QF435 Risk Management for Capital Markets

Course Catalog Description


Risk Control and derivative pricing are major concerns for financial institutions. Yet, as recent events have shown us there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial market. Many of the standard models seen on Wall Street however are based on simplified assumptions and can lead to systematic (and sometimes dramatic) underestimation of real risks. Starting from a detailed analysis of market data, one can take into account more faithfully the real behavior of financial markets (in particular the ‘rare events’) for asset allocation, derivative pricing and hedging, and risk control. This course will introduce some concepts to better address these issues. There will also be a few sessions in the Hanlon lab learning to use a Bloomberg terminal.

Various financial instruments will be presented in a form familiar to Wall Street traders (i.e. Bloomberg screens). The purpose of Risk Management is to provide a valuation of these financial contracts ("pricing") and to provide various measures of risk and methods to hedge these risks as best as possible ("hedging"). These tasks are not just performed by "Risk Managers" but by "Traders" who price and hedge their respective trading books on a daily basis. Successful trading (over extended periods of time) comes down to successful risk management. Successful risk management comes down to robust valuation which is the main prerogative of Financial Engineering. Valuation of financial instruments begins with an analysis of possible future events (i.e. stock price moves, interest rate moves, defaults, etc.). Dealing with the future involves the mathematics of statistics and probability. The first step is to find a probability distribution that is suitable for the financial instrument at hand. The next step is to calibrate this distribution. The third step is to generate future events using this calibrated distribution and based on this, provide the necessary valuation and risk measures for the financial contract at hand. The failure of any of these steps can lead to incorrect valuation and therefore an incorrect assessment of the risks of the financial instrument under consideration.

Campus Fall Spring Summer
On Campus X X
Web Campus


Professor Email Office
Thomas Lonon
Tlonon@stevens.edu Altorfer 303

More Information

Course Outcomes

By the end of this course, the students will be able to:

  1. Market Quotes of Major Asset Classes
  2. Risk Types of Major Asset Classes
  3. Statistical Analysis of Financial Data for Risk Management
  4. Stochastic Processes and Risk Measures (VAR, CVAR)

Course Resources


Practical Methods of Financial Engineering and Risk Management, Stevens Quantitative Finance Series, Rupak Chatterjee, Apress-Springer, 2014.

Additional References



Grading Policies

Assignments: There will be weekly homework assignments throughout the semester, with problems inspired from your textbook and on necessary skills.

The assignments and their weights are as shown below:

  • Homework - 30%
  • Midterm - 30%
  • Final Exams - 35%
  • Attendance - 5%
  • TOTAL - 100%

Attendance will be an all or nothing grade. If you are unable to attend at least 80% of the classes (barring medical emergencies with doctor's notes) you will receive a 0 for your attendance score.

Please note that your grade will be determined solely on the work you present over the course of the semester. No consideration such as your desire for a better grade for academic standing or job offers will be considered.

Extra Credit: On some of the homework assignments and possibly on the exams, there will be the occasional extra credit problem. This is the only source of extra credit for the course. There are no "extra assignments" that students can do to raise their average outside of the ones assigned. There are no exceptions, don't even bother coming to me and asking about extra work at the end of the semester, as I will only direct your attention to this part of the syllabus.

Extensions and Re-submits It is my policy to never give a student an extension after a deadline is missed. You know before you actually miss a deadline that you will miss the deadline. If you reach out to me before an assignment is due and let me know why you will miss the deadline, if its a valid reason (and this does not have to include medical issues, I realize that sometimes life just gets in the way) I have no problem providing an extension if necessary.

I will under very rare circumstances allow a student to re-submit an assignment that has already been submitted, but it is my policy to not allow a re-submit of an assignment once it has been graded. Once the assignment has been graded, you now possess much better information than the average student and it is therefore unfair to the others in the class to allow this.

Lecture Outline

Topic Reading
Week 1 Financial Instruments Chapter 1
Week 2 Future Swaps and Building a Yield Curve Chapter 1 & 2
Week 3 Derivatives Chapter 1
Week 4 Probability Theory Chapter 3
Week 5 Creating Variables and Distributions Chapter 3
Week 6 Calibrating Distributions and Basic Risk Measures Chapter 3
Week 7 Term Structures and Dynamic Portfolio Allocation Chapter 3
Week 8 Midterm
Week 9 Stochastic Calculus Chapter 4
Week 10 Geometric Brownian Motion and Monte Carlo Chapter 4
Week 11 GARCH Chapter 4
Week 12 Trading Strategies Chapter 4
Week 13 Optimal Hedging Monte Carlo Methods Chapter 5
Week 14 Chapter 5 and Review