To establish bounds in this way, you have to start with some claim about the distribution of the input data. In this case, the data is natural human language, so it's difficult or impossible to directly state what distribution the input was drawn from. Even worse, the prize is for compressing a particular text, not a sample from a distribution, so tight bounds are actually not possible to compute.

There is some discussion on the Hutter prize page, under "What is the ultimate compression of enwik9?"

http://prize.hutter1.net/hfaq.htm