# Corporate Risk Management

- Credits: 5
- Ending: Examination
- Range: 20sP
- Semester: summer
- Year: 1
- Faculty of Business Economics with seat in Košice

## Teachers

## Included in study programs

**Teaching results**

The aim of the course is to provide comprehensive concepts of risk management in companies for students. The course provides an overview and interpretation of tools to understand and master the theoretical and practical knowledge related to the identification, analysis, measurement, and assessment of risk. The course also focuses on use of new methods and tools of risk management for selection of appropriate strategies.

Knowledge:

The graduate will gain knowledge about corporate risk management. The knowledge covers development of risk management concepts, methods of risk identification and analysis, as well as models for risk measurement and risk assessment. Case studies analyses helps graduate to understand the basic strategies of risk management.

Skill:

The graduate will be able to create economic models using spreadsheets and apply mathematical and statistical tools to business processes. Skillset also encompasses mastering the probability theory and uncertainty estimation. Other abilities include identification, measurement, and assessment and management of corporate risks.

Competence:

The graduate will master the rules and procedures of creating economic models with elements of uncertainty and risk. They will master the process of design and assessment of economic models and simulations. The graduate will be able to provide recommendation for the transfer, reduction and elimination of risks and other economic problems.

**Indicative content**

Consultations:

Introduction to probability theory

Basic concepts of risk

Risk classification

Identification of risks in the company

Risk analysis

Risk assessment

Selection of risk variants

Risk management

Tree diagrams

Expert methods of risk assessment

Monte Carlo simulation

Methods of risk treatment

Other methods of risk reduction

Self-study:

Introduction to probability theory. Classical definition of probability.

Probability of Multiple Random Variables. Joint and union probability, probability of dependent and independent phenomena.

Conditional probability, Bayes' theorem.

Discrete random variable. Discrete distributions and their application in risk analysis.

Continuous random variable. Continuous distributions and their application in risk analysis.

Preparation for midterm exams I.

Use of MS Excel for economic analysis.

Creation of models using MS Excel.

Sensitivity analysis using MS Excel.

Scenario planning using MS Excel.

Monte Carlo simulation. Monte Carlo simulation procedure. Monte Carlo simulation in MS Excel.

Rules of decision-making in conditions of risk. Case Study I: Risk assessments using descriptive characteristics: percentiles, median, mode, skewness, sharpness.

Preparation for Midterm exam II.

**Support literature**

Elementary literature:

1. TKÁČ, M. - TKÁČ, M. Podnikové riziká I : posudzovanie a zaobchádzanie s rizikom. 1. vyd. Bratislava: Ekonóm, 2016. 202 s. ISBN 978-80-225-4330-9.

2. PELIKÁN Š. Pravděpodobnost: cvičení Pedagogická fakulta UJEP, 1996 – 137s

3. LEHMAN, Dale; GROENENDAAL, Huybert. Practical Spreadsheet Modeling Using@ Risk. CRC Press, 2019

4. TICHÝ, Milík. Ovládání rizika: analýza a management. Nakladatelství CH Beck, 2006.

5. FOTR, Jiří; HNILICA, Jiří. Aplikovaná analýza rizika. Praha, Grada Publishing, 2014.

6. SIVÁK, R., a kol. Riziko vo financiách av bankovníctve (5th vyd.). Bratislava: Sprint, 2018, 2.

Supplementary literature:

1. YOE, Charles. Principles of risk analysis: decision making under uncertainty (2 ed). CRC press, 2019.

2. LEHMAN, Dale; GROENENDAAL, Huybert; NOLDER, Greg. Practical spreadsheet risk modeling for management. CRC Press, 2011.

**Syllabus**

Consultations: Introduction to probability theory Basic concepts of risk Risk classification Identification of risks in the company Risk analysis Risk assessment Selection of risk variants Risk management Tree diagrams Expert methods of risk assessment Monte Carlo simulation Methods of risk treatment Other methods of risk reduction Self-study: Introduction to probability theory. Classical definition of probability. Probability of Multiple Random Variables. Joint and union probability, probability of dependent and independent phenomena. Conditional probability, Bayes' theorem. Discrete random variable. Discrete distributions and their application in risk analysis. Continuous random variable. Continuous distributions and their application in risk analysis. Preparation for midterm exams I. Use of MS Excel for economic analysis. Creation of models using MS Excel. Sensitivity analysis using MS Excel. Scenario planning using MS Excel. Monte Carlo simulation. Monte Carlo simulation procedure. Monte Carlo simulation in MS Excel. Rules of decision-making in conditions of risk. Case Study I: Risk assessments using descriptive characteristics: percentiles, median, mode, skewness, sharpness. Preparation for Midterm exam II.

**Requirements to complete the course**

Midterm written exams

Final written exam

Midterm evaluation:

midterm written exams - 40% of course (total points 40)

Final written exam:

final written exam - 60% of course (total points 60)

**Student workload**

participation consultation - 20 hours

preparation for consultation - 13 hours

self-study - 32 hours

preparation for midterm written exams - 28 hours

preparation for the final exam - 37 hours

Total: 130 hours

**Language whose command is required to complete the course**

Slovak

Date of approval: 11.03.2022

Date of the latest change: 13.05.2022