Most managers use some type of value criteria dividend discount model rankings, low price/earnings ratios, low price/book values and the like when selecting stocks. But the returns to value investing depend greatly on how the method is applied. For example, the investment results of a strategy that picks the "top" stocks according to a pure value model, with no adjustments to control for systematic risk factors, were out of control during the 1987-90 period. The most undervalued stocks did not perform as well as the most overvalued stocks.

Fortunately, various methods of risk control can be easily incorporated into value strategies. An Arbitrage Pricing Theory approach called the Risk Attribute Model (RAM), for example, controls a portfolio's exposures to such risk factors as economic growth, credit cycles, long term interest rates, short term interest rates, inflation, U.S. dollar changes and the overall market effect. The proper use of RAM in an optimized portfolio process provides much higher returns, at lower risk, than simply picking the most undervalued stocks.

Value, like other stock ranking techniques, should be applied with discipline. Value works better when employed with optimized risk factors than without. Moreover, actively tilting a portfolio's exposure to various macroeconomic factors, in accordance with the manager's expectations of their behavior, can add even more value.