Analysis and optimization of risk

Course: Systems and methods of decision making

Structural unit: Faculty of Computer Science and Cybernetics

Title
Analysis and optimization of risk
Code
ДВВ.02
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
3
Learning outcomes
Know the essence of the category "risk" and its main types. Know the basic methods of measuring and analyzing of risk. Know the main principles of risk management and optimization of its level.
Form of study
Full-time form
Prerequisites and co-requisites
Know: have a basic mathematical education, knowledge of basic concepts of mathematical and functional analysis, probability theory and mathematical statistics, programming, operations research, econometrics. Be able to: identify the main factors which determined of the real processes, select appropriate mathematical methods for their effective analysis and construction of formal models for this processes.
Course content
System analysis of the categories "uncertainty" and "risk", presentation of the basic methods of decision-making under uncertainties, modern approaches to optimization of risk and its management, examples of the risk control of the complex stochastic systems.
Recommended or required reading and other learning resources/tools
1. А.А. Voina. Lectures on the basics of statistics. Koszalin. PK. 2015. – 375 p. 2. А.А. Voina. Risk in financial processes and the methods of research of the conjuncture. – Koszalin. PK. 2009, – 446 p. 3. A.A. Lobanov, A.V. Chugunov. Encyclopedia of financial risk management. – М., 2007. – 880 p. 4. А.А. Voina. Economic risk. Mathematical models and control methods. – K., 2001. – 100 p. 5. M.M. Leonenko, Yu.S. Mishura, V.M. Parkhomenko, Ya.I. Yadrenko. Probabilistic and statistical methods in econometrics and financial mathematics. – К., 1995. – 380 p. 6. A.N. Shiryaev. Fndamentals of stochastic financial mathematics. – М., 1998. 7. А.А. Voina. Risk control in multidimensional insurance models // Journal of Computational and Applied Mathematics. № 2(95). 2007, P. 13 – 23.
Planned learning activities and teaching methods
Lecture, laboratory work, independent work.
Assessment methods and criteria
Test work, defense of laboratory work, exam.
Language of instruction
ukrainian

Lecturers

This discipline is taught by the following teachers

Alexander Andrejevich Voina
Applied Statistics
Faculty of Computer Science and Cybernetics

Departments

The following departments are involved in teaching the above discipline

Applied Statistics
Faculty of Computer Science and Cybernetics