Analysts have, or can easily get, estimates of a company’s future financial performance. What they need and do not have are valid forecasts of expected return. The T-Model provides a conceptual framework for turning readily available financial results into return forecasts.

The T-Model states investment return in three terms—growth, cash-flow yield and valuation change—each of which depends on familiar accounting results—return on equity, growth and change in price/book ratio. When these data are known exactly (i.e., with hindsight), the T-Model explains over 90 per cent of the return on individual stocks or portfolios.

Of course, return forecasts require forecasts of the T-Model components. Forecasting ROE is equivalent to forecasting earnings—something the analyst does anyway. Growth requires an estimate of the increase in shareholders’ equity over the holding period, which will depend in part on the company’s reinvestment rate. Valuation change is probably the most difficult variable to forecast and, in the short run, it is the most volatile and also the most dominant in terms of its effects on return. In the long run, however, its contribution to return should be less than that of either of the other two variables, and its value should approach some “average” for the company or industry.

With such forecasts, the T-Model allows the user to compare total return forecasts for various companies and to analyze their sensitivity to changes in the estimates. Forecasts of expected return made by the model with completely naive input data show very successful stock-selection capability.