In the preceding expression we chose to solve for the value of the stock. This value could then be compared with actual price to see if the stock should be purchased. An alternative way to employ this model is to set the right-hand side of the preceding equation equal to actual price, but to leave the discount rate unspecified. The equation could then be solved for the discount rate implied by the analyst's expectation and the present price. This rate can be viewed as the analyst's estimate of expected return. The stock would be


Figure 18.1 Growth-rate pattern for a three-period model.

purchased or sold depending on the relationship between the analyst's estimate of expected return and what the firm considers a fair return for the stock given its risk.

As we move from a constant growth model to a two-period growth model to a three-period growth model, and perhaps even beyond this, we have increased the number and the complexity of the inputs the analyst must provide. If growth patterns are overly simplified, insufficient information will be provided by the forecasts. If they are made too complex, the forecasts are likely to be inaccurate. This trade-off is most apparent in the two extreme models discussed earlier. Analysts cannot develop year-by-year growth estimates into the indefinite future. At the other extreme, asking the analysts to provide only a single average growth forecast means losing the chance for the analyst to provide information about the future pattern of the company's growth. The trade-off between complexity and manageability will have to be made on the basis of the forecasting skills of an organization. No matter how this is decided, one of the principal benefits of using a valuation model can be the preparation of a comparable and explicit set of forecasts over time. Only if forecasts are made explicit can an organization evaluate and improve its performance over time.

Before leaving DCF models, it is worth noting another type of DCF model that is sometimes used by security analysts.

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