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Learning Quantitative Finance with R

You're reading from   Learning Quantitative Finance with R Implement machine learning, time-series analysis, algorithmic trading and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786462411
Length 284 pages
Edition 1st Edition
Languages
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Authors (2):
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PRASHANT VATS PRASHANT VATS
Author Profile Icon PRASHANT VATS
PRASHANT VATS
Dr. Param Jeet Dr. Param Jeet
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Dr. Param Jeet
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to R 2. Statistical Modeling FREE CHAPTER 3. Econometric and Wavelet Analysis 4. Time Series Modeling 5. Algorithmic Trading 6. Trading Using Machine Learning 7. Risk Management 8. Optimization 9. Derivative Pricing

Capital asset pricing model


The capital asset pricing model (CAPM) model helps to gauge risk contributed by security or portfolio to its benchmark and is measured by beta (). Using the CAPM model, we can estimate the expected excess return of an individual security or portfolio which is proportional to its beta:

Here:

  • E(Ri): Expected return of security

  • E(Rm): Expected return of market

  • Ri: Rate of return of security

  • Rf: Risk Free rate of return

  • Rm: Benchmark or market return

  • : Beta of the security

CVX is regressed against DJI using linear model as per equation 5.4.

Here I used zero as risk-free return in the following command:

>rf<- rep(0,length(dji))
>model <- lm((ret_cvx  -rf) ~ (ret_dji -rf) )
> model
Call:
lm(formula = (ret_cvx - rf) ~ (ret_dji - rf))
Coefficients:
(Intercept)  ret_dji
-0.0002013    1.1034521 

You can see the intercept term in the above result is alpha (-0.0002013) and coefficient for ret_dji is beta (1.1034521). However, you can also use the PerformanceAnalytics...

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