In this study, we test an investor's market behavior using probability functions. Furthermore, by establishing a consistent mean-variance model based on compound independent axioms with a unique certainty equivalency C = u −1 (E(u(X)], we present an alternate strategy to solve cooperative investment in a dynamic manner for mean-variance utility function. As a result, an explicit formula based on the exponential utility function over the normal distribution is established to approximate the certainty equivalent for each investor corresponding to the mean-variance utility function. Furthermore, we dene how alternative decision-making theories, like prospect theory, can be applied to solve cooperative investment schemes by taking investors' preferences into account as a function of choice, and we make the assumption that weight does not always have to coincide with probability. Therefore, Prospect Theory (PT) argues that decision weights have a tendency to underweight moderate and high probabilities and overweight small ones. Furthermore, the Prospect Theory Approach can be used to make investors' perceptions of risk consistent with logical decision-making through the use of suitable modeling. Additionally, a numerical experiment using S&P100 data is displayed.