Skip to main content

A simple quantitative finance library for Python

Project description

Library Overview This library provides tools for retrieving, managing, and analyzing stock market data. Data access and preprocessing are handled within the dataCollectionAndModification class, while core computational logic and baseline signal generation are implemented in the stockStandardSignalRetrieval class. The evaluationOfSignals class functions help to evaluate signals collected in the stockStandardSignalRetrieval class. Furthermore monte carlo, black scholes, and greek computations are available.

Disclaimer ⚠️ This library is intended strictly for educational and research purposes. It is not designed to provide financial advice or investment recommendations. Do not use this software as a basis for making real-world investment decisions.

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

quickquantcfr-1.1.1.tar.gz (6.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quickquantcfr-1.1.1-py3-none-any.whl (6.0 kB view details)

Uploaded Python 3

File details

Details for the file quickquantcfr-1.1.1.tar.gz.

File metadata

  • Download URL: quickquantcfr-1.1.1.tar.gz
  • Upload date:
  • Size: 6.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for quickquantcfr-1.1.1.tar.gz
Algorithm Hash digest
SHA256 ea8f88b407d52714a8cf85e64a6ea08c47d6906899dc039bf7b4061f1eae811b
MD5 6c4b8341967e4e03a0d003cf32e6709b
BLAKE2b-256 4605dd5e6a8195e6f2fb50936c20e06b66065b4db7cfc9550ab79a4b7416863a

See more details on using hashes here.

File details

Details for the file quickquantcfr-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: quickquantcfr-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 6.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for quickquantcfr-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 63fb21d8d70c76cd362471884bce82c10827e76498fbdcd73eb5fdfe8057d4a9
MD5 7e38c735705160ea7cc2a8e1a6c74109
BLAKE2b-256 5579c4e989a78320b31b798da1ce1608b47d9c6eb57e203e18f58700c57b719c

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