1) Prerequisites:

1. Mathematics: A good mathematical foundation in calculus, probability, and statistics is essential. This includes understanding stochastic processes, differential equations, and Fourier transformations.
2. Finance: Basic understanding of financial markets and instruments. Knowledge about trading, hedging strategies, and risk management would be beneficial.
3. Programming: Competency in Python is necessary as the course involves simulation and implementing financial models in Python.
4. Economics: While not strictly necessary, understanding macroeconomics can provide helpful context for the movements of financial markets.
5. Previous coursework: A Basic course in financial mathematics would be beneficial.

2) Aim of the course: 

The “Computational Finance” course empowers students with the mathematical, statistical, and computational skills necessary to navigate the complex world of financial markets. It aims to demystify the intricate structure of financial instruments and the sophisticated models used to price them. Through this course, students will explore the heart of financial markets, exploring options trading, hedging strategies, and asset price modelling. Using various mathematical models, they will learn to simulate stock price movements and calculate implied volatility and price options. The course introduces students to advanced concepts such as stochastic volatility models, Fourier transformations for option pricing, and Monte Carlo simulation. It further explores exotic derivatives and provides hands-on experience with hedging strategies. This course is a journey into the fascinating world of computational finance, providing students with the knowledge and tools to tackle real-world financial problems using Python. It’s not just about learning theories but about equipping oneself with the skills to create, innovate, and lead in the finance industry.

3) Rules about Homework/Exam

Two hand-in exercise lists, one per quarter; individual project and written or oral examinations, depending on the number of course participants. 

The final grade is a weighted grade from homework submissions (20%), individual projects (30%), and the exam (50%). A minimum grade of 5 on the exam is required to pass the course.

4) Lecture notes/Literature

- The course is based on the book: "Mathematical Modeling and Computation in Finance: with Exercises and Python and Matlab Computer Codes", 2019. C.W. Oosterlee & L.A. Grzelak. World Scientific Publishing Co. Pte. Ltd., ISBN: 978-1-78634-794-7.
- Lecture slides will be provided during the course.
- The supplementary pre-recorded lectures are available on youtube

5) Lecturers

- dr.ir. L.A. Grzelak, https://www.uu.nl/medewerkers/LAGrzelak

- prof.dr.ir. C.W. Oosterlee, https://www.uu.nl/medewerkers/CWOosterlee