Python for Finance
Analyze Big Financial Data
Publisher: O'Reilly Media
Final Release Date: March 2014
Pages: 350

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The world of finance requires detailed analysis of large amounts of data in very short periods of time. Python for Finance provides the Python techniques and tools you need to successfully apply Python for the development of financial applications and interactive financial analytics. The first part of the book shows how to set-up your Python infrastructure, the second is more topic-oriented, and the third offers readers relevant case studies.

The author includes topics such as integration with Excel, stochastics, statistical analysis, and handling derivatives valuation (through a Monte Carlo simulation). Useful Python libraries are also covered, including NumPy, SciPy, matplotlib, and pandas.

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oreillyPython for Finance
 
3.0

(based on 1 review)

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3.0

Not as good as Python for Data Analysis

By Matt Cullen-Meyer

from Denver, CO

About Me Financial Analyst

Verified Buyer

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    Cons

    • Not comprehensive enough

    Best Uses

      Comments about oreilly Python for Finance:

      The author provides many interesting examples, but does not provide sufficient background or support to, say, modify the code for custom purposes. At other times the author gives overviews of very basic Python topics, such as data types and structures. In this respect the book suffers from an indecision on whether it is an introductory or advanced text. Most of the concepts considered herein are covered more in depth in Python for Data Analysis. This has been a nice refresher text, but I do not recommend it for the beginner or for anyone hoping to learn the pandas library for the first time.

      (Disclaimer: I'm writing this having only gone through the first early release.)

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      November 2014 (est.)