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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

General time series


A time series is the sequence of data usually collected at regular intervals. There are a lot of domains where information is stored in time series form and needs to be analyzed for future planning.

For example, in the financial domain, we have the daily/monthly data available for unemployment, GDP, daily exchange rates, share prices, and so on. So all the investors or the people working in financial institutions need to plan their future strategy and so they want to analyze the time series data. Thus time series play a crucial role in the financial domain.

Time series data is very unpredictable in nature and to understand the data we need to decompose the time series data into various components, as given here:

  • Trend: This is a pattern of long-term movements in the mean of time series data. The trend may be linear or nonlinear and keeps changing across time. There is no sure process to identify the exact trend but if it is behaving monotonously then it is possible to estimate...

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