August 2009
Intermediate to advanced
244 pages
9h 5m
English
Content preview from Financial Modelling in Python
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2 Financial Modelling in Python
1.1.2 Python Integrates Well with Data Analysis, Visualisation and GUI Toolkits
Another compelling argument for the use of Python by quantitative analysts is the ease with
which Python integrates with visualisation software such as GNUPlot
2
making it possible
for the analyst to construct personalised ‘Matlab-like’
3
enivronments. Furthermore, quantita-
tive analysts generally have neither the interest or time to invest in producing graphical user
interfaces (GUIs). They can be nonetheless important. Python provides Tk-based
4
GUI tools
making it straightforward to wrap programs into GUIs. Readers interested in learning more
about how Python can be integrated with GUI building, data analysis and visualisation soft-
ware are particularly recommended to consult Hans Peter Langtangen’s Python Scripting for
Computational Science [14].
1.1.3 Python ‘Plays Well with Others’
A variety of techniques exist to extend Python from the C and C++ programming languages.
Conversely, a Python interpreter is easily embedded in C and C++ programs. In the world
of financial engineering, C/C++ prevails and large bodies of this code exist in most financial
institutions. The ability for new programs to be written in Python that can interoperate with
these code investments is a huge victory for the analyst and the institutions ...
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