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Mastering R for Quantitative Finance

You're reading from   Mastering R for Quantitative Finance Use R to optimize your trading strategy and build up your own risk management system

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Length 362 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (15) Chapters Close

Preface 1. Time Series Analysis FREE CHAPTER 2. Factor Models 3. Forecasting Volume 4. Big Data – Advanced Analytics 5. FX Derivatives 6. Interest Rate Derivatives and Models 7. Exotic Options 8. Optimal Hedging 9. Fundamental Analysis 10. Technical Analysis, Neural Networks, and Logoptimal Portfolios 11. Asset and Liability Management 12. Capital Adequacy 13. Systemic Risks Index

Summary

In this chapter, we reviewed some important concepts of time series analysis, such as cointegration, vector-autoregression, and GARCH-type conditional volatility models. Meanwhile, we have provided a useful introduction to some tips and tricks to start modeling with R for quantitative and empirical finance. We hope that you find these exercises useful, but again, it should be noted that this chapter is far from being complete both from time series and econometric theory, and from R programming's point of view. The R programming language is very well documented on the Internet, and the R user's community consists of thousands of advanced and professional users. We encourage you to go beyond books, be a self-learner, and do not stop if you are stuck with a problem; almost certainly, you will find an answer on the Internet to proceed. Use the documentation of R packages and the help files heavily, and study the official R-site, http://cran.r-project.org/, frequently. The remaining chapters will provide you with numerous additional examples to find your way in the plethora of R facilities, packages, and functions.

You have been reading a chapter from
Mastering R for Quantitative Finance
Published in: Mar 2015
Publisher:
ISBN-13: 9781783552078
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