This repository contains different tools to simulate underlyings under SV dynamics. As well, we have implemented several tools for computing option price under SV.
The next packages are using of a intesive way:
- python ~= 3.9
- numpy~=1.21.5
- numba~=0.55.1
- ncephes~=1.1.0
- matplotlib~=3.5.1
- scipy~=1.7.3
- pandas~=1.4.2
- statsmodels~=0.13.2
- tabulate~=0.8.9
- prettytable~=2.4.0
- setuptools~=61.2.0
- py_vol ~= Last version
- sobol_seq ~= Last version
We will a brief description of each module of the library.
In this module, the reader can find two numerical methods Fourier inversion or COS method to price options under dynamics with known characteristic function. Currently, we have implemented the characteristic function for the Heston and Merton model. In addition, we have included the different approximations for implied volatility, vol swap, variance swap
Here the reader can find the numerical experiments performed for each chapter of the book.
Tools for sampling the fractional brownian motion and the truncated fractional brownian.
In this module, the reader can find the different instruments that we have used in the book. These instruments are independent of the model, for this reason, we cause the same instrument for different MC engines.
This module contains the different MC pricers that the user can use in any MC Engine.
We have included a one dimensional PDE solver. Under the local volatility model, this numerical is so stable and fast. The user can use generic boundary conditions and solver the PDE using explicit, implicit, or theta scheme.
This module contains generic functionalities (random number generator, numba functions, ...) that are used in several parts of the library.
The term struct for building volatility surface. We have implemented SVI and SABR.