Store the variance-covariance matrix of residuals into a matrix

[Yuyi He]

Dear all,

I am doing a project on the predictability of an asset pricing model. In order to test the joint significance of my pricing errors, I need to compute the following test statistic.

To do that, I need first compute the variance-covariance matrix of the alpha hat(pricing errors) with the following formula:

However, I encounter a problem calculating the sigma(variance-covariance matrix of residuals from time-series regressions). I succeeded to compute the variance-covariance matrix with the following code:

corr pf1-pf30,cov

But I cannot find a way to store this matrix so that I can use it in the following computations.
Here is an extract of the main variables in my dataset.

* Example generated by -dataex-. To install: ssc install dataex
clear
input str5 portfolio float(portfolio_n residual pf1 pf2 pf3 pf4 pf5 pf6 pf7 pf8 pf9 pf10 pf11 pf12 pf13 pf14 pf15 pf16 pf17 pf18 pf19 pf20 pf21 pf22 pf23 pf24 pf25 pf26 pf27 pf28 pf29 pf30)
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end

Here is the code that I used to generate the residuals for each portfolio.

gen b_mktrf = .
gen b_smb = .
gen b_hml = .
gen b_lmu = .
gen residual=.

sort portfolio t_month

egen portfolio_n=group(portfolio)
forvalues y=1/30{
    capture{
        quietly regress ret_e mktrf smb hml LMU if portfolio_n == `y'
        replace b_mktrf =_b[mktrf]   if portfolio_n == `y'
        replace b_smb =_b[smb]   if portfolio_n == `y'
        replace b_hml =_b[hml]   if portfolio_n == `y'
        replace b_lmu =_b[LMU]   if portfolio_n == `y'
        predict temp, residuals
        replace residual = temp  if portfolio_n  == `y'
        drop temp
    }
}

tab portfolio_n,gen(pf)
forvalues y=1/30{
    replace pf`y'=residual if  portfolio_n == `y'
}

Could someone help me out please?

[Rich Goldstein]

as it says in the help file, this is already saved automatically in the matrix r(C) - just make then into your own matrix before doing anything else so you don't lose it

[Yuyi He]

Indeed, thank you so much!