Library for stochastic process simulation
Project description
ito_diffusions
Libraries for stochastic processes simulation and visualization including:
- Ito diffusion : Brownian motion, Geometric Brownian motion, Vasicek, CIR...
- Jump processes : Ito diffusion driven by a Levy process i.e with a jump component with a given intensity and jump size distribution;
- Multidimensional processes, stochastic volatility diffusions (SABR...);
- Fractional Brownian motion, Karhunen-Loeve expansion, fractional diffusions;
- Times series models (AR, MA, ARMA, ARCH, GARCH, NAGARCH...);
- Self-Avoiding Walks (SAW), Schramm-Loewner Evolution (SLE).
To install : pip install ito-diffusions https://pypi.org/project/ito-diffusions/
To test : python -m pytest
For numerous examples : https://github.com/sauxpa/stochastic
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ito_diffusions-1.4.1.tar.gz.
File metadata
- Download URL: ito_diffusions-1.4.1.tar.gz
- Upload date:
- Size: 32.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6adc8bed91b7136ac7d336ca7eda9425591d131893affd52e0b99e3dad15004e
|
|
| MD5 |
5e5e13c56b887ae5d5e3f8fe844d0443
|
|
| BLAKE2b-256 |
493e403b6ebbe97fb02629d243ac1fdfcf3743761f17a1917e9b89be92df5c00
|
File details
Details for the file ito_diffusions-1.4.1-py3-none-any.whl.
File metadata
- Download URL: ito_diffusions-1.4.1-py3-none-any.whl
- Upload date:
- Size: 37.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a63e26c307eb03337b548ba66488441edf0d5d3d439736eab7d2781b3456ea5f
|
|
| MD5 |
7faafffcc79ba2aed8d52291064437bb
|
|
| BLAKE2b-256 |
57d38618046e67bceaf4e134e791f6f076e15697847df12df9c6224b2febdabb
|