This work studies the problem of decision-making under risk by agents whose information processing abilities may be limited. The constructed theoretical framework grounds on findings from economic laboratory experiments, incorporates existing neuroscience knowledge, and is implemented using information-theoretic formalism. Activation of the above information-processing constraints distorts the subjective perception of the objective stochastic environment the agent operates in, and the constrained-optimal decision-making requires appropriate adjustments. In the selected application, a general equilibrium macro-finance model, such biases of subjective perspective as overconfidence, pessimism and categorization thus emerge endogenously. The theoretical implications receive empirical support in a mutually consistent way: according to (cross-checked) calibrations, they allow us to reverse-engineer and rationalize the phenomena known as the equity premium/risk-free rate puzzles; as well as contribute to the understanding of such regularities as the portfolio underdiversification puzzle, style investing and the non-monotone pricing kernel puzzle. On the other hand, these results also help rationalize, by formulating certain optimizing foundations behind, the experimental evidence that underlies the Allais paradox and that is systematized in, e.g., the (cumulative) prospect theory.