Mastering Python for Finance

by James Ma Weiming (Author)

11 ratings

ISBN-13: 978-1784394516

ISBN-10: 1784394513

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Mastering Python for Finance: Implement advanced state-of-the-art financial statistical applications using Python, 2nd Edition
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Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

About This Book

Explore financial models used by the industry and ways of solving them with this guide
Discover the various features that Python provides for scientific computing and harness them to enhance your financial applications
Build state-of-the-art infrastructure for critical aspects such as modeling, trading, pricing, and analytics

Who This Book Is For

If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.

What You Will Learn

Perform interactive computing with IPython Notebook
Solve linear equations of financial models and perform ordinary least squares regression
Explore nonlinear modeling and solutions for optimum points using root-finding algorithms and solvers
Discover different types of numerical procedures used in pricing options
Model fixed-income instruments with bonds and interest rates
Manage big data with NoSQL and perform analytics with Hadoop
Build a high-frequency algorithmic trading platform with Python
Create an event-driven backtesting tool and measure your strategies

In Detail

Built initially for scientific computing, Python quickly found its place in finance. Its flexibility and robustness can be easily incorporated into applications for mathematical studies, research, and software development.

With this book, you will learn about all the tools you need to successfully perform research studies and modeling, improve your trading strategies, and effectively manage risks. You will explore the various tools and techniques used in solving complex problems commonly faced in finance.

You will learn how to price financial instruments such as stocks, options, interest rate derivatives, and futures using computational methods. Also, you will learn how you can perform data analytics on market indexes and use NoSQL to store tick data.

James Ma Weiming
43
Paperback
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Eryk Lewinson
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Marcos Lopez de Prado
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Editorial Reviews

About the Author

James Ma Weiming is a software engineer based in Singapore. His studies and research are focused on financial technology, machine learning, data sciences, and computational finance. James started his career in financial services working with treasury fixed income and foreign exchange products, and fund distribution. His interests in derivatives led him to Chicago, where he worked with veteran traders of the Chicago Board of Trade to devise high-frequency, low-latency strategies to game the market. He holds an MS degree in finance from Illinois Tech's Stuart School of Business in the United States and a bachelor's degree in computer engineering from Nanyang Technological University.

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Product details

Publisher ‏ : ‎ Packt Publishing (April 29, 2015)
Language ‏ : ‎ English
Paperback ‏ : ‎ 340 pages
ISBN-10 ‏ : ‎ 1784394513
ISBN-13 ‏ : ‎ 978-1784394516
Item Weight ‏ : ‎ 1.29 pounds
Dimensions ‏ : ‎ 7.5 x 0.77 x 9.25 inches

Best Sellers Rank: #2,893,999 in Books (See Top 100 in Books)
- #328 in Business Accounting Software Computer
- #336 in Personal Finance Software (Books)
- #1,236 in Mathematical & Statistical Software

Customer Reviews:
11 ratings

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James Ma Weiming

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James Ma Weiming is a software engineer and researcher based in Singapore. His studies and research are focused on financial technology, machine learning, data sciences, and computational finance. James started his career in financial services working with treasury fixed income and foreign exchange products, and fund distribution. His interests in derivatives led him to Chicago, where he worked with veteran traders of the Chicago Board of Trade to devise high-frequency, low-latency strategies to game the market. He holds an MS degree in finance from Illinois Tech's Stuart School of Business in the United States and a bachelor's degree in computer engineering from Nanyang Technological University.

Customer reviews

5 star		26%
4 star		32%
3 star		22%
2 star		20%
1 star 0% (0%)		0%

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Federico Han

A pretty good survey on many object-oriented implementations common in Finance

Reviewed in the United States on February 28, 2018

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A pretty good survey on many object-oriented implementations common in Finance.
Plenty of applications and examples -some indeed with errors , though on the positive it is a useful learning experience to do some minor debugging !-.
As with many practical reference books try to buy the print version, this is not bedtime reading stuff.

2 people found this helpful

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looksee

The book introduces many new concepts, however after trying ...

Reviewed in the United States on July 25, 2016

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The book introduces many new concepts, however after trying to make my way through the book, the code need an update, Starting at chapter 3 you will encounter numerous mistakes and omissions that cause the code to fail. Chapter 6 is rife with mistakes. Buy only if you have time to debug the code.

8 people found this helpful

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Amazon Customer

Very general

Reviewed in the United States on May 5, 2017

Verified Purchase

This book is very general.

One person found this helpful

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Dimitri Shvorob

Get the Hilpisch book instead

Reviewed in the United States on October 27, 2016

I will bang this drum again: a book review which shows no awareness of possible alternatives is not useful. In this case, you need to have seen "Python for Finance" by Yves Hilpisch to be able to skim this Packt-standard-low-quality book and label it a "pass". A 20-page (that's 20 sparse Packt pages, meaning 12 or so regular ones) tour of Hadoop, a 10-page encounter with MongoDB (using "pymongo"), and 35 pages going through Python interfaces to Interactive Brokers and Oanda trading platforms ("IbPy" and "oandapy", respectively) are not much of a saving grace: far superior resources are a quick Google search away.

10 people found this helpful

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Duncan W. Robinson

excellent book combining academic theory w/ practical applications in Python

Reviewed in the United States on June 14, 2015

Wow… good stuff. Mastering Python for Finance really delivers. It does a fine job blending academic theory with a practitioner’s penchant for useful applications, delivering Python code all the way to guide the reader along his / her journey. I have not worked all of the examples yet, but I am looking forward to doing so – especially the sections that use Hadoop & Python together.

10 people found this helpful

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Martin Galli

Bon livre

Reviewed in France on January 1, 2017

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Bon livre en général mais dommage qu'il soit en Python 2.7 et non Python3.5. Sinon, les solutions sont très bien expliquées et l'organisation est claire.

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Ho Yan Chan

Three Stars

Reviewed in the United Kingdom on May 2, 2018

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Kindleのお客様

理論は薄め。とりあえずPythonで金融工学やりたい人向け

Reviewed in Japan on July 6, 2016

Verified Purchase

金融工学の基礎を一通り習得した人が、pythonでコードをかけるようになるための一冊。

目次の内容に対して、特に数学的な証明等なしで天下り的にPythonのコードが羅列されているので、ファイナンスの入門者にはお勧めしない。

費用対効果は高い。

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