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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

Diving into deeper concepts

The focus of this chapter will be on how to retrieve economic, finance, and accounting related data, especially public data. For example, Yahoo Finance offers rich data, such as historical trading price, current price, option data, annual and quarterly financial statements, and bond data. Such publicly available data could be used to estimate β (market risk), volatility (total risk), Sharpe ratio, Jensen's alpha, Treynor ratio, liquidity, transaction costs, and conduct financial statement analysis (ratio analysis) and performance evaluation. In future chapters, the topics mentioned would be discussed in more detail. For the public data related to economics, finance, and accounting, many wonderful sources are available, see the following table:

Name

Data types

Yahoo Finance

Historical price, annual and quarterly financial statements, and so on

Google Finance

Current, historical trading prices

Federal Reserve Economic Data

Interest rates, rates...

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