Readme file for Python Financials 
Copyright (c) 2000 g.p.ciceri <gp.ciceri@acm.org>

Python Financials (pyFinancials) is free software.
These programs/libraries are distributed under either the GNU General
Public Licence or GNU Library General Public Licence as published by 
the Free Software Foundation. 
See the files COPYING, COPYING.LIB for copying permission of these programs. 


What's this
============

Python Financials (pyFinancials in the following) is a collection
of algorithms for advanced financials calculations. 

These initials releases depend heavily upon the excellent "Financial
Numerical Recipes", by Bernt Arne Oedegaard.  

You can find them at:

http://finance.bi.no/~bernt/gcc_prog/algoritms/algoritms/algoritms.html

Actually I've reimplemented (from C++) some of these algorithms:

- Cash Flow (IRR)
- Basic Option Pricing
- Binomial Option Pricing
- Finite Difference
- Option Price MC Simulation
- Futures Algorithms
- Bonds Algorithms
- General Simulation
- Term Structure Algorithms
- Fixed Income Modellin

Missing features
================

- I need more algorithms, of course.
- This implementation uses python lists, I'd like to do
some tests with NumPy arrays (efficiency ???)
- The original C++ implementations use STL, and SWIG doesn't like this
too much (for what I've understood), so I wasn't able to swig them.
Anyone dares ??? 
- Testing, testing, testing: much more testing is required.
- A simple installation procedure


Installation	
============

If you want to play with simulations, start building the extension
module in the subdirectory ./knuthran (random number generator).
Then simply copy the *.py somewhere in your $PYTHONPATH, and enjoy (hopefully).


Documentation
=============

Refer to Financial Numerical Recipes Documentation (and source code), 
it's excellent.


Examples
========

Actually, every module comes with its own examples: only run
the module from the command line (ex.: python Bonds.py). 


Recommended Additional Documentation
====================================

Refer to Financial Numerical Recipes Bibliography, again.


Contact
=======

If you have any queries, suggestions and problems in using pyFinancials,
contact gp.ciceri@acm.org. I'd like to hear from you.

