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The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core tradin
A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Pyt
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core tradin
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key FeaturesExplore advanced financia
Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pand
