Although investors like to talk about carefully building portfolios, most still distinguish among investments based on the returns they expect them to generate. The recent market meltdown, however, has changed the equation somewhat, bringing risk to the forefront. Thoroughly chagrined, investors are once again looking both ways before they cross the road.

Of course, it all depends on what risk actually means to clients. Are they more concerned with the possibility of losing a portion of their hard-earned savings? Or is it the uncertainty of achieving the target rate of return that bothers them?

A number of measures have been devised that attempt to assess the merits of money managers by quantifying their risk-adjusted performance.

The Sharpe ratio, for instance, quantifies a fund’s return in excess of a guaranteed investment relative to its standard deviation. Simply put, the higher the Sharpe ratio, the better the fund’s returns have been relative to the amount of risk shouldered.

Unfortunately, because this measure uses standard deviation as a key determinant, many analysts worry that it doesn’t sufficiently differentiate between funds that swing wildly but still make money and those that are just more consistent in the manner in which they lose money.

Focusing on downside risk — the probability and extent to which an investment’s price may decline — provides more insight, the analysts argue. Because stocks that are more likely to decline when the market return is below its mean are inherently less attractive, the average return on these stocks must be higher to warrant the additional risk.

In a recent paper entitled Sorting Out Downside Beta, professors Thierry Post, Pim Van Vliet and Simon Lansdorp of Rotterdam’s Erasmus University attempt to determine whether looking more closely at downside risk, rather than the overall market risk, might better explain the variation in future returns among stocks.

They measure beta, the tendency of a stock’s returns to respond to swings in the market, and its downside counterpart, based on five years of historical stock and market returns.

Using return data for a broad sample of U.S. stocks spanning 1926-2007 and various measures of downside beta, the researchers conclude that sorting stocks by downside risk better explains the differences in future returns of these stocks than differentiating through regular market risk.

They find that stocks that are highly correlated with the market when it declines have higher expected returns than stocks that are not well matched with the market during its slides.

Over the period, a value-weighted portfolio, rebalanced annually, invested in the tenth of stocks with the highest beta generated an average annual return of 3.7% before trading costs.

However, a similar portfolio that concentrated on the tenth of stocks with the highest downside beta produced an average annual return of 5.5% before transaction costs, they report.

Downside beta outperforms overall beta in explaining future returns of individual stocks in four sub-periods, the researchers say, although the results vary considerably. And it is this inconsistency that leads them to temporize when making their observations.

Although downside beta seems to work better than beta in explaining differences in future returns among individual stocks, their conclusion leans rather heavily on the high average return for stocks with the highest tenth of downside beta. Conclusions based on other deciles are often different, they note.

One of the challenges of using downside risk measures in portfolio diagnosis is in their computational complexity, points out Brian J. Jacobsen, a professor at Wisconsin Lutheran College, in his paper The Use of Downside Risk Measures in Tax-Efficient Portfolio Construction and Evaluation.

His concern is whether downside risk measures offer enough benefits to offset their implementation and transaction costs, particularly among high net-worth investors who are concerned about tax efficiency. IE