Compare SFM estimated using robust estimators with that estimated by OLS

This function provies a simple plug and play option for user to compare the SFM estimates by lm and lmrobdetMM functions, using the fit.models framework. This will allow for an easier comparison using charts and tables

SFM.fit.models(
  Ra,
  Rb,
  Rf = 0,
  family = "mopt",
  which.plots = NULL,
  plots = TRUE
)

Arguments

Ra

an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns

Rb

return vector of the benchmark asset

Rf

risk free rate, in same period as your returns

family

(Optional): If method == "Robust": This is a string specifying the name of the family of loss function to be used (current valid options are "bisquare", "opt" and "mopt"). Incomplete entries will be matched to the current valid options. Defaults to "mopt". Else: the parameter is ignored

which.plots

specify the plot numbers that you want to see. Default option is that program will ask you to choose a plot

plots

Boolean to output plots after the function. Defaults to TRUE

Author

Dhairya Jain

Examples

if (FALSE) { # \dontrun{
# First we load the data
    data(managers)
    mgrs <- managers["2002/"]  # So that all have managers have complete history
    names(mgrs)[7:10] <- c("LSEQ","SP500","Bond10Yr","RF") # Short names for last 3
    
    # NOTE: Use plots=TRUE to be able to see plots

    fitModels <- SFM.fit.models(mgrs$HAM1,mgrs$SP500,Rf = mgrs$RF, plots=FALSE)
    coef(fitModels)
    summary(fitModels)
    class(fitModels)
    
    SFM.fit.models(mgrs$HAM1, mgrs$SP500, Rf = mgrs$RF, plots=FALSE)
    
    SFM.fit.models(mgrs[,6], mgrs[,8], Rf=.035/12, plots=FALSE) 
    
    SFM.fit.models(mgrs$HAM6, mgrs$SP500, Rf=.035/12, family = "mopt", 
                   which.plots = c(1,2), plots=FALSE) 
     
     SFM.fit.models(mgrs$HAM2, mgrs$SP500, Rf = mgrs$RF, family = "opt", 
                    plots=FALSE)
} # }