American Options Pricing ANN
Project description
American Options ANN
This is still a work in progress, all
v0.1.*
releases are testing releases.
This is a Python package for American Options Pricing using Artificial Neural Networks (ANN) that assumes the option follows a GARCH process. The package will contain 3 stages of datasets for 3 GARCH models:
- HN-GARCH
- Duan-NGARCH
- GJR GARCH
Project Structure
main.py
: Contains the main entry point for the program, and is in charge of running the Training and Testing of the ANN model.model.py
: Contains the implementation of the ANN model used for pricing American Options.dataset.py
: Contains parsing the CSV files and preparing the data for training and testing.utils.py
: Contains utility functions for the package.
Installation
pip install ao_ann
Running Locally
This project uses the Python package manager uv
, this can be installed using the following command:
$ git clone https://github.com/Mustafif/AO_ANN.git
$ cd AO_ANN
$ pip3 install uv # install uv
$ uv sync
$ uv run main.py # run the main.py file
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ao_ann-0.1.3.tar.gz
(8.0 kB
view details)
Built Distribution
File details
Details for the file ao_ann-0.1.3.tar.gz
.
File metadata
- Download URL: ao_ann-0.1.3.tar.gz
- Upload date:
- Size: 8.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d6a9c7277a17e1f173942e08edd05976926975acce13ccd45f7e8cba874b12c6 |
|
MD5 | 90910edd591fd80631984ad12be2248d |
|
BLAKE2b-256 | b4a6812b8217688bf91cfa552564643be441dc39eac4cc4695d071860a8c1742 |
File details
Details for the file ao_ann-0.1.3-py3-none-any.whl
.
File metadata
- Download URL: ao_ann-0.1.3-py3-none-any.whl
- Upload date:
- Size: 8.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 87f4ccccd0c934f5d0c323cb477f0bc53d41dec16db6c1aa6495925b33d226c7 |
|
MD5 | b1fea4c70ad9e1a755fbc8b73ff25e08 |
|
BLAKE2b-256 | 7fd4c89ce39360fed4ec4d686d94b211f457eb350923c24fa0d7b846b7166b6f |