Python financial Big data analytics PDF

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The only professional book that deals with the use of Python to analyze financial big data is a must-read by practitioners in the field of financial application development.

With its simple, easy-to-read, scalable, and large and vibrant scientific computing community, Python is widely and rapidly used in the financial industry that needs to analyze and process large amounts of data, and becomes the preferred programming language for the industry's core application development. The Python financial Big Data analysis provides tips and tools for data analysis using Python and for developing related applications.

"Python Financial Big Data analysis" is divided into 3 parts, a total of 19 chapters, the 1th part describes the application of Python in finance, which covers the reasons for Python for the financial industry, Python's infrastructure and tools, And some specific examples of how Python is used in econometrics; Part 2nd introduces the most important Python libraries, technologies, and methodologies in financial analysis and application development, covering Python data types and structures, data visualization with Matplotlib, Financial time series data processing, high performance input/output operations, high-performance Python technology and libraries, multiple mathematical tools required in finance, random number generation and stochastic process simulations, Python statistics applications, integration of Python and Excel, Python's object-oriented programming and GUI development, the integration of Python and web technologies, and the development of Web-based applications and Web services; The 3rd part focuses on the development of Monte Carlo simulation options and derivatives pricing, which covers the introduction of the valuation framework, the simulation of financial models, Knowledge of derivatives valuation, portfolio valuation, volatility options, etc.

"Python Financial Big Data analytics" is ideal for developers of financial industries interested in using Python for big data analysis and processing.

Author profile ...

Yves Hilpsch is the founder and shareholder of Python Quants (Germany) Co., Ltd. and co-founder of the Python Quants (New York) Limited liability company. The group provides Python-based financial and derivative analysis software (see http://pythonquants.com,http://quant-platfrom.com and HTTP/ dx-analytics.com), as well as consulting, development and training services related to Python and finance.

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

Catalogue--Introduction to the author
Copyright notice
Content Summary
O ' Reilly Media, Inc. Introduction
Objective
Part 1th Python and finance
The 1th chapter Why Python is used for financial
Chapter 2nd Infrastructure and tools
3rd Introductory Example
Part 2nd Financial Analysis and development
Chapter 4th data Types and structure
The 5th chapter of data visualization
Chapter 6th Financial Time series
7th. Input/Output operation
8th High-Performance python
The 9th Chapter Mathematics Tools
10th Chapter Inference Statistics
Chapter 11th Statistics
12th Chapter Excel Integration
The 13th chapter object-oriented and graphical user interface
14th Chapter Web Integration
Part 3rd Derivative Analysis Library
Chapter 15th Valuation Framework
The 16th chapter the simulation of financial model
17th. Valuation of Derivative products
18th Investment Portfolio Valuation
19th Chapter Volatility Options
Appendix A featured Best Practices
Appendix B Call Option Class
Appendix C Date and Time

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Python financial Big data analytics PDF