Stochastic signaling is investigated under second and fourth moment constraints for the detection of scalar-valued binary signals in additive noise channels. Sufficient conditions are derived to determine when the use of stochastic signals instead of deterministic ones can or cannot enhance the error performance of a given binary communications system. Also, a convex relaxation approach is employed to obtain approximate solutions of the optimal stochastic signaling problem. Finally, numerical examples are presented, and extensions of the results to M-ary communications systems and to other criteria than the average probability of error are discussed.