<p>We formulate a two-agent infinite horizon stochastic optimization model for demand response decision making of a load serving entity (LSE) in a stochastic energy market that addresses different types of customers and energy resources simultaneously. Finding stochastic bounds for this real-time optimization problem provides insight into the behavior of the system. However, a question arises whether bounds exist when we have two different customer agents. The present study develops a research methodology to answer this question. In stochastic programming (SP), a wait-and-see solution is at least as good as an optimal policy. On the other hand, a policy that uses the expected value problem is no better than an optimal policy. This is well established in SP when there is a single agent. Our experiments show that two separate agents with perfect information may in fact yield inferior results than when both agents follow a mean value problem policy. Nevertheless, we have derived bounds when the first agent follows the same set of actions. A two-agent demand response problem has been used as a case study to show this claim, and computational experiments are provided. The quality of decision-making policies is evaluated in a simulation that includes uncertainties.</p>