| 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/ | - | |
