Skip to main content

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:

  1. HN-GARCH
  2. Duan-NGARCH
  3. GJR GARCH

Project Structure

  • ann.py: Contains training and evaluation of the ANN model, as well as the main entry point for the program (ao_ann_main(...))
  • loss.py: Contains the function to calculate the different loss measures between target and predicted values.
  • 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

Todo

  • Comments in the code
  • Documentation
  • Example program

Metadata

Release files for ao_ann 0.1.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ao_ann 0.1.6
File Size Uploaded
ao_ann-0.1.6.tar.gz 9.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for ao_ann 0.1.6
File Interpreter ABI Platform
ao_ann-0.1.6-py3-none-any.whl Python 3 none any Details

Total release size: 19.5 kB

Release files / ao_ann-0.1.6.tar.gz

Download URL ao_ann-0.1.6.tar.gz
Size 9.6 kB
Tags Source
SHA-256 checksum
How to use checksums
069f88f23d0fbd33cd8e0993a4d40594c9a22b1a8dfd232ab842ab855aa7cb29
BLAKE2b-256 checksum
How to use checksums
a3a7aa173de8bc164327308bc09f85083e6ca31b7b6feb995946b994e4c66486
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.6.6

Release files / ao_ann-0.1.6-py3-none-any.whl

Download URL ao_ann-0.1.6-py3-none-any.whl
Size 10.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b64258595c68812570c818003ed3fae3937e96b535acc0581578d856ea464377
BLAKE2b-256 checksum
How to use checksums
bf7d9ede880c706054e4a8f0dc7030e73bd637c0c7492e2dbecd2528a274b0d9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.6.6

Release history Release notifications | RSS feed

This release

0.1.6 This release

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page