This is the second post in the series about Multiple Factor Models. I will build on the code presented in the prior post, Multiple Factor Model – Fundamental Data, and I will show how to build Fundamental factors described in the CSFB Alpha Factor Framework. For details of the CSFB Alpha Factor Framework please...
The Multiple Factor Model can be used to decompose returns and calculate risk. Following are some examples of the Multiple Factor Models: The expected returns factor model: Commonality In The Determinants Of Expected Stock Returns by R. Haugen, N. Baker (1996) The expected returns factor model: CSFB Quantitative Research, Alpha Factor Framework on page...
In a recent post (here, by @teramonagi), Teramonagi mentioned the use of PCA to model yield curve, i.e. to obtain the three factor, "parallel shift", "twist" and "butterfly". As in Nelson & Siegel, if m is maturity, is the yield of the cu...
When creating a subset of a dataframe, I often exclude rows based on the level of a factor. However, the "levels" of the factor remain intact. This is the intended behavior of R, but it can cause problems in some cases. I finally discovered how to clea...
If you have a vector of factors it is easy to get the factor level; however, I always forget how to extract the factor value. I ran into the answer here.> x<-factor(c(round(rnorm(10),2),"A","B",NA))> x 1.61 1.12 1.26 0.09 -0.13 0.16 -...
Very often, especially when plotting data, I need to reorder the levels of a factor because the default order is alphabetical. There must be many ways of reordering the levels; however, I always forget which package to look in. A direct way of reorderi...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).