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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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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

Simple linear regression


In simple linear regression, we try to predict one variable in terms of a second variable called a predictor variable. The variable we are trying to predict is called the dependent variable and is denoted by y, and the independent variable is denoted by x. In simple linear regression, we assume a linear relationship between the dependent attribute and predictor attribute.

First we need to plot the data to understand the linear relationship between the dependent variable and independent variable. Here our, data consists of two variables:

  • YPrice: Dependent variable

  • XPrice: Predictor variable

In this case, we are trying to predict Yprice in terms of XPrice. StockXprice is the independent variable and StockYprice is the dependent variable. For every element of StockXprice, there is an element of StockYprice, which implies one-to-one mapping between elements of StockXprice and StockYprice.

A few lines of data used for the following analysis are displayed using the following...

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