A couple of weeks back I published the first part of a full-chapter excerpt from my new book, Quantitative Investment Portfolio Analytics In R: An Introduction To R For Modeling Portfolio Risk and Return. Here’s the second half of this two-part excerpt of Chapter 5, which reviews the basics for factor analysis via R code. The chapter sample below focuses on additional analytics, including a primer on a close cousin to factor analysis: principal component analysis (PCA).  (Note: for a cleaner read, the footnotes that appear in the book have been removed for this web-based version of the chapter. For a complete list of the book’s chapters, see here. Keep in mind that all the code published in Quantitative Investment Portfolio Analytics In R can be accessed via a single file by way of a link that’s published in the book.)
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