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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
Author Profile Icon Dr. Param Jeet
Dr. Param Jeet
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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

Multivariate linear regression


In multiple linear regression, we try to explain the dependent variable in terms of more than one predictor variable. The multiple linear regression equation is given by the following formula:

Here are multiple linear regression parameters and can be obtained by minimizing the sum of squares, which is also known as the OLS method of estimation.

Let us an take an example where we have the dependent variable StockYPrice and we are trying to predict it in terms of independent variables StockX1Price, StockX2Price, StockX3Price, and StockX4Price, which are present in the dataset DataMR.

Now let us fit the multiple regression model and get parameter estimates of multiple regression:

> MultipleR.lm = lm(StockYPrice ~  StockX1Price + StockX2Price +  StockX3Price + StockX4Price,  data=DataMR) 
> summary(MultipleR.lm) 

When we execute the preceding code, it fits the multiple regression model on the data and gives the basic summary of statistics associated...

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