Python for Finance
Analyze Big Financial Data
Publisher: O'Reilly Media
Final Release Date: December 2014
Pages: 606

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 trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance.

Using practical examples through 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, with topics that include:

  • Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices
  • Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression
  • Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
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oreillyPython for Finance
 
2.8

(based on 4 reviews)

Ratings Distribution

  • 5 Stars

     

    (1)

  • 4 Stars

     

    (0)

  • 3 Stars

     

    (1)

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33%

of respondents would recommend this to a friend.

Reviewed by 4 customers

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(1 of 1 customers found this review helpful)

 
2.0

This is really a cookbook more than a learning book

By Experienced Programmer

from Minnesota

About Me Developer

Verified Buyer

Pros

  • Lots Of Good References

Cons

  • Disconnected Flow

Best Uses

  • As A Cookbook Reference

Comments about oreilly Python for Finance:

It wasn't that impressive a read. I felt like I was handed someone's research notes. There are lots of good citations to follow. However, the information was not organized into a learning story that builds up. It was really a cookbook of examples. If it had been properly titled or described as a cookbook, I would not have gotten it in the first place.

(3 of 3 customers found this review helpful)

 
1.0

The are better books

By Curious to learn

from At home

Verified Reviewer

Pros

  • Show Some Py Abilities

Cons

  • Messy

Best Uses

  • Not At All

Comments about oreilly Python for Finance:

I liked the idea of learning Python and update me on calculating financial stuff.

I find the book messy. The author seem to show of what is possible to do, but are not building up the readers knowledge. If you are new in programming don't consider this book. If you are experienced programmer and want to learn Python, look somewhere else. If have PhD in Finance and experience in programming, maybe interesting, but most likely you don't need the book.
You will not learn Python nor finance by reading this book.

I have started to read Python for Data Analysis by Wes McKinney and find it way much better. I also reading Python for Finance by Yuxing Yan, which I also find much better. Yan has phD in Finance and explains how to use Python as finance calculator, builds up understand of Python and later brings up the more strength of pandas and such.

(3 of 3 customers found this review helpful)

 
5.0

I think it is great book

By Jason

from Toronto Canada

Pros

  • Accurate
  • Helpful examples
  • Well-written

Cons

    Best Uses

    • Intermediate

    Comments about oreilly Python for Finance:

    As someone working in finance it is tough to find a book that truly illustrates the application of python for finance. I understand the above review about it being indecisive if advanced or beginner text but I would consider myself very basic as my only other experience with python was basic code academy and I found the examples good to learn from and experiment with changing code. I would definitely recommend if you want to use Python for finance.

    (15 of 16 customers found this review helpful)

     
    3.0

    Not as good as Python for Data Analysis

    By Matt Cullen-Meyer

    from Denver, CO

    About Me Financial Analyst

    Verified Buyer

    Pros

      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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