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Mastering Python for Finance

You're reading from   Mastering Python for Finance Implement advanced state-of-the-art financial statistical applications using Python

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Length 426 pages
Edition 2nd Edition
Languages
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Author (1):
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James Ma Weiming James Ma Weiming
Author Profile Icon James Ma Weiming
James Ma Weiming
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Python FREE CHAPTER
2. Overview of Financial Analysis with Python 3. Section 2: Financial Concepts
4. The Importance of Linearity in Finance 5. Nonlinearity in Finance 6. Numerical Methods for Pricing Options 7. Modeling Interest Rates and Derivatives 8. Statistical Analysis of Time Series Data 9. Section 3: A Hands-On Approach
10. Interactive Financial Analytics with the VIX 11. Building an Algorithmic Trading Platform 12. Implementing a Backtesting System 13. Machine Learning for Finance 14. Deep Learning for Finance 15. Other Books You May Enjoy

The Capital Asset Pricing Model and the security market line

A lot of the financial literature devotes exclusive discussions to the Capital Asset Pricing Model (CAPM). In this section, we will explore key concepts that highlight the importance of linearity in finance.

In the famous CAPM, the relationship between risk and rates of return in a security is described as follows:

For a security, i, its returns are defined as Ri and its beta as βi. The CAPM defines the return of the security as the sum of the risk-free rate, Rf, and the multiplication of its beta with the risk premium. The risk premium can be thought of as the market portfolio's excess returns exclusive of the risk-free rate. The following is a visual representation of the CAPM:

Beta is a measure of the systematic risk of a stock a risk that cannot be diversified away. In essence, it describes...

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