This module provides some technical indicators for analysing stocks.
Description and features
Description
This module provides some technical indicators for analysing stocks.
When I can I will add more.
If anyone wishes to contribute with new code or corrections/suggestions, feel free.
This module was done and tested under Windows with Python 2.7.3 and numpy 1.6.1.
Features
Relative Strength Index (RSI), ROC, MA envelopes Simple Moving Average (SMA), Weighted Moving Average (WMA), Exponential Moving Average (EMA) Bollinger Bands (BB), Bollinger Bandwidth, %B
Installation
Installation
$ pip install taiResources and contributing
Resources
Contributing
If Other repository above is Github or compatible, follow these guidelines for contributing:
Fork the repository .
Make a branch of master and commit your changes to it.
Ensure that your name is added to the end of the AUTHORS.rst file using the format: Name <email@domain.com>
Submit a Pull Request to the master branch.
1 maintainer
Metadata
1 maintainer
Release files for tai 0.0.45
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| tai-0.0.45.zip | 605.5 kB | Without provenance | Details |
Release files / tai-0.0.45.zip
| Download URL | tai-0.0.45.zip |
|---|---|
| Size | 605.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
777ba13d175b910ba26a847ce7178f4062cfa27bf52ebada5f10c602c3896f05
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BLAKE2b-256 checksum How to use checksums |
8d1009ede3d45bcbb07bcc20b775d1e565335507b1370d9fdce62478634c49f6
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for tai 0.0.45
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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