Ebook Introduction to R for Quantitative Finance, by Gergely Daróczi
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Introduction to R for Quantitative Finance, by Gergely Daróczi
Ebook Introduction to R for Quantitative Finance, by Gergely Daróczi
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About the Author
Gergely Daróczi Gergely Daróczi is a Ph.D. candidate in Sociology with around eight years' experience in data management and analysis tasks within the R programming environment. Besides teaching Statistics at different Hungarian universities and doing data analysis jobs for several years, Gergely has founded and coordinated a UK-based online reporting startup company recently. This latter software or platform as a service which is called rapporter.net will potentially provide an intuitive frontend and an interface to all the methods and techniques covered in the book. His role in the book was to provide R implementation of the QF problems and methods.
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Product details
Paperback: 164 pages
Publisher: Packt Publishing (November 22, 2013)
Language: English
ISBN-10: 178328093X
ISBN-13: 978-1783280933
Product Dimensions:
7.5 x 0.4 x 9.2 inches
Shipping Weight: 13.3 ounces (View shipping rates and policies)
Average Customer Review:
2.7 out of 5 stars
14 customer reviews
Amazon Best Sellers Rank:
#885,507 in Books (See Top 100 in Books)
I really enjoyed this book. After working through the problems several times I realized how powerful R was and how many tools that are at my disposal. I think the author gives a great spread of very common financial calculations with repeatable examples. I am not am professional in any way but really felt it was good for someone who had a basic knowledge of quantitative finance and was looking to see how to apply that in R.Overall I think i got a great deal out of this book and it gives me much more confidence in working with R. Espeically for people just getting into either quant finance or working in RUsing the kindle version, i did have some annoying problems with the code. Because of 2 things. First off there are + signs on every line which is how its outputted in R, which you must remove. Also the kindle cut/paste function always gives the copyright and location. Which you have to delete out of every time you cut and paste. Its not really the authors fault just a quirk of the kindle cut and paste system. I did not subtract a star for this because of the kindle interface, however i can see where someone else would.
This book claims to be a book on R in finance. It provides very little information on either R or finance.I'll use one example to illustrate the faults of this book. The authors give an example of cointegration and hedging of airplane fuel with options on heating oil. The authors state that they assume that you have a background in finance. Fine. I've done this kind of hedging, but it was a year ago. Having a brief discussion of the relevant equations would be useful. This would provide a context for the R code.As far as the R code goes, all the authors really give are some function calls without much in the way of context. You would get almost as much reading the R on-line documentation.This book is of no use to anyone who knows something about modern quantitative finance and it's of no use when it comes to learning to use R for finance. I short, the book is of no use at all.Packt Publishing seems to specialize in short books that are at either poorly written or at a ridiculously introductory level. I also bought their Machine Learning with R. This could be retitled Machine Learning with R for High School students (and not High School students who are taking AP Calculus or Computer Science).
Is better to read the different web forums that this book. Is just a simple very light introduction to R...
The price seduces you and you click on buy. And start trying to come over your loss 30 minutes later. Lesson : Any R book which adds value beyond what is freely available on the internet is going to cost you upwards of USD 25. Sad, but true.
More for academics, not for use in actual investing.The portfolio optimization chapter is good.The text is refreshingly straightforward.On the other hand, not all of the the code is available for download.
The thin book has about 140 small pages and combines nine short contributed papers, which look like a set of notes for a master's-level finance course. Here's the list of topics, and the R packages in use.AR and GARCH estimation (timeSeries, zoo, FinTS, urca, rugarch)Mean-variance portfolio optimization (fPortfolio)CAPM / "beta" (n/a)Yield-curve fitting (termstrc)Black-Scholes, SDE simulation and copulae (fOptions, sde, copula)Extreme-value theory / GPD fitting (evir)Network analysis (igraph)With 10-20 pages per chapter, coverage is brief, and assumes that the reader knows the finance and statistics parts, and is familiar with R, so only the specific R examples need to be shown. This creates a problem, as finance/statistics/R-beginners are discouraged, while the non-beginners find sketchily explained basics. You really can find equally good, or better, references online - the R-Bloggers site has many; sometimes you can just look up the R package's vignette - but if you are willing to pay $15 for a convenience, go for it.UPD. With the benefit of a little more life experience, I would say: don't spend your time on *any* R book. Python is the way to go.
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