PORTFOLIO MANAGEMENT

Course: Economic analysis and statistics

Structural unit: Faculty of Economics

Title
PORTFOLIO MANAGEMENT
Code
3.2.1.7
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
5
Learning outcomes
To develop, substantiate and take effective decisions for development of social-economic systems and management of economic subject`s activity (program`s result «ПРН 2») To collect, process and analyse statistical data information, scientific and analytical materials, which are necessary for solution of complex economic tasks (program`s result «ПРН 8») To identify and critically assess conditions and tendencies of social-economic development, to form and analyze models of economic systems and processes (program`s result «ПРН 11») To ground management decisions of economic entities development considering goals, resources, constraints and risks (program`s result «ПРН 12») To assess potential risks, social-economical consequences of management decisions program`s result «ПРН 13»
Form of study
Prerequisites and co-requisites
• Successful learning courses «Investments», «Risk Theory», «Statistics», «Prodability Theory for Economists». • Knowledge of investment processes, financial markets functioning, methods of statistical analysis, proficiency in building of economic-mathematical models
Course content
The academic discipline is designed around three subject modules: Module I. A Framework for Portfolio Management Module II. Portfolio Management: Traditional and Alternative Assets Module III. Hedging Portfolio and Performance Evaluation Each module consists of a relatively independent part of the course and aims at meeting specific goals and learning objectives. Thus, Module I is focused on exploring modern environment of portfolio management process. Also, this module aims to teach students techniques of creating IPS (Investment policy statement) for individual and institutional investors, analyzing “risk-return” correspondence for investment opportunities, and using different techniques for handling data.
Recommended or required reading and other learning resources/tools
Planned learning activities and teaching methods
Assessment methods and criteria
Assessments structure - During semester (max scores 80 / min scores 48) 1. Fulfilling laboratory works – totally 8 laboratory works during the course. Each laboratory work estimated by scores in range 0-5. Maximum scores are 40. Minimum acceptable is 24 scores. Laboratory works 1-4 form grades for Module 1, laboratory works 5-8 form grades for Module 2. 2. Tests and participation in discussions of case studies during semester include 20 + 20 = 40 (max) scores which form Module 3 grade (Minimum acceptable is 24 scores).
Language of instruction
English

Lecturers

This discipline is taught by the following teachers

Andrii Borysovych Kaminsky
Department of Economic Cybernetics
Faculty of Economics

Departments

The following departments are involved in teaching the above discipline

Department of Economic Cybernetics
Faculty of Economics