The FINSIM model provides a fundamental and analytical basis for security evaluation. The methodology presented includes the relevant economic and firm variables in an efficient computational scheme and is useful for:1. reducing the analysts' judgments about the future to a specific stock price (the model described does not replace the analyst, rather it provides the analyst with a vehicle to determine the implications of his critical assumptions);2. testing the probable impact of changed expectations concerning the firm and/or the level of the market on stock value;3. getting at what “the markets” expectations must be to justify the current price;4. determining the value of additional information (are results changed significantly to pay for the expense of refined estimates?);5. determining the impact of alternative growth horizons on value; and6. determining what the actual growth rate of total earnings must be to overcome the dilution effects of financing with external equity.While the security analyst still faces the problems associated with decision making under uncertainty, the methodology presented facilitates the use of sensitivity analysis to study the implications of uncertain knowledge of parameters.

William W. Hogan, James M. Warren, Toward the Development of an Equilibrium Capital-Market Model Based on Semivariance, The Journal of Financial and Quantitative Analysis, Vol. 9, No. 1 (Jan., 1974), pp. 1-11

Portfolio selection models based on expected value-semivariance (E-S) criteria have been suggested as offering certain advantages over the expected value-variance (E-V) approach. Although variance is more tractable mathematically, it has not always been satisfying to financial theorists ([3, pp. 278–284], [5], [6], [7, pp. 193–194], and [10, pp. 72–73]). In the pioneering work in portfolio analysis, Markowitz [7, p. 194] observed that semivariance concentrates on reducing losses as opposed to variance which considers extreme gains, as well as extreme losses, as undesirable. In the presence of nonsymmetrical probability distributions, this equal weighting of gains and losses may not adequately describe the alternative portfolios available to the decision maker.