Hi R,

 

I have dummy exposures on the RHS of the regression equation and to
these I add the standardized scores of 4 Barra risk indices. 

LHS of the regression is the stock excess returns

R(i) = a(i) + d1(i)*f1(i) + d2(i)*f2(i) + ... + dn(i)*fn(i) +
x1(i)*g1(i) + ... + x4(i)*g4(i) + e(i)

where

R(i) is the excess return of stock i
a(i) is the intercept term
dj(i), j = 1, ..., n are the dummy exposures
fj(i), j = 1, ..., n are the dummy returns estimated in the regression 
xj(i), j = 1, 2, 3, 4 are the risk index exposures
gj(i), j = 1, 2, 3, 4 are the risk index returns estimated in the
regression
e(i) is the residual term

 

summary(lm(as.formula(paste("final_dat[[i]][,2]~",paste(gsub("
",".",(names(final_dat[[i]])[3:24])),collapse="+"))),final_dat[[i]]))[[4
]]

 

So my question is- am I correct in regressing stock returns against a
combination of dummy variables and zscores ? Also to get the actual
factor returns can I directly add the intercept to dummy returns
estimated in the regression in spite of the presence of the z-scores in
the regression?

 

Thank you,

Ravi

 

 

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