By Yves Hilpisch
The monetary has followed Python at an enormous fee lately, with a few of the greatest funding banks and hedge cash utilizing it to construct middle buying and selling and chance administration platforms. This hands-on consultant is helping either builders and quantitative analysts start with Python, and publications you thru an important elements of utilizing Python for quantitative finance.
Using sensible examples in the course of the publication, writer Yves Hilpisch additionally indicates you ways to improve a full-fledged framework for Monte Carlo simulation-based derivatives and chance analytics, in keeping with a wide, real looking case examine. a lot of the ebook makes use of interactive IPython Notebooks, with issues that include:
* basics: Python facts buildings, NumPy array dealing with, time sequence research with pandas, visualization with matplotlib, excessive functionality I/O operations with PyTables, date/time info dealing with, and chosen most sensible practices
* monetary issues: mathematical suggestions with NumPy, SciPy and SymPy similar to regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; records for normality exams, mean-variance portfolio optimization, imperative part research (PCA), and Bayesian regression
* certain issues: functionality Python for monetary algorithms, corresponding to vectorization and parallelization, integrating Python with Excel, and construction monetary functions in keeping with net applied sciences
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