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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 8. Time-Series Analysis

In finance and economics, a huge amount of our data is in the format of time-series, such as stock prices and Gross Domestic Products (GDP). From Chapter 4, Sources of Data, it is shown that from Yahoo!Finance, we could download daily, weekly, and monthly historical price time-series. From Federal Reserve Bank's Economics Data Library (FRED), we could retrieve many historical time-series such as GDP. For time-series, there exist many issues, such as how to estimate returns from historical price data, how to merge datasets with the same or different frequencies, seasonality, and detect auto-correlation. Understanding those properties is vitally important for our knowledge development.

In this chapter, the following topics will be covered:

  • Introduction to time-series analysis
  • Design a good date variable, and merging different datasets by date
  • Normal distribution and normality test
  • Term structure of interest rates, 52-week high, and low trading strategy...
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