This paper considers the theoretical framework of the consumption-based asset-pricing model and derives successive approximations of the modified basic pricing equation using Taylor series expansions of the investor’s utility function during the averaging time interval Δ. For linear and quadratic Taylor approximations we derive new expressions for the mean asset price, mean payoff, their volatilities, skewness and amount of asset that delivers max to investor’s utility. We introduce new market-based price probability determined by statistical moments of the market trade values and volumes. We show that the market-based price probability results zero correla-tions between time-series of n-th power of price pn and trade volume Un, but doesn’t cause statis-tical independence and we derive correlation between time-series of price p and squares of trade volume U2. The market-based treatment of the random trade price describes impact of the size of market trade values and volumes on price probability. Predictions of the market-based price probability at horizon T should match forecasts of statistical moments of the trade values and volumes at the same horizon T. The market-based price probability emphasizes direct dependence on random properties of market trades.