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Learning Quantitative Finance with R

You're reading from  Learning Quantitative Finance with R

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781786462411
Pages 284 pages
Edition 1st Edition
Languages
Authors (2):
Dr. Param Jeet Dr. Param Jeet
Profile icon Dr. Param Jeet
PRASHANT VATS PRASHANT VATS
Profile icon PRASHANT VATS
View More author details

Table of Contents (16) Chapters

Learning Quantitative Finance with R
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to R 2. Statistical Modeling 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

Standardization


In statistics, standardization plays a crucial role as we have various attributes for modeling and all of them have different scales. So for comparison purposes, we need to standardize the variables to bring them on the same scale. Centering the values and creating the z scores is done in R by the scale() function. It takes the following arguments:

  • x: A numeric object

  • center: If TRUE, the object's column means are subtracted from the values in those columns (ignoring NAs); if FALSE, centering is not performed

  • scale: If TRUE, the centered column values are divided by the column's standard deviation (when center is also TRUE; otherwise, the root mean square is used); if FALSE, scaling is not performed

If we want to center the data of Volume in our dataset, we just need to execute the following code:

>scale(Sampledata$Volume, center=TRUE, scale=FALSE) 

If we want to standardize the data of volume in our dataset, we just need to execute the following code:

>scale(Sampledata...
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