In tri-reference point theory, four regions-failure, loss, gain and success-are formed by three reference points-minimum requirement (MR), status quo (SQ), and goal (G)-which play an important role in decision-making. Considering investors' three reference points with respect to investment returns, optimization models of portfolios including structured products are constructed by employing investors' maximum perceived value in tri-reference point theory as the objective under the premise of satisfying the safety-first principle. Then, a hybrid particle swarm optimization algorithm that is suitable for solving these models is designed. In this setting, the superiority of structured products relative to riskless assets and underlying assets are studied by changing the parameters in trireference point theory. The results show that structured products are the most favored by investors when both MR and G are relatively high. This is because under these circumstances, structured products are capable of satisfying investors' demand for relatively high returns under the premise of ensuring safety and in turn attract the most investors in the market.