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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Chapter 4. Sources of Data

Since our society entered a so-called information era, we have been engulfed by a huge amount of information or data. For this very reason, there is an increasing demand for persons armed with data handling skills, such as data scientists or graduates from business analytics programs. Kane (2006) proposed an open source finance concept which consists of three components:

  • The use of open source software in testing hypotheses and implementing investment strategies
  • Cheap access to financial data
  • Replication to confirm published research results

In this book, these three components are simply called: open software, open data, and open codes. Python is one of the best-known pieces of open source software. At the moment, usage of public data is quite inconsistent with the current environment. In this book, we use a huge amount of data, especially public data. In this chapter, the following topics will be covered:

  • Open source finance
  • Source of macro-economic data...
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