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Mastering R for Quantitative Finance

Mastering R for Quantitative Finance

By : Gabler
4 (11)
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Mastering R for Quantitative Finance

Mastering R for Quantitative Finance

4 (11)
By: Gabler

Overview of this book

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.
Table of Contents (15 chapters)
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14
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.

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