İŞL461

School of Economics and Administrative Sciences \ Business Administration

3

6

Compulsory

English

İŞL361 or İŞL161

Management

This course provides a detailed understanding of the principles of risk management for financial and non-financial institutions. The course begins by analysing the main types of risk encountered in financial markets such as market risk, credit risk, interest rate risk, foreign exchange risk and operational risk. Risk measurement, hedging with appropriate instruments and techniques, risk management policies, and the use of financial derivatives in risk management are also covered. Students learn risk measurement methods such as Value at Risk (VaR), Duration, Return on Capital Adjusted Risk (RAROC) and Stress Testing. The course is supported by case studies and practical examples to provide students with a solid foundation in financial risk management.

1. Financial Institutions Management: A Risk Management Approach – Saunders and Cornett, Irwin/McGraw-Hill; 4th edition
2. Options, Futures and Other Derivatives – John C. Hull, Prentice Hall; 9th edition
3. Risk Management and Financial Institutions – John C. Hull, Prentice Hall

To teach financial risk management concepts and methodologies in a comprehensive manner,
To gain the ability to measure and manage different types of risk such as market, credit, interest rate and operational risk,
To analyse financial regulations and their effects on risk management,
To provide the ability to apply financial modelling and analytical tools in risk management decisions.

1. Knows the types of risks encountered in financial markets and how they are measured.
2. Know the principles and stages of financial risk management from the perspective of financial institutions and companies.
3. Know appropriate hedging and risk management approaches.
4. Know the use of derivative instruments in risk management.
5. Knows BASEL applications and BRSA regulations for financial institutions and can follow the changes.
6. Knows the usage areas of artificial intelligence and machine learning models in financial risk management.
7. Knows financial data platforms, knows how to access, analyse and interpret financial data through the platform.

Week 1: Course Introduction and Introduction to Risk Management
Week 2: Interest Rate Risk
Week 3: Interest Rate Risk - Duration Model
Week 4: Market Risk, Refinitiv Training
Week 5: Market Risk
Week 6: Exchange Rate Risk
Week 7: Midterm Exam, Credit Risk
Week 8: Credit Risk
Week 9: Operational Risk and Technological Risks
Week 10: Financial Regulations and Risk Management: BASEL Standards, BRSA Regulations, Refinitiv Training
Week 11: Machine Learning Models in Risk Management
Week 12: Case Analysis

• Midterm 30 %
• Final 40 %
• Case Analysis Report and Discussion 15 %
• Refitiniv Homework 15 %