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Python for Finance

You're reading from  Python for Finance

Product type Book
Published in Apr 2014
Publisher
ISBN-13 9781783284375
Pages 408 pages
Edition 1st Edition
Languages
Author (1):
Yuxing Yan Yuxing Yan
Profile icon Yuxing Yan

Table of Contents (20) Chapters

Python for Finance
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction and Installation of Python Using Python as an Ordinary Calculator Using Python as a Financial Calculator 13 Lines of Python to Price a Call Option Introduction to Modules Introduction to NumPy and SciPy Visual Finance via Matplotlib Statistical Analysis of Time Series The Black-Scholes-Merton Option Model Python Loops and Implied Volatility Monte Carlo Simulation and Options Volatility Measures and GARCH Index

Summary


In this chapter, we showed how to use the matplotlib module to vividly explain many financial concepts by using graph, pictures, color, and size. For example, in a two-dimensional graph, we showed a few stocks' returns and volatility, the NPV profile, multiple IRRs, and the portfolio diversification effect.

In Chapter 8, Statistical Analysis of Time Series, first we demonstrate how to retrieve historical time series data from several public data sources, such as Yahoo! Finance, Google Finance, Federal Reserve Data Library, and Prof. French's Data Library. Then, we discussed various statistical tests, such as T-test, F-test, and normality test. In addition, we presented Python programs to run capital asset pricing model (CAPM), run a Fama-French three-factor model, estimate the Roll (1984) spread, estimate Value at Risk (VaR) for individual stocks, and also estimate the Amihud (2002) illiquidity measure, and the Pastor and Stambaugh (2003) liquidity measure for portfolios. For the...

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