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The state-preference approach offers a general framework for theoretical exploration in asset pricing, yet it struggles with empirical application. Recent advancements in asset pricing have shifted away from the restrictive assumptions of the CAPM, which relies on an arbitrary market portfolio and emphasizes efficiency. In contrast, models like the arbitrage pricing theory maintain a linear risk-return relationship by assuming no arbitrage opportunities, making them more empirically viable. However, these models fall short in explaining the economic dynamics of risk premia. The "conditional" CAPM introduces an econometric framework that links changing economic conditions to the variability of risk premia, though it still relies on ad-hoc assumptions regarding the pricing kernel's economic nature. A significant evolution in asset pricing modeling involves reversing the inquiry: rather than imposing strict conditions on distributions and preferences, this approach utilizes observed returns to establish necessary restrictions on the stochastic properties of the pricing kernel. Typically, a simple Euler-type equation is employed to characterize this innovative method.