Part I presents a formulation to optimize reserves for contingent events while explicitly including their response times. Part II highlights the implications of using this formulation in a reserves market. There are four aspects of the formulation that are of interest: (1) the performance of the solver, (2) the importance of inertia and contingency size. These implications are highlighted through two examples. (3) The proposed formulation is compared against a reserve optimization which does not distinguish between different response speeds, but adjusts the reserve requirement to satisfy the same frequency limits. Differentiating between response speeds within the optimization can provide a 23% reduction in total reserve requirement on average, which improves to a reduction of 52% in low inertia conditions. (4) A marginal pricing methodology is developed which prices reserve in a market context, and gives a unique price to each reserve provider depending on response speed. This gives incentive for reserve providers to improve response speed.