Skip to main content

Package for dealing with bond pricing and hedging

Project description

QuantGYMM

This a simple package to deal with bond pricing and bond hedging. This project was born during the Group Assignment for the Fixed Income course in the MAFIRM at Collegio Carlo Alberto, and as personal challenge to create something useful. It is a simple Python package that allows to fit term structures and perform bond pricing. Please see the documentation for further details.

Getting started

Before installing 'QuantGYMM', be sure that you have a Python version >= 3.9 installed in you computer/local enviroment. If you are using a conda, I suggest to create a virtual enviroment and install a suitable Python version.

Suggested Set Up:

  1. Create virtual enviroment and activate it:
conda create --name [your_env_name_here] python=3.10
conda activate [your_env_name_here]
  1. Install Jypyter (optional):
conda install jupyter
  1. Install QuantGYMM:
pip install QuantGYMM

or (better):

python3 -m pip install QuantGYMM

Alternative:

  1. You could clone the repository:
git clone https://github.com/GianlucaBroll95/QuantGYMM.git

and then install running from within the directory:

pip install .

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

quantgymm-0.2.2.tar.gz (22.6 kB view details)

Uploaded Source

Built Distribution

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

quantgymm-0.2.2-py3-none-any.whl (25.3 kB view details)

Uploaded Python 3

File details

Details for the file quantgymm-0.2.2.tar.gz.

File metadata

  • Download URL: quantgymm-0.2.2.tar.gz
  • Upload date:
  • Size: 22.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for quantgymm-0.2.2.tar.gz
Algorithm Hash digest
SHA256 9d9fd4a0db7f5e653910c2d1b15ebeee70c51d5d86a297a35573076e40a36d2f
MD5 20c657c357fe61994c5750d2b235965b
BLAKE2b-256 5c99a2adbdf56eafe99fd94fb139c47553b06a1e43be4dd5cb6fb4155b1f2500

See more details on using hashes here.

File details

Details for the file quantgymm-0.2.2-py3-none-any.whl.

File metadata

  • Download URL: quantgymm-0.2.2-py3-none-any.whl
  • Upload date:
  • Size: 25.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for quantgymm-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 fed9c1881ffb76c6d464c675dfc7d75a49e891f55bab8290dc12c9dbc24a7c75
MD5 357aae93a90f8271b6142c75f207ab55
BLAKE2b-256 a93ac8f192821df331e031cd7ef4609f6665d97fb2033958d39750a460a57d14

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