Skip to main content

A CLI for finding mispriced options.

Project description

panelbeater

PyPi

A CLI for finding mispriced options.

Dependencies :globe_with_meridians:

Python 3.11.6:

Raison D'être :thought_balloon:

panelbeater trains models at t+X iteratively to come up with the calibrated expected distribution of an asset price in the future. It then finds the current prices of options for an asset, and determines whether it should be bought and for how much.

Architecture :triangular_ruler:

panelbeater goes through the following steps:

  1. Downloads the historical data.
  2. Performs feature engineering on the data.
  3. Trains the required models and copulas to operate on the data panel.
  4. Downloads the current data.
  5. Runs inference on t+X for the latest options to find the probability distribution on the asset prices to their expiry dates.
  6. Finds any mispriced options and size the position accordingly.

Installation :inbox_tray:

This is a python package hosted on pypi, so to install simply run the following command:

pip install panelbeater

or install using this local repository:

python setup.py install --old-and-unmanageable

Usage example :eyes:

You can run panelbeater as a CLI like so:

panelbeater

This performs a full train, inference and attempts to find mispriced options.

License :memo:

The project is available under the MIT License.

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

panelbeater-0.2.40.tar.gz (23.9 kB view details)

Uploaded Source

File details

Details for the file panelbeater-0.2.40.tar.gz.

File metadata

  • Download URL: panelbeater-0.2.40.tar.gz
  • Upload date:
  • Size: 23.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.6

File hashes

Hashes for panelbeater-0.2.40.tar.gz
Algorithm Hash digest
SHA256 75576ff0e0570aa896f2676e4ee9aa32ce6cc2331b090ac299d1353c30035719
MD5 c52cc89b4fca0db24cb09d3a79d20d70
BLAKE2b-256 460e03b45944ad02fefb202b1561ea2f68746cdb5bc48e6b6c827388c56c0553

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page