1.1 Black-Scholes numerical methods.ipynb | 239.1 KB | |
1.2 SDE simulations and statistics.ipynb | 750.6 KB | |
1.3 Fourier transform methods.ipynb | 266 KB | |
1.4 SDE - Heston model.ipynb | 416 KB | |
1.5 SDE - Lévy processes.ipynb | 298.9 KB | |
2.1 Black-Scholes PDE and sparse matrices.ipynb | 327.2 KB | |
2.2 Exotic options.ipynb | 996.5 KB | |
2.3 American Options.ipynb | 264.9 KB | |
3.1 Merton jump-diffusion, PIDE method.ipynb | 209.1 KB | |
3.2 Variance Gamma model, PIDE method.ipynb | 330.3 KB | |
3.3 Pricing with the NIG Process.ipynb | 144.3 KB | |
4.1 Option pricing with transaction costs.ipynb | 176 KB | |
4.2 Volatility smile and model calibration.ipynb | 837.7 KB | |
5.1 Linear regression - Kalman filter.ipynb | 1.5 MB | |
5.2 Kalman auto-correlation tracking - AR(1) process.ipynb | 1.7 MB | |
5.3 Volatility tracking.ipynb | 1.3 MB | |
6.1 Ornstein-Uhlenbeck process and applications.ipynb | 1.1 MB | |
7.1 Classical MVO.ipynb | 689 KB | |
A.1 Solution of linear equations.ipynb | 144.1 KB | |
A.2 Optimize and speed up the code. (SOR algorithm, Cython and C).ipynb | 22.3 KB | |
A.3 Introduction to Lévy processes and PIDEs.pdf | 397.2 KB | |
CITATION.cff | 391 bytes | |
Dockerfile | 1.2 KB | |
LICENSE | 34.5 KB | |
README.md | 7.5 KB | |
data/ | - | |
docker-compose.yml | 297 bytes | |
environment.yml | 7 KB | |
latex/ | - | |
list_of_packages.txt | 95 bytes | |
pyproject.toml | 669 bytes | |
requirements.txt | 2.3 KB | |
setup.py | 566 bytes | |
src/ | - | |