FE535 Introduction to Financial Risk Management
Course Catalog Description
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 indepth 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 realworld examples, students will learn how to implement risk management strategies effectively. To reinforce learning and facilitate practical application, the course includes two miniprojects. These projects are designed to give students handson experience in applying the concepts and techniques learned in class to realworld data and scenarios, enhancing their problemsolving and analytical skills
Campus  Fall  Spring  Summer 

On Campus  X  X  
Web Campus  X  X 
Instructors
Professor  Office  

Majeed Simaan  msimaan@stevens.edu  Babbio 629 
Anthony Diaco  adiaco@stevens.edu 
More Information
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, inclass labs, and applied projects utilizing realworld 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:
 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.
 Model Risk using Stochastic Processes: Develop and apply stochastic models to simulate financial risks for assessment and management
 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.
 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.
 Apply Derivatives for Linear and NonLinear Risk Management: Utilize derivatives, including options and futures, to manage both linear and nonlinear 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
SelfAssessment
At the beginning of the class, a quantitative selfassessment 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 selfreflection, allowing students to evaluate their understanding of the material. It is important to note that this selfassessment 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 selfassessment as a tool to identify any areas where they may need to focus additional attention, ensuring they are wellprepared to embark on the journey of financial risk management.
Course Resources
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 (McGrawHill) 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)) )
HANDOUTS
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 miniprojects. These, however, will only serve as a complement to the textbook and should not, by any means, be treated as a substitute.
Grading
Grading Policies
Type  Weights  Notes 

Exam I  30%  Exam I will consist of multiplechoice and openended questions, spanning all topics covered during the first half of the course. 
Exam II  30%  Exam II will consist of multiplechoice and openended questions, spanning all topics covered during the second half of the course. 
MiniProjects  20% 
There will be 2 miniprojects over the semester. Each
submission counts as 10 points of the final grade. The
projects will be completed and graded as a team. For each
project, a presentation is required.
Presentation: upon submission, teams are expected to present their work and highlight individual contribution and synergy. Each presentation counts as 5 points and will be graded on the individual level. Note: the assignments will require computation and working with data. I will provide handouts and tutorials on this. These will be mainly conducted using R. Nonetheless, teams are welcome to use any other programming language or statistical software. However, my contribution is limited to R. 
Labs  10%  We will have multiple labs during classes. The purpose of these is to encourage discussion among the team members and apply recently learned topics. The labs will require some computer computations. Hence, the students are encouraged to work with their laptops. 
Participation  10%  Discussions are highly encouraged, including class
attendance and general participation. Additionally,
attendance will be taken over the course of the semester.
The class will integrate DataCamp (DC) as part of the programming process. There will be multiple assignments over the semester that will count as part of your class participation. 
Lecture Outline
Week  Topic  Reading  Assignment 

Week 1  Intro to Risk Management  Ch. 1 from Jorion
Recommended: Ch.1 from Hull 

Week 2  Portfolio Theory and CAPM  Ch. 1 from Jorion
Recommended: Ch.1 from Hull 
Refresh your probability and statistics knowledge: read Ch. 2 and Ch 3 from Jorion 
Week 3  Modeling and Simulation: Law of Large Numbers  Ch. 4 from Jorion
Recommended: Ch. 7 from Hull 

Week 4  Modeling and Simulation:Brownian Motion (BM)  see above  Lab 1 Due 
Week 5  Calibration of Geometric BM and application to RM  see above  Lab 2 Due 
Week 6  Introduction to Bonds, Time Value of Money  Ch. 6 from Jorion  Lab 3 Due 
Week 7  Exam I  Exam I Week  
Week 8  Interest Rate Risk  Project 1 Update  
Week 9  Introduction to Derivatives  Ch. 7 from Jorion
Recommended: Ch. 5 from Hull For further information on the OTC market refer to Ch 18 from Hull 

Week 10  Introduction to Derivatives II  see above  Project I Due 
Week 11  Managing Linear Risk  Ch. 13 from Jorion
Recommended: Ch.8 from Hull 

Week 12  Managing Linear Risk II  see above  
Week 13  Thanksgiving Recess; No Classes Project 2 Update  
Week 14  Option Markets  Ch. 8 from Jorion Recommended: Ch. 8 from Hull  Lab 5 Due 
Week 15  Managing NonLinear Risk  Ch. 14 from Jorion Recommended: Ch. 8 from Hull  Lab 6 Due 
Week 16  Exam II Week  Project 2 Due 