paFm: Compute cumulative mean attribution for factor models
In sangeeuw/factorAnalytics: Factor Analytics

Description Usage Arguments Details Value Author(s) References See Also Examples

Decompose total returns into returns attributed to factors and specific returns. An object of class "pafm" is generated, with methods for generic functions plot, summary and print.

1	paFm(fit, ...)

`fit`	an object of class `tsfm`, `sfm` or `ffm`.
`...`	other arguments/controls passed to the fit methods.

Total returns can be decomposed into returns attributed to factors and specific returns.
R_t = ∑ b_k * f_kt + u_t, t=1...T
b_k is exposure to factor k and f_kt is factor k's return at time t. The return attributed to factor k is b_k * f_kt and specific return is u_t.

The returned object is of class "pafm" containing

`cum.ret.attr.f`	N X K matrix of cumulative return attributed to factors.
`cum.spec.ret`	length-N vector of cumulative specific returns.
`attr.list`	list of time series of attributed returns for every portfolio.

Yi-An Chen and Sangeetha Srinivasan

Grinold, R. and Kahn, R. (1999) Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk. McGraw-Hill.

fitTsfm, fitSfm, fitFfm for the factor model fitting functions.

The pafm methods for generic functions: plot.pafm, print.pafm and summary.pafm.

data(managers)
fit <- fitTsfm(asset.names=colnames(managers[, (1:6)]), 
               factor.names=c("EDHEC.LS.EQ","SP500.TR"), data=managers)
# without benchmark
fm.attr <- paFm(fit)