Metadata-Version: 2.1
Name: yaopt
Version: 0.1.3
Summary: Basic options pricing in Python
Home-page: https://github.com/someben/yaopt
Author: Ben Gimpert
Author-email: ben@somethingmodern.com
License: MIT
Keywords: yaopt
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: numpy
Requires-Dist: scipy

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yaopt
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.. image:: https://badge.fury.io/py/yaopt.png                                                                   
   :target: http://badge.fury.io/py/yaopt                                                   


Basic Options Pricing (in Python)
***********************************

“Oh cool. Probably a little easier than spinning up the QuantLib stack.” — `Wes McKinney <https://github.com/wesm>`_, creator of `Pandas <https://github.com/pydata/pandas>`_.


Features
==========

#. Option valuation w/ Black-Scholes, lattice (binomial tree), and Monte Carlo simulation models.                                  
#. Basic Greeks calculation (delta, theta, rho, vega, gamma) across each valuation model.
#. Discrete dividends support in the lattice (binomial tree) and Monte Carlo simulation models.
#. Early exercise (American options) support in Monte Carlo simulation through the Longstaff-Schwartz technique.
#. Minimal dependencies, just Numpy & SciPy.
#. Free software, released under the MIT license.





History
-------

0.1.0 (2023-01-10)
---------------------

* First release on PyPI.

0.1.2 (2024-09-06)
---------------------

* Fix to Black-Scholes implied volatility.

0.1.3 (2024-09-06)
---------------------

* Fix to README.


