Vectorizing tensor outer product using permute is slower than for-loop

Hi Everyone. I have the following code for computing outer products of two second-order tensors to get a fourth-order tensor. I did it using for-loops. I also attempted to vectorize using permute and bsxfun. I timed both versions. But the for-loop turns out to be faster. I am not able to understand if there is a better way to vectorize.

clear;
clc;

F = rand(200); %I run out of memory in bsxfun() for larger 2D arrays

C_for  = zeros(3,3,3,3);
tic;
for l=1:3
    for M=1:3
        for n=1:3
            for O=1:3
                C_for(l,M,n,O) = F(M,l)*F(O,n);
            end
        end
    end
end
toc;

tic;  
A = permute(F,[2,1,3,4]);
B = permute(F,[3,4,2,1]);
C_vec = bsxfun(@times,A,B);
toc;

My output for tic-toc is:

 For loop: Elapsed time is 0.000289 seconds
 Vectorized: Elapsed time is 8.725277 seconds

Any suggestions to improve the vectorization?

 Regards,
 Amit