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Python for Finance

You're reading from   Python for Finance If your interest is finance and trading, then using Python to build a financial calculator makes absolute sense. As does this book which is a hands-on guide covering everything from option theory to time series.

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Product type Paperback
Published in Apr 2014
Publisher
ISBN-13 9781783284375
Length 408 pages
Edition 1st Edition
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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 (14) Chapters Close

Preface 1. Introduction and Installation of Python 2. Using Python as an Ordinary Calculator FREE CHAPTER 3. Using Python as a Financial Calculator 4. 13 Lines of Python to Price a Call Option 5. Introduction to Modules 6. Introduction to NumPy and SciPy 7. Visual Finance via Matplotlib 8. Statistical Analysis of Time Series 9. The Black-Scholes-Merton Option Model 10. Python Loops and Implied Volatility 11. Monte Carlo Simulation and Options 12. Volatility Measures and GARCH Index

Chapter 8. Statistical Analysis of Time Series

Understanding the properties of financial time series is very important in finance. In this chapter, we will discuss many issues, such as downloading historical prices, estimating returns, total risk, market risk, correlation among stocks, correlation among different countries' markets from various types of portfolios, and a portfolio variance-covariance matrix; constructing an efficient portfolio and an efficient frontier; estimating Roll (1984) spread; and also estimating the Amihud (2002) illiquidity measure, and Pastor and Stambaugh's (2003) liquidity measure for portfolios. The two related Python modules used are Pandas and statsmodels.

In this chapter, we will cover the following topics:

  • Installation of Pandas and statsmodels
  • Using Pandas and statsmodels
  • Open data sources, and retrieving data from Excel, text, CSV, and MATLAB files, and from a web page
  • Date variable, DataFrame, and merging different datasets by date
  • Term...
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