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Python for Finance Cookbook

You're reading from   Python for Finance Cookbook Over 50 recipes for applying modern Python libraries to financial data analysis

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781789618518
Length 432 pages
Edition 1st Edition
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Author (1):
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Eryk Lewinson Eryk Lewinson
Author Profile Icon Eryk Lewinson
Eryk Lewinson
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Table of Contents (12) Chapters Close

Preface 1. Financial Data and Preprocessing 2. Technical Analysis in Python FREE CHAPTER 3. Time Series Modeling 4. Multi-Factor Models 5. Modeling Volatility with GARCH Class Models 6. Monte Carlo Simulations in Finance 7. Asset Allocation in Python 8. Identifying Credit Default with Machine Learning 9. Advanced Machine Learning Models in Finance 10. Deep Learning in Finance 11. Other Books You May Enjoy

Implementing the Fama-French three-factor model in Python

In their famous paper, Fama and French expanded the CAPM model by adding two additional factors explaining the excess returns of an asset or portfolio. The factors they considered are:

  • The market factor (MKT): It measures the excess return of the market, analogical to the one in the CAPM.
  • The size factor, SMB (Small Minus Big): It measures the excess return of stocks with a small market cap over those with a large market cap.
  • The value factor, HML (High Minus Low): It measures the excess return of value stocks over growth stocks. Value stocks have a high book-to-market ratio, while the growth stocks are characterized by a low ratio.

The model can be represented as follows:

Or in its simpler form:

Here, E(ri) denotes the expected return on asset i, rf is the risk-free rate (such as a government bond), and α is...

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