overview of the role of capital markets and the financial industry in the working of capitalist economies, liberal governments and international relations.

To do so, the course:

• Introduces the history, theory, mechanisms, tools and finalities of corporate and public finance;
• Places the role of the financial industry in the broader environment of macroeconomic and
• microeconomic;
• Analyses the relationship between the financial economy and the real economy.

The course has four goals:

– To provide students with a comprehensive and evolutionary (e.g. historical)

understanding of the key players, functions and mechanisms of financial markets;

– To present an overview of the theories and methods used in the financial industry;

– To allow students a critical appraisal of the role of the financial industry in the workings

of liberal economies, and of the relationship between finance and the broader public purpose;

– To enable students to reach an adequate level of sophistication on current issues and

concerns in financial, monetary, fiscal and regulatory policies. Such level of

sophistication is necessary to understand the role of finance in debates over economic,

public policy and international relations.

Last but not least, to have fun – finance and economics provide wonderful learning opportunities

on broader social science subjects, including anthropology, psychology, sociology, political

science and international relations.

Data collection and analysis (Maksym Obrizan and Tymofii Brik)

The main purpose of this course is to learn tools for automatic data collection (primarily, in R and Python).

Maksym will teach the first half of the course (focusing on R) starting with business, economic and financial applications of web scraping together with related ethical considerations.

Then we will study simple tools for data collection and analysis which do not require programming skills: Excel, Power BI and OpenRefine.

Finally, we will consider automated data collection in R with numerous applications.

The Python part will introduce handy tools of working with complicated data structures that come in different formats. We will focus on the advantages of Beautiful soup. Another key feature that makes Python popular among scholars and practitioners is a simple toolkit for the natural language processing. Throughout the duration of the course student will work in groups on their assignments. The course will expand the knowledge of R and Python obtained in the first two courses in the sequence.

Students are expected to bring a laptop to class (as a lot of class time will be spent in a “lab” style) with all necessary programs installed.

The courses with the Master’s in Economic Analysis program offers unique skills in economic and financial modeling and analysis, and it is an ideal preparation for positions that require a high level of analytical sophistication like research-oriented and analytical functions in international organizations or businesses, as well as for further study at international Ph.D. Programs.

Microeconomics IV: General Competitive Equilibrium Analysis and Market Failures (Oleg Nivievskyi)

This fourth part of the microeconomic sequence is the most interesting one from the real world’s point of view. The partial equilibrium models studied before are inadequate to analyze interconnected markets, and markets are in reality interconnected.

To be able to view several markets simultaneously, general equilibrium models are introduced. AL locational efficiency in exchange economies and economies with production is investigated.

We will also look at a number of allocation problems caused by the existence of public goods and externalities. A short introduction to the theory of public choice will be provided.

Macroeconomics IV: Monetary Economics (Elena Besedina)

This course is the last in the Macroeconomic sequence. First, we will consider the Keynesian view of fluctuations (IS-LM model). In this course, we will introduce dynamics in the static models.

Students will learn how expectations are formed and how they affect equilibria in the models. In particular, on the example of cobweb model and IS-LM model the students will study the price dynamics in the under different expectations hypotheses, including static expectation, adaptive expectations, rational expectations and adaptive learning.

The second half of the course is devoted to the price stickiness, inflation and monetary policy.

Learning outcomes

1.  Students will learn about IS-LM model
2.  Students will learn about expectations formation
3.  Students will be able to solve dynamic models under static and adaptive expectations
4. hypotheses
5.  Students will be able to solve models with rational expectations using two methods: (1)
6. undetermined coefficients and (2) repeated substition
7.  Students will learn about monetary policy rules.

Mathematics for Economists IV: Linear and Nonlinear Dynamics (Iryna Sushko)

Studies related to Nonlinear Economic Dynamics have recently become more prominent both in micro- and macroeconomics. The mini-term IV means to introduce students to the theory of Nonlinear Dynamical Systems and show how its tools and methods are used in the investigation of dynamic economic models.

The goal of this mini course is to present several important notions and ideas from this theory in a setting that is as simple as possible. Specifically, we shall first recall some basic elements of the theory of Linear Difference Equations, then we turn to the theory of Nonlinear Difference Equations, namely, one- and two-dimensional maps, including such topics as stability, bifurcation theory and routes to chaos.

The only prerequisite for the course is a standard background in calculus and linear algebra.

Duration and format of courses:

Classes are held daily twice a week.

Teaching semester lasts 8 weeks from April 27th to June 19 th 2020.

Upon completion of the course, each participant will receive a certificate.

Cost of one course: 6000 UAH

Program Manager: Mariia Pashkova, [email protected], +38 050 522 20 58