Welcome to the repository for the code developed as part of my Bachelor's thesis. This code accompanies my thesis titled "Lookback Option Pricing with the COS Method".
In this repo you will find the following folders:
- density_approximation: an early demonstration of the COS Method Density approximation procedure
- montecarlo: a demonstration of monte carlo density approximation for lookback options
- option_pricing: the implementation of the cos method for european and lookback option pricing as in chapter 3 of my thesis
- option_pricing_extended: the implementation of cos method lookback option pricing via the spitzer recursion algorithm, as in chapter 4 of my thesis
To run the code locally, please follow these steps:
- Clone this repository to your local machine using
git clone https://github.com/JordPBvE/bachelor-project.git
- Make sure you have python installed, if not, see https://wiki.python.org/moin/BeginnersGuide/Download
- Install the required dependancies, either globally or in a virtual environment (for virtual environment, see https://docs.python.org/3/library/venv.html)
pip install numpy matplotlib scipy colorama winsound
To run one of the four programs, navigate into the correct folder in your terminal and run
python main.py
Results to simulations can be found in the program folders. Gemerally, the most impoertant results are saved into fig.png images, and additional results, often used in testing, are inserted under names explaining the content.