Skip to main content

Financial stochastic processes and statistical tools

Project description

FinRav 💹

FinRav is an open-source Python library for quantitative finance and statistical modeling.
It provides clean, modular tools for simulating stochastic processes and analyzing financial time series.


✨ Features

  • stoch — A comprehensive module for simulating stochastic processes, including Brownian motion, fractional Brownian motion, and other time-series models commonly used in quantitative finance.

  • stats — A collection of statistical analysis tools for parameter estimation, distribution fitting, and evaluating heavy-tailed behavior in financial data

  • monte_carlo — A flexible Monte Carlo simulation framework for modeling uncertainty, pricing derivatives, and analyzing risk under stochastic dynamics.

⚙️ Installation

pip install finRav

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

finrav-0.4.9.tar.gz (11.1 kB view details)

Uploaded Source

Built Distribution

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

finrav-0.4.9-py3-none-any.whl (18.7 kB view details)

Uploaded Python 3

File details

Details for the file finrav-0.4.9.tar.gz.

File metadata

  • Download URL: finrav-0.4.9.tar.gz
  • Upload date:
  • Size: 11.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for finrav-0.4.9.tar.gz
Algorithm Hash digest
SHA256 56077c9eeaa867e3769c6071e3ab53a37729ddba7727fc62e6dab20f9b8296ce
MD5 15cca9237448aa0059a479ed194c2d71
BLAKE2b-256 01021f62df1ef67ed2d92c21ad6e51d2d368ec42bb16b25ef3f5248b8d02332e

See more details on using hashes here.

File details

Details for the file finrav-0.4.9-py3-none-any.whl.

File metadata

  • Download URL: finrav-0.4.9-py3-none-any.whl
  • Upload date:
  • Size: 18.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for finrav-0.4.9-py3-none-any.whl
Algorithm Hash digest
SHA256 e1757d1594fbacd1a896d63104bb47f7c2715e81f015ea0d031ebf92aec8cf2b
MD5 9b7d41fec7790e58cefe608fe33e5b7e
BLAKE2b-256 28050469ee2d1cddcbd920f43b4508cd1901395042c2d54dfbe8f16204cd55a0

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