How to compute n bivariate copulas in modern portfolio theory?

Hi everyone, i'm trying to explain the dependance structures between n financial stock returns. Instead of using a single n-variate copula, I tried to use n*(n-1)/2 copulas to explain the dependance structures one-to-one. But how can I find an optimal portfolio of stocks (using modern portfolio theory) using these bivariate copulas? I already found the best family and the correspondent parameter(s) for each bivariate copula. But now I don't know how to manage them... Here I'm finding the simulated returns of each one-to-one stock.

nPoints = 100;
R = zeros(nAsset,nAsset,nPoints,2);
for i=1:nAsset
    for j=1:i-1
        if strcmp(copula_type(i,j),'t')==1
            U = copularnd(copula_type(i,j), [1 copula_coefficients(i,j,1); copula_coefficients(i,j,1) 1], copula_coefficients(i,j,2), nPoints);
            R(i,j,:,:) = [marginal{i}.icdf(U(:,1)) marginal{j}.icdf(U(:,2))];
        elseif strcmp(copula_type(i,j),'Gaussian')==1
            U = copularnd(copula_type(i,j), [1 copula_coefficients(i,j,1); copula_coefficients(i,j,1) 1], nPoints);
            R(i,j,:,:) = [marginal{i}.icdf(U(:,1)) marginal{j}.icdf(U(:,2))];
        else
            U = copularnd(copula_type(i,j), copula_coefficients(i,j,1), nPoints);
            R(i,j,:,:) = [marginal{i}.icdf(U(:,1)) marginal{j}.icdf(U(:,2))];
        end
    end
end

I'd like to create a Markowitz's frontier using Expected Shortfall as risk measure, but I don't know how to manage these n*(n-1)/2 copulas :(

Please help me :)

Thanks, Enrico.