Introduction

The main goal of a student enrolled in FE621 is to obtain essential computational tools used in the financial industry by modern financial quantitative analysts. The students are to become familiar with such methods as stochastic processes approximation, approximation for solutions to PDE’s, decision methods, and simulation. The purpose is to learn to apply the results to forecasting, asset pricing, hedging, risk assessment, as well as other financial problems. Students must have a strong mathematical background (FE543/FE610), and be familiar with derivatives terminology and concepts at the level of Hull’s textbook (FE620).

The course is split in modules and each module will cover theory and test the student’s knowledge on developing and implementing algorithms to solve real problems.

Course Materials

Class notes will be posted on Canvas. The topics covered can be found in a variety of textbooks and other online sources, such as

1. L. Clewlow and C. Strickland. Implementing derivative models, Wiley, 1998
2. P. Glasserman. Monte Carlo methods in financial engineering, Springer, 2003.
3. A. Hirsa. Computational methods in finance, Chapman & Hall, 2012.
4. M. Mariani and I. Florescu. Quantitative Finance, John Wiley & Sons, 2019
5. J. Hull. Options, futures, and other derivatives, Prentice Hall, 2014

Grading Policies

Grades – Please submit ALL work using pdf format The final grade will be determined upon the student’s performance in the course. We will have multiple assignments and quizzes throughout the course. Most of the grade will be coming from the in class midterm as well as from the final. The work tends to be programming intensive so an early start is necessary especially if there are gaps in your programming skills. Only use the .pdf format for submitting assignment files. You should be able to transform any document into a pdf file. You can use Adobe acrobat - should be free to Stevens students as far as I know (please call the students help desk), or a simple alternative: use a pdf printer driver. I write all my documents in LATEXand that typesetting program produces pdf files. Generally the grade distribution follows the following percentages.

• Assignments 30%
• Midterm 25%
• Midterm 40%
• Midterm 5%

Assignment submission guidelines

Late assignments will not be accepted under any circumstances without prior notice and permission of the instructor. If outside circumstances are affecting your ability to perform in the course, you must contact your instructor before you fall behind. It is recommended to notify at least 24 hours before due.

1. Present your solutions in a clear and readable manner. Please write complete sentences, highlight final answers, explain your reasoning etc. Submitting code without any interpretation of results will be severely penalized.
2. Make sure the TA does not have to search through multiple pages of code in order to find your results
3. You can discuss problems with other students but you must solve, write, and submit your own solution. Please see the Graduate Student Code of Academic Integrity.
4. You are not allowed to use solutions of former students, or plagiate online sources, including the output of generative AI technologies.