Stock Price Prediction
Project description
STOCKER
Stocker is a python tool that uses ANN to predict the stock's close price for the next business day. Suggestions and contributions of all kinds are very welcome.
Authors
- Juan Camilo Gonzalez Angarita - jcamiloangarita
- Moses Maalidefaa Tantuoyir
- Anthony Ibeme
See the full list of contributors involved in this project.
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Get pwptemp
- Users: Wheels for Python from PyPI
pip install stocker
- Developers: Source code from github
git clone https://github.com/jcamiloangarita/stocker
Quick use
>>> import stocker
>>> stocker.predict.tomorrow('AAPL')
[266.07, 1.276, '2019-11-11']
Notice that output = [predicted price, error(%), date of the next business day]
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
stocker-0.1.11.tar.gz
(7.2 kB
view details)
Built Distribution
File details
Details for the file stocker-0.1.11.tar.gz
.
File metadata
- Download URL: stocker-0.1.11.tar.gz
- Upload date:
- Size: 7.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.52.0 CPython/3.8.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 |
2e38d0581510a66f0ccc2bf0ab61d477e6ba5ae2bffdd6cee0ec7b918c82ea90
|
|
MD5 |
698553ffbecb87bacc1034cb304d5105
|
|
BLAKE2b-256 |
8b5dce104f7624f8a271fba11b2e0b092bea13a09ab20646f8b4b740e4aa1740
|
File details
Details for the file stocker-0.1.11-py3-none-any.whl
.
File metadata
- Download URL: stocker-0.1.11-py3-none-any.whl
- Upload date:
- Size: 8.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.52.0 CPython/3.8.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 |
ef3499d28cb706487f0c78e97de8a0467e166bd4899a4a2264306f57d83dcc0f
|
|
MD5 |
ac1edee9e4ce8b20acc427de3a3031af
|
|
BLAKE2b-256 |
d97afd05582d233f26e8860c9bbf0922cc3722bfca45fa16681fc6818cc2eb87
|