Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return Paperback – June 18, 2018

It is seldom I find a book on programming that I feel hits the right balance between application and programming language, but for me this one hit the sweet spot. For those with a bit of investment savvy and a bit of R programming skills, this book succintly covers a number of topics familiar to quants who apply mathematical methods to the analysis of investing. What I liked most about the book were its simple examples, pulling primarily from the Performance Analytics library. The book covers backtesting, “optimal” portfolios, factor analysis, and various forms of risk assessment. It’s a very small 123-page book, so don’t expect to be taught R programming and don’t expect derivations and long-winded explanations of complex portfolio analysis methods. The book is designed for those who know a bit about R programming (the more experience the better) and who understand the fundamentals of quantitative measures of investing (things like the definition of volatility, the reason for diversification of portfolios, etc.). For the money I found this one to be excellent and to deliver more useful portfolio analysis firepower than many other books I own that contain far more pages.

I teach an alternative investing course, so this book caught my eye when it came out last summer. It aligns with my view that the key to leveraging the capabilities of any language is leveraging the IP embedded in the available package libraries. I could see adding more packages to expand on this fine book that I recommend for anyone serious about quantitative investing using modern methods for portfolio selection coupled with traditional trading rules.I gave it 4 stars because the book is printed on a small paper and I like big books. Perhaps a kindle version would solve this?

I have been reading some of the articles on capitalspectator.com and even occasionally going through some of the R codes. This book is not for beginners. But it can definitely help someone with basic R for finance programming skills bring their knowledge to another level. It is concise, goes right to the point and covers a broad range of quant finance topics. Students of R finance can use other books that give more details on the basics and background theory. Then use this one as the core for practical assignments. This is just a wonderful book to have in your library.

Book is a basic but practical intro into portfolio measurement in R. Good start in the R journey for beginners.

This book (actually novella I think) is ok. It's essentially a short manual for the Performance Analytics package in R. It claims to be an intro to R with applications to investments. It fails as an intro and for someone with a lot of experience in R, it also fails to add any insights in quant applications. You're better off to print the manual to the Performance Analytics package for free. This book should cost maybe $4.99 not over $30! What a money grab.