We consider the problem of finding a shortest path in a directed graph with a quadratic objective func- tion (the QSPP). We show that the QSPP cannot be approximated unless P = NP . For the case of a convex objective function, an n -approximation algorithm is presented, where n is the number of nodes in the graph, and APX -hardness is shown. Furthermore, we prove that even if only adjacent arcs play a part in the quadratic objective function, the problem still cannot be approximated unless P = NP . In order to solve the problem we first propose a mixed integer programming formulation, and then devise an ef- ficient exact Branch-and-Bound algorithm for the general QSPP, where lower bounds are computed by considering a reformulation scheme that is solvable through a number of minimum cost flow problems. In our computational experiments we solve to optimality different classes of instances with up to 10 0 0 nodes.