Motivated by the recently launched 2CM data trading platform of China Mobile Hong Kong, we study the optimal user mobile data trading problem under the future demand uncertainty. We consider a brokerage-based market, where sellers and buyers propose their selling and buying prices and quantities to the trading platform, respectively. The platform acts as a broker, which facilitates the trade by matching the supply and demand. To understand users' realistic trading behaviors, we use prospect theory (PT) from behavioral economics in the modeling, which leads to a challenging non-convex optimization problem. Nevertheless, we are able to determine the unique optimal solution in closed-form, by utilizing the unimodal structure of the objective function. When comparing with the benchmark expected utility theory (EUT), we show that a PT user with a low reference point is more willing to buy mobile data. Moreover, when the probability of high demand is low, comparing with an EUT user, a PT user is more willing to buy mobile data due to the probability distortion.