Illuminating some market jargon

January 30, 2015

When was the last time you really understood what a computer programmer said? Computer programmers, like others involved in highly complex and specialized fields, tend to speak in what can be called “techno babble.” Their conversations are so laden with the jargon of the trade that they might as well be speaking a foreign language.

Investment professionals, unfortunately, are also often guilty of using techno babble. Three terms that are often tossed about in conversations regarding money managers are: “alpha,” “beta” and “R-squared.” However, a good understanding of these statistics can provide some useful insight into a manager’s performance; therefore, they are worth learning about.

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-squared statistic, the higher the relationship between the two. An R-squared of 100 means that the portfolio’s performance exactly tracked the market. R-squared is important because of its relationship to the alpha and beta statistics.

An R-squared over 90 indicates that some significance can be placed on the alpha and beta statistics. If an R-squared is less than 90, it means that the alpha and beta statistics are meaningless. When an R-squared is low, a comparison to the market (for example the Standard & Poor’s 500) is not meaningful; therefore, a comparison to a different investment category index should be considered.

The alpha statistic is the measure of the money manager’s skill (or lack of skill) over and above the market itself. 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 the same amount of 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 1.0 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%. Conversely, 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-squared 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.

The opinions voiced in this material are for general information only and are not intended to provide specific advice or recommendations for the individual. Randy Neumann is a financial professional with and securities offered through LPL Financial, member FINRA/SIPC.