"TECHNOBABBLE" EXPLAINED

When was the last time you really understood what a computer programmer was saying? Computer programmers, like others involved in highly complex and specialized fields, tend to speak in what I call "technobabble." Their conversations are so laden with jargon that they might as well be speaking a foreign language. Investment professionals, unfortunately, are often guilty of using technobabble. Three terms that are often carelessly tossed around in conversations about money managers are "alpha," "beta" and "R-squared." These statistics, if properly understood, can provide a great deal of insight into a manager's performance.

Alpha, beta, and R-squared provide information regarding the performance of a portfolio relative to the performance of another portfolio or the market itself. The first step in comparing a portfolio to, say the market, is to plot the performance of both on a graph. The R-squared statistic measures how closely the portfolio and the market follow one another. In other words, if you graphed the performance of the portfolio and the market and placed the graphs on top of each other, would the graphs be substantially the same or substantially different. R-squared is expressed as a number between 0 and 100. The lower the R-squared, the lower the relationship between the performance of the portfolio and the performance of the market. The higher the R-square statistic, the higher the relationship between the two. An R-square of 100 means that the portfolio's performance exactly tracked the market. R-square is important because of its relationship to the alpha and beta statistics. An R-square over 90 indicates that some significance can be placed on the alpha and beta statistics. R-squares less than 90 mean that the alpha and beta statistics are meaningless.

The alpha statistic is the measure of the money manager's skill (or lack of skill). It is defined as the expected return of the portfolio if the market return is zero. A positive alpha statistic is a good sign, since the manager is expected to have a positive return if the market is flat. A negative alpha is a bad sign, because the money manager may actually be hurting portfolio performance through his/her efforts.

Beta is a measure of relative risk. A beta statistic of 1.0 means that the portfolio has just as much risk as the market. A beta of greater than 1.0 indicates that the portfolio has more risk than the market. A beta of less than one means that the portfolio is less risky than the market. For example, if the portfolio's beta is 1.2 and the market goes up 10%, the portfolio should go up 12%. If the market is down 10% the same portfolio should be down 12%.

These statistics can be used together to estimate future performance. Assume a manager's R-square statistic is 96, his alpha is 1.2, and his beta is .90. Given an expected market return of 10% over the next year, the manager's return is estimated to be 10.2%. This is calculated as follows: Expected return = alpha + (beta * market return). In this case the calculation equals 1.2% + (.90 * 10%) or 10.2%. No single statistic should be the determining factor in hiring any manager. However, understanding alpha, beta, and R-squared can add to your understanding of a money manager's performance.