Non-linear Option Pricing · Mathematics
Various algorithms and techniques to price derivatives: American options, Insurance, Stochastic volatility models.
A lot. This course teaches a lot and everyone I speak to learn a lot!! The course material is super interesting. It is very useful for someone with background in Python but want to excel in the language.
Longstaff-Schwartz algorithm for pricing different kinds of options, BSDEs, UMM, UVM, particle method for smile calibration
This course is difficult, but you won't regret taking it because of the brilliant instructors and what you will learn from it.
It covers Python code know-how, advanced topics on contract pricing.
Only take this class if you are comfortable with learning some advanced pricing algorithms. Evaluate yourself in terms of how well you receive challenges before enrolling on this course. You will either find yourself hating or loving this course purely depending on your ability.
Don't take it unless you are very interested in the topics provided
Non-linear problems arising in finance: both from a math and coding point of view -> the coding part really helps understanding the math. Really interesting homeworks
American option pricing Insurance pricing Regressions Stochastic Volatility
I learned about numerical simulations to different option types: American, multiple exercise, uncertain mortality, uncertain volatility, and stochastic local volatility. I learned about the theory behind these problems, from basics of stochastic processes to the Feynman-Kac formula. I also learned a lot of Python programming including how to perform regressions and how to vectorize my code.