This is a "dual" question of a popular post on math.se.
Some mathematical objects in computational complexity theory have multiple-letter names. Complexity classes such as $\mathbf{BPP}$ have an established multiple-letter name. So do some computational problems, although the naming convension seems to vary.
I am happy with names such as $\mathbf{BPP}$; however, when I write $\mathbf{PromiseBPP}$ on paper or blackboard over and over, I wish its name were more concise (in fact, some authors prefer to write it as $\mathbf{prBPP}$).
In a popular textbook in complexity, a polynomial that appears in the chapter on algebraic complexity of the book is named as $\mathtt{EXACTLY-ONCE}$, which I do not think is a suitable name to write by hand.
Considering the arguments in the original post on math.se, the pros of shorter names seem to apply more to TCS than those of longer names. After all, what theoreticians do is to work on paper and blackboards, not to write large and complex software with editors that do auto-completion.
Some early literature takes different approach to names. In Cinderella Book, computational problems have concise names such as $L_{\mathrm h}$ (which stands for the Hamiltonian path problem).
Thus the question is: why do theoreticians in CS use multiple-letter variables? Or do we have to give long names to objects we are working on?