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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

Chapter 3. Econometric and Wavelet Analysis

In financial analytics, we need techniques to do predictive modeling for forecasting and finding the drivers for different target variables. In this chapter, we will discuss types of regression and how we can build a regression model in R for building predictive models. Also we will discuss, how we can implement a variable selection method and other aspects associated with regression. This chapter will not contain theoretical description but will just guide you in how to implement a regression model in R in the financial space. Regression analysis can be used for doing forecast on cross-sectional data in the financial domain. We will also cover frequency analysis of the data, and how transformations such as Fast Fourier, wavelet, Hilbert, haar transformations in time, and frequency domains help to remove noise in the data.

This chapter covers the following topics:

  • Simple linear regression

  • Multivariate linear regression

  • Multicollinearity

  • ANOVA

  • Feature...

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