mafipy 0.1.dev2

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mafipy

Description

mathmatical finance in python. Supported methods are belows:

• replication method
  • QuantoCMS
• Analytic formula
  • Black Scholes
  • Black
  • SABR
• Quasi Monte Carlo
  • sobol sequence (cython) up to 21202 dimension

Installation

pip install mafipy

Run examples

git clone https://github.com/i05nagai/mafipy.git
cd mafipy
python examples/plot_smile_curve_sabr.py

You will see the following drawing.

Documentation

• API document
• Benchmarks

Contributing

Set up development environment.

git clone https://github.com/i05nagai/mafipy.git
cd mafipy
git submodule init
git submodule update
pip install -r requirements.txt

Builds

To generate c files,

python setup.py build_ext

Test

To run tests, you additionally need to install pytest.

pip install -r requirements-dev.txt
python setup.py test

Benchmarks

asv is required to execute benchmarks. You can install asv by pip.

pip install asv

Then

# execute benchmarks
python setup.py benchmark
# generate html file from the results
python setup.py benchmark_publish
# preview the generated html through local server
python setup.py benchmark_preview

Related Projects

• GitHub - lballabio/QuantLib: The QuantLib C++ library
  • One of the best library for mathmatical finance. The library is written in C++. There are many wrapper projects of the QuantLib.
• GitHub - finmath/finmath-lib: Mathematical Finance Library: Algorithms and methodologies related to mathematical finance.
  • Mathematical Finance Library: Algorithms and methodologies related to mathematical finance. The library is written in Java.