Introduction

This course offers a comprehensive exploration of risk modeling and management, structured to align closely with the GARP curriculum of the Financial Risk Manager (FRM) with a primary focus on Part I. Students will embark on a detailed journey through the essential concepts and methodologies that form the foundation of modern financial risk management.

• The course starts with an in-depth review of the Foundations of Risk Management, where students will gain insights into risk types, risk control, portfolio and asset pricing theory, and the role of risk management in the financial industry. This sets the stage for exploring Quantitative Analysis, where students will learn to apply statistical techniques and models critical for measuring and managing risk effectively
• The course then delves into Financial Market Products, with a particular emphasis on derivatives, options, and other financial instruments used in the markets today. Students will study the mechanics, pricing, and strategic use of these products in risk management. In this exposition, the course will also introduce Valuation and Risk Models, providing students with the tools needed to assess and manage the risk associated with financial assets and portfolios.

A significant portion of the course will be dedicated to Market Risk, focusing on the practical application of derivatives to hedge and manage risk in financial markets. Through detailed case studies and real-world examples, students will learn how to implement risk management strategies effectively. To reinforce learning and facilitate practical application, the course includes two mini-projects. These projects are designed to give students hands-on experience in applying the concepts and techniques learned in class to real-world data and scenarios, enhancing their problem-solving and analytical skills

Course Outcome

The course aims to equip students with a deep understanding of the core financial concepts and analytical tools essential for effective risk management. Through a blend of lectures, discussions, in-class labs, and applied projects utilizing real-world data and computational methods, students will develop both the theoretical knowledge and practical skills necessary to think and act as professional risk managers. This course also aims to provide a thorough understanding of various topics covered in the FRM Part I, offering students a comprehensive foundation that will aid in their exam preparation and professional development. By the end of this course, students will be able to:

After successful completion of this course, you will be able to:

1. Identify and Manage Different Types of Risk: Distinguish between different types of risk, such as model risk, market risk, and credit risk, and implement appropriate risk management techniques.
2. Model Risk using Stochastic Processes: Develop and apply stochastic models to simulate financial risks for assessment and management
3. Use Statistical Analysis for Risk Pricing and Management: Employ statistical tools and techniques to analyze financial data, focusing on pricing risk and implementing risk management strategies.
4. Understand Different Types of Asset Classes and Derivatives: Gain a solid understanding of various asset classes, including equities, fixed income, and derivatives, and how they are used in risk management.
5. Apply Derivatives for Linear and Non-Linear Risk Management: Utilize derivatives, including options and futures, to manage both linear and non-linear risks in financial portfolios.

PREREQUISITES

Quantitative Background:

• A solid understanding of probability, statistics, and calculus is assumed. This includes knowledge of probability distributions, expectation, variance, covariance, conditional probability, independence, etc.
  • "Introduction to Probability" by Grinstead and Snell is a great publicly available resource, which is available via this link (https://stats.libretexts.org/Bookshelves/Probability_Theory/Book%3A_Introductory_Probability_(Grinstead_and_Snell)) .
• Calculus skills involving derivatives, partial derivatives, optimization (finding maxima/minima), and Taylor series are important. Some familiarity with integrals is also expected.

Linear Algebra

• Proficiency in solving systems of linear equations is important
• Comfort with matrix operations, including addition, multiplication, transposition, and matrix inversion, is necessary.

Programming Knowledge:

• While the course tasks can be completed using tools like Excel, having programming knowledge will be highly beneficial. The course specifically focuses on R coding.
• Students are expected to be open to learning and using programming to solve financial risk management problems.
• The course will provide learning materials and handouts to help students learn programming, particularly in R

Self-Assessment
At the beginning of the class, a quantitative self-assessment is shared with the students (see file FE_535_Quant_Assessment.pdf under the Notes Moldule)

• The assessment includes a set of quantitative questions designed to gauge student's familiarity with foundational concepts essential for this course.
• Each question offers an opportunity for self-reflection, allowing students to evaluate their understanding of the material. It is important to note that this self-assessment is intended solely for personal evaluation and does not require the submission of responses or answers. The primary goal is to help students determine their readiness to engage with the course content effectively.
• Students are encouraged to use this self-assessment as a tool to identify any areas where they may need to focus additional attention, ensuring they are well-prepared to embark on the journey of financial risk management.

Textbook

Financial Risk Manager Handbook, + Test Bank: FRM Part I / Part II 6th Edition by Philippe Jorion

Additional References

Risk Management and Financial Institutions (Wiley Finance) 4th Edition by John C. Hull

The Economic Foundations of Risk Management: Theory, Practice, and Applications by Robert A. Jarrow

The Essentials of Risk Management (McGraw-Hill) 2nd Edition by Michel Crouhy, Dan Galai , and Robert Mark

Risk Management and Simulation by Aparna Gupta

Mathematics and Statistics for Financial Risk Management by Michael B. Miller

Introduction to Probability by Charles M. Grinstead and Laurie Snell (publicly available (https://stats.libretexts.org/Bookshelves/Probability_Theory/Book%3A_Introductory_Probability_(Grinstead_and_Snell)) )

A set of handouts/lecture notes will be given as the course progresses. These handouts will be very useful for conducting computations and addressing the underlying tasks from the mini-projects. These, however, will only serve as a complement to the textbook and should not, by any means, be treated as a substitute.

Grading Policies