Metadata-Version: 2.4
Name: py_volanalytics
Version: 0.1.1
Summary: Vol-fitting methods and pricing-analytics for volatility derivatives
Home-page: https://github.com/quasar-chunawala/py_volanalytics
Author: quasar-chunawala
Author-email: quasar-chunawala <quasar.chunawala@gmail.com>
Project-URL: Homepage, https://github.com/quasar-chunawala/py_volanalytics
Requires-Python: >=3.12
Description-Content-Type: text/markdown
License-File: LICENSE.txt
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Requires-Dist: attrs>=25.3.0
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Requires-Dist: scienceplots>=2.1.1
Requires-Dist: matplotlib>=3.10.1
Requires-Dist: setuptools>=77.0.3
Requires-Dist: pip>=25.0.0
Requires-Dist: twine>=6.1.0
Requires-Dist: wheel>=0.45.1
Dynamic: author
Dynamic: home-page
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# py_volanalytics

I like to research and code up robust implementations of algorithms and pricing analytics. I would also like to write implementations of the core blocks one needs for such tasks - optimizers, fourier transforms, characteristic functions, FFT etc.

Over time, the cost of writing my own library and the understanding and flexibility that comes with it will hopefully outweigh the sunk cost of building things ground up. 

Features
--------


Installation
-------------
The easiest way to install `py_volanalytics` is by using `pip`:

```
# to install the latest release (from PyPI)
pip install py_volanalytics

# to install the latest release (using Conda)
conda install -c conda-forge py_volanalytics

# to install the latest commit (from GitHub)
pip install git+https://github.com/quasar-chunawala/py_volanalytics

# to clone and install from a local copy
git clone https://github.com/quasar-chunawala/py_volanlyticss.git
cd py_volanalytics
pip install -e .
```

PyPi package
------------
[py_volanalytics](https://pypi.org/project/py-volanalytics/0.1.0/)

References
----------
- [The local volatility surface](https://emanuelderman.com/wp-content/uploads/1996/06/gs-local_volatility_surface.pdf), *Emanuel Derman, 1996*
