In computational markets utilizing algorithms that establish a market equilibrium (general equilibrium), competitive behavior is usually assumed: each agent makes its demand (supply) decisions so as to maximize its utility (profit) assuming that it has no impact on market prices. However, there is a potential gain from strategic behavior (via speculating about others) because an agent does affect the market prices, which affect the supply/demand decisions of others, which again affect the market prices that the agent faces. We present a method for computing the maximal advantage of speculative behavior in equilibrium markets. Our analysis is valid for a wide variety of known market protocols. We also construct demand revelation strategies that guarantee that an agent can drive the market to an equilibrium where the agent's maximal advantage from speculation materializes. Our study of a particular market shows that as the number of agents increases, gains from speculation decrease, often turning negligible already at moderate numbers of agents. The study also shows that under uncertainty regarding others, competitive acting is often close to optimal, while speculation can make the agent significantly worse off, even if the agent's beliefs are just slightly biased. Finally, protocol dependent game theoretic issues related to multiple agents counterspeculating are discussed.