Download Ebook Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return, by James Picerno
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Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return, by James Picerno
Download Ebook Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return, by James Picerno
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Product details
Paperback: 134 pages
Publisher: CreateSpace Independent Publishing Platform (June 18, 2018)
Language: English
ISBN-10: 1987583515
ISBN-13: 978-1987583519
Product Dimensions:
6 x 0.3 x 9 inches
Shipping Weight: 6.7 ounces (View shipping rates and policies)
Average Customer Review:
4.5 out of 5 stars
2 customer reviews
Amazon Best Sellers Rank:
#242,169 in Books (See Top 100 in Books)
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?
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