GRA 6513 Financial Risk Management

GRA 6513 Financial Risk Management

Course code: 
GRA 6513
Course coordinator: 
Adam Walter Winegar
Course name in Norwegian: 
Financial Risk Management
Product category: 
MSc in Finance
2024 Spring
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

This course provides an introduction to derivatives and risk management with a focus on applications to financial firms. The remarkable growth in the use of financial derivative instruments for risk-management combined with their increasing complexity makes the basic understanding of derivatives and their applications essential for both students and specialists in finance, as well as general business practitioners. Moreover, risk management is a key area of focus for creating sustainable firms in a changing business environments, especially as firms become more internationally focused.

The objective of this course is to provide students with an understanding of financial risk management. Specifically, we will focus on questions such as: why financial institutions (and non-financial corporations) should manage their financial risks; what risks firms, especially financial institutions, face; and what tools they use to do so (mainly derivative securities). The course will give a brief overview of the valuation and the use of derivatives for risk management, as well as insights into hedging decisions, motivations, and the different types of risks financial firms face (e.g., market, liquidity, and credit risks). In addition, the course will explore how firms measure and managing their financial risks by utilizing computer simulation tools (e.g., via R or Python). We will also examine how regulations specific to financial institutions affect their risk management practices. The course will contain both theory and examples/cases of risk management applications. Overall, students should leave the course with the ability to understand the causes of past failures and have the ability to prevent them in the future. Another primary goal of this course is to allow students an opportunity to apply their theoretical knowledge and skills gained in prior courses to various real-world applications.

The course starts with an overview of how risk management adds value. It then covers the valuation of derivatives and the markets in which they trade, including the valuation of the most common derivative securities (e.g., forwards, swaps, and options). With the knowledge of these fundamental tools, the course then delves into measuring and managing the various types of risks faced by financial institutions, including market, credit/counterparty, and liquidity risks. Emphasis is placed on building models using statistical tools and software packages (e.g. Python or R) and applying them to real world cases. Throughout the course, students will explore financial crises and failures of major financial institutions as well changing financial regulations. Students will utilize these examples as way to learn from the past to create more sustainable financial institutions in the future.

Learning outcomes - Knowledge

This course will give students an understanding of the tools and practices of financial risk management. The students at the end of the course are expected to know:​

  • Fundamentals of derivative markets, the valuation of derivative securities, and how to implement hedging strategies using derivative portfolios (e.g., forwards, swaps, and options)
  • Understand key risks that financial institutions face including market, credit, and liquidity risks
  • What causes failures of financial institutions including how risk management failures can lead to international financial crises
Learning outcomes - Skills

The students at the end of the course are expected to be able to:

  • Value plain vanilla forwards, futures, options and swaps with standard methods and Monte Carlo simulations
  • Estimate common risk measures (e.g., Value-at-Risk and Expected shortfall) and the effects of risk management tools (hedges) using historical simulations and Monte Carlo simulations via computer tools (e.g. Python or R)
  • Model financial institutions portfolios based on simulations of changing market conditions
General Competence

The student should be able to critically think about how risk management adds value for various financial and non-financial corporations in order to create sustainable practices in modern businesses. This includes the knowledge of available instruments and measures, their use in practice, and their individual strengths and limitations.

Course content

Part I: Introduction and Derivatives

  1. How risk management adds value
  2. Valuing of forwards, futures, options and swaps
  3. Derivative markets

Part II: Risk Management

  1. Managing market risks
  2. Modeling and measuing risk (e.g., Volatility, Value-at-Risk, and Expected Shortfall)
  3. Financial Crises and Regulations
  4. Credit risk, default probabilities and value adjustments
  5. Liquidity Risks
  6. Corporate risk management
Teaching and learning activities


  1. Lectures - Lectures by the instructor are key to providing the students the theory and concepts of risk management as well as the tools of risk management. During lectures multiple real-world examples and problems will be shown and worked-through for students to gain the necessary skills. Finally, we will have occasionally have guest lectures to highlight how modern companies use risk management.
  2. Discussion - News and academic articles will be discussed as a larger group in order to encourage students to recognize and critically think about the implementation of risk management in modern companies. We will also discuss several cases that highlight risk management failures and successes. Finally, we will occasionally utilize in-class simulation exercises (e.g., trading games) that allow students to apply and test their knowledge of derivative markets.
  3. Videos and Other Digital Activities - We will utilize videos, both internally and externally produced, to expand on topics from lecture, provide additional content, and highlight risk management topics (e.g., the financial crisis of 2008). In addition, we will go through in-class applications of digital tools including Python/R and Excel. This will allow students to further hone their programming and modeling skills in a supervised environment.

Excercises and Assignments

  1. Group Assignments - A primary way to evaluate student's learning will be the use of group assignments, this is especially true for topics that are unable to be evaluated in an exam setting (e.g, the use of software tools). Students are given the opportunity to value derivative securities, discuss how risk management adds value, and model hedging strategies and risk measures in real-world cases. Students use digital tools (e.g., Python/R) and multiple estimation methods (e.g., Monte Carlo) in order to complete the assignments, giving them a practical implementation of their knowledge regarding models, estimation, and software. Finally, the assignments allow students to work together in a team environment creating useful practical skills in writing, time management, and coordination.
  2. Practice Problems - Outside of group assignments students are also given numerous practice problems in order to self-assess their own learning. These are provided at the end of each major topic and generally consist of select questions from the primary textbooks as well as mock exams.


  • A majority of the assessment of the students' learning will come from a written exam. The exam will evaluate the knowledge, skills, and general competencies of the students. This will include how risk management adds value, the theory and application of derivatives pricing and markets, understanding of financial failures and crises, basic calculations of risk measures, the various risks financial institutions face, and the application of risk management tools.
Software tools
Software defined under the section "Teaching and learning activities".
Additional information

The exam for this course has been changed starting academic year 2023/2024. The course now has two exam codes instead of one. It is not possible to retake the old version of the exam. Please note new exam codes in the Exam section of the course description. 

It is the student’s own responsibility to obtain any information provided in class.

Honour Code
Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honour code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honour code system, to which the faculty are also deeply committed. Any violation of the honour code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honour code and academic integrity. If you have any questions about your responsibilities under the honour code, please ask.


All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.


Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Exam category: 
Form of assessment: 
Written submission
Group (1 - 5)
1 Semester(s)
Submission due 2 weeks after the end of classes.
Group size may vary due to class size and other considerations.
Exam code: 
GRA 65132
Grading scale: 
Examination when next scheduled course
Exam category: 
Form of assessment: 
Written submission
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
3 Hour(s)
Final written examination under supervision
Exam code: 
GRA 65133
Grading scale: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight: 
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.