Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging

APPENDIX A Python in a Nutshell

This appendix introduces into the Python language mainly by the means of simple interactive examples and some shorter code snippets (i.e. modules and scripts). It cannot replace any kind of proper training in this programming language or more comprehensive treatments in book form.

By reading this appendix, you will NOT learn how to code in general or learn Python from scratch to black belt level. However, for someone coming with C++ experience, for example, the appendix illustrates fundamental aspects of Python that are useful for derivatives analytics and financial engineering in general. For someone who starts out in these areas, the topics covered provide a first glimpse at coding in general and for derivatives analytics in particular. For this group, the appendix may act as a starting point for digging deeper into areas of further interest.

The best Python foundation for this book can be gained by reading the recent book by the same author (Hilpisch, 2014). That book focuses on teaching Python for finance and covers many topics of interest in this area on more than 600 pages. Another useful book is McKinney (2012) which introduces in detail the main data analysis tools and libraries needed for the applications presented in this book (in particular NumPy and pandas). For general introductions to Python from a scientific point of view, you can consult either the book by Langtangen (2009) or the freely available lecture notes of Haenel et al. ...