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. 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.tar.gz (22.4 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-py3-none-any.whl (24.8 kB view details)

Uploaded Python 3

File details

Details for the file QuantGYMM-0.2.tar.gz.

File metadata

  • Download URL: QuantGYMM-0.2.tar.gz
  • Upload date:
  • Size: 22.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.4

File hashes

Hashes for QuantGYMM-0.2.tar.gz
Algorithm Hash digest
SHA256 6246a2e9e91dae809bb4381464d41b14ac3c9669e237ab2c17b2398770a5b4db
MD5 2b360e84fe77ca471a35dcff2609eedc
BLAKE2b-256 b9a51b65b20e8001873f1abb0e128f2206845707e236fa973b9e95be64d7ca5d

See more details on using hashes here.

File details

Details for the file QuantGYMM-0.2-py3-none-any.whl.

File metadata

  • Download URL: QuantGYMM-0.2-py3-none-any.whl
  • Upload date:
  • Size: 24.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.4

File hashes

Hashes for QuantGYMM-0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 9af1b0b77a89e695cc15f3ede29918effa5f424259af8bddb51b16fa05e9850d
MD5 2a93ff851a6e4423b506d0ca9a63cbe7
BLAKE2b-256 6a77a43ec6ed557c6fa6aaa744e9ed5e37163d25b6d0b7636d2834ab2de95cbc

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