Is python financial big data analysis useful?

"Python Financial Big Data Analysis" is a Chinese translation book published by People's Posts and Telecommunications Press in December 2015. The author is [Germany] Yves Schilpisko and the translator is Yao Jun.

#"Financial Big Data Analysis with Python", the only professional book that explains in detail the use of Python to analyze and process financial big data; in the field of financial application development A must read for practitioners. It is suitable for developers in the financial industry who are interested in using Python for big data analysis and processing. (Recommended learning: Python video tutorial)

Content introduction

Python is known for its simplicity, easy-to-read, scalability and ease of use. The huge and active scientific computing community has been widely and rapidly used in the financial industry that requires analysis and processing of large amounts of data, and has become the preferred programming language for developing core applications in this industry.

"Python Financial Big Data Analysis" provides tips and tools for using Python for data analysis and developing related applications.

"Python Financial Big Data Analysis" is divided into 3 parts and 19 chapters in total.

Part 1 introduces the application of Python in finance. It covers the reasons why Python is used in the financial industry, Python’s infrastructure and tools, and some specific introductory examples of Python in quantitative finance. ;

Part 2 introduces the most important Python libraries, technologies and methods in financial analysis and application development. It covers Python data types and structures, data visualization with matplotlib, and financial time series data. Processing, high-performance input/output operations, high-performance Python technology and libraries, various mathematical tools needed in finance, random number generation and random process simulation, Python statistical applications, integration of Python and Excel, Python object-oriented programming and GUI development, integration of Python and Web technology, and development based on Web applications and Web services;

Part 3 focuses on the development of practical applications of Monte Carlo simulation options and derivatives pricing. The content covers the introduction of valuation frameworks, simulation of financial models, valuation of derivatives, valuation of investment portfolios, volatility options and other knowledge.

About the author

Yves Hilpsch is the founder and managing shareholder of Python Quants (Germany) GmbH and a co-owner of Python Quants (New York) GmbH founder. The group provides Python-based financial and derivatives analysis software (see http://pythonquants.com, http://quant-platfrom.com and http://dx-analytics.com), as well as Python and finance-related Consulting, development and training services.

Yves is also the author of Derivatives Analytics with Python (Wiley Finance, 2015). As a graduate student in business management with a PhD in mathematical finance, he teaches numerical methods in computational finance at the University of Saarland.

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