A simple example:
Suppose that your VaR is at the 99.5th percentile. Consider two identical and independent loss distributions which take the value 100 0.3% of the time and 0 otherwise.
The VaR of each distribution is 0, as at the 99.5th percentile of the loss distribution we expect to have no loss.
The sum of the distributions takes the value 0 99.4009% of the time (97%*97%) and is non-zero the rest of the time. So in this case the sum has a VaR which is strictly greater than 0, but because the individual distributions have VaR of 0, the sum of the VaRs is still 0.
Hope this answers your question, basically when you have a very skew distribution the VaR fails subadditivity.
It is important to realise that VaR is not always subadditive because often people take two VaR and add them together and say "well this is an upper bound". Since this isn't true it can cause wrong decisions to be made.
Last edited by a moderator: Feb 11, 2015