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I've read that the laplace distribution is better for forecasting purposes than the normal distribution due to it better accounting for fat tails. However, when I run the numbers in matlab, laplace ends up with skinnier tails than a normal distribution. Am I doing anything wrong? Here is the code:

%laplace distribution

a = laprnd(755,100000,0,0.0034);
for x = 1:length(a)
   rets(x) = prod(1+a(:,x))-1;
end

[sum(rets>.0419)/length(rets),sum(rets<-.1688)/length(rets)]



ans = 

0.3122    0.0264





%Normal Distribution

j = normrnd(0,0.0034,755,100000);
for y = 1:length(j)
    retsj(y) = prod(1+j(:,y))-1;
end

[sum(retsj>.0419)/length(retsj),sum(retsj<-.1688)/length(retsj)]




ans = 

0.3151    0.0267

laprnd code is here: https://www.mathworks.com/matlabcentral/fileexchange/13705-laplacian-random-number-generator

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