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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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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

Chapter 6.  Trading Using Machine Learning

In the capital market, machine learning-based algorithmic trading is quite popular these days and many companies are putting a lot of effort into machine learning-based algorithms which are either proprietary or for clients. Machine learning algorithms are programmed in such a way that they learn continuously and change their behavior automatically. This helps to identify new patterns when they emerge in the market. Sometimes patterns in the capital market are so complex they cannot be captured by humans. Even if humans somehow managed to find one pattern, humans do not have the tendency to find it efficiently. Complexity in patterns forces people to look for alternative mechanisms which identify such complex patterns accurately and efficiently.

In the previous chapter, you got the feel of momentum, pairs-trading-based algorithmic trading, and portfolio construction. In this chapter, I will explain step by step a few supervised and unsupervised...

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