Abstract: A system and method directed to improving efforts to plan for investor life goals. The method combines unique approaches of assessing investor risk tolerance using utility theory and investor preferences using conjoint analysis, Analytic Hierarchy Process (“AHP”), or the like in combination with existing industry financial projection methods using linear projections, Monte Carlo simulation, or the like. Further, the method improves upon existing financial projection approaches with the addition of regression techniques to streamline adjustments to the plan objectives, resources, and constraints. The method includes a means of determining an optimal combination of attribute preferences that have an acceptable probability of achieving plan goals while maximizing investor satisfaction as measured by total utility.

Abstract: A system and method directed to improving efforts to plan for investor life goals. The method combines unique approaches of assessing investor risk tolerance using utility theory and investor preferences using conjoint analysis, Analytic Hierarchy Process (“AHP”), or the like in combination with existing industry financial projection methods using linear projections, Monte Carlo simulation, or the like. Further, the method improves upon existing financial projection approaches with the addition of regression techniques to streamline adjustments to the plan objectives, resources, and constraints. The method includes a means of determining an optimal combination of attribute preferences that have an acceptable probability of achieving plan goals while maximizing investor satisfaction as measured by total utility.

Abstract: A system and method directed to improving efforts to plan for investor life goals. The method combines unique approaches of assessing investor risk tolerance using utility theory and investor preferences using conjoint analysis, Analytic Hierarchy Process (“AHP”), or the like in combination with existing industry financial projection methods using linear projections, Monte Carlo simulation, or the like. Further, the method improves upon existing financial projection approaches with the addition of regression techniques to streamline adjustments to the plan objectives, resources, and constraints. The method includes a means of determining an optimal combination of attribute preferences that have an acceptable probability of achieving plan goals while maximizing investor satisfaction as measured by total utility.