I hope you are all still motivated to continue with the Computational Finance course. Today I would like to share Lecture no 5 (out of 14).
Today we will discuss the concept of Jumps in the modelling of stock prices and option pricing.
Python codes and the Lecture slides you can find in the link in the description of the lecture.
Content of today’s lecture is as follows:
5.1. Inclusion of Jumps in the Stock Process
5.2. Poisson Process and Implementation in Python
5.3. Ito’s Lemma and Jumps
5.4. Jumps and Asset Dynamics under the Q-Measure
5.5. Partial Integro-Differential Equations
5.6. Different Jump Distributions and Implied Volatility
5.7. Expectation and Jump Processes
5.8. Characteristic Function for a Jump Process
—–>Lecture 5- Jump Processes
Lecture 6- Affine Jump Diffusion Processes
Lecture 7- Stochastic Volatility Models
Lecture 8- Fourier Transform for Option Pricing
Lecture 9- Monte Carlo
Lecture 10- Monte Carlo of the Heston Model
Lecture 11- Hedging and Monte Carlo Greeks
Lecture 12- Forward Start Options and Model of Bates
Lecture 13- Exotic Derivatives
Lecture 14- Summary