Beta: The Alpha and Omega to Risk Analysis?

Beta.

When people use this word, they might mean "second," as opposed to "first." Or they could be referring to a particle in physics, a protein conformation in biology, or a test in computer programming. But when investors use it, they mean "risk."

Technically, according to sources such as the Fool glossary or Investor Words, beta is the measure of a security's volatility compared with the volatility of the stock market as a whole, often measured by the S&P 500 index. It comes from the capital asset pricing model. In a sense, it indicates how much broad market moves affect a stock's price.

A beta greater than 1 means the security is more volatile than the overall market, while a value less than 1 means the security is less volatile. Some stocks, such as Boeing (NYSE: BA  ) , have a beta near 1, which means they track the movement of the overall stock market fairly closely. Boeing's current beta is 0.91. Other stocks, such as Altria Group (NYSE: MO  ) , have a beta less than 1 -- 0.50 in this case -- and thus have less volatility than the overall stock market. Still others, such as JDS Uniphase (Nasdaq: JDSU  ) , have a large beta -- 3.22 for this company -- and have wilder price swings than the overall stock market. Cash has a beta of 0, since it's always worth the same (excluding inflation effects), regardless of how the stock market moves.

How is beta calculated?
Well, for those who really want to get into it, there are several descriptions available, including this one. Suffice it to say that it's a statistical calculation of how a company's stock price returns vary when compared with an index's returns.

For us more visual learners, a simpler way to calculate beta is the following.

  • First, determine the price fluctuations for the index over some time period -- for instance, the end of each week for the past five years.
  • Second, determine the price fluctuations for the stock over the same period.
  • Third, make a graph with the index's fluctuations on the X-axis and the stock's fluctuations on the Y-axis. For instance, on Oct. 28, 2005, the S&P 500 had moved up by 1.6% from Oct. 21 -- from 1179.59 to 1198.41. Boeing's price moved down by 0.58% between those two weeks -- from $66.02 to $65.64. This would correspond to a point of (+1.60, - 0.58) on the graph.
  • Repeat this procedure for the entire range of dates. (Hint: Use a spreadsheet to do all this.)
  • Finally, fit a straight line to the plot and look at the slope. That is the beta. For an example of this using five years for Boeing, look here, where beta was calculated to be +1.20.

The easiest way to "calculate" it, though, is to let someone else do it. Many summary financial websites list beta as one of the company's key statistics. The values given earlier are from MSN Money's website.

What does it all mean?
As mentioned above, beta is a measure of how volatile a stock's price is compared with the overall market. If the market rises 10%, then one could expect JDS Uniphase's price to rise by 32% (3.22 times 10%). On the other hand, Altria could be expected to rise only 5%.

This is also the case for downward movements. If the market drops by 5%, then these two companies could be expected to drop by 16% and 2.5%, respectively. In the capital asset pricing model, beta is a measure of the company's market risk. That is, it measures how the company's price will probably react if the market goes up or down by some percentage.

What are some shortcomings to the calculation?
First, the value one gets from any of the above calculation methods is heavily dependent upon several considerations. These include how long a timeframe is used (one year, three years, etc.), how often the prices are compared (weekly, monthly, etc.), and even when within the period the calculation begins (e.g., end of the month versus middle of the month). For example, if I calculate JDS Uniphase's beta using closing weekly prices vs. the S&P 500 index over the past five years, I get 2.51. If instead I calculate it over the past three years, I get 2.18.

This also explains the difference astute readers may have noticed between my beta calculation for Boeing of 1.20 and the 0.91 beta number for Boeing I mention at the beginning of the article. MSN Money's data provider for the 0.91 figure uses end-of-month data for the past five years, whereas my example used end-of-week data. Timeframe really matters.

Second, companies change over time, and, therefore, the beta does as well. Take Boeing, for example. Is it the same company it was five years ago? If not, then one shouldn't use a beta based on five years of prices. Further, as companies become larger and more diversified, their beta tends to get closer to 1.

When Boeing first started out in Seattle, it built only airplanes (although for a time, it also built furniture). Over time, it expanded and started to manufacture joint direct attack munitions and harpoon missiles, sold computer services, built interplanetary probes, and even managed housing projects and built desalinization plants. Obviously, it has become more diversified. In 1971, its beta was 1.81. Today, its beta is 0.91.

Third, choice of index for comparison is important. Should one use the S&P 500, the Russell 2000, the Wilshire 5000, or the NYSE Composite? What if the company is foreign? Ideally, one should use as broad an index as possible -- one that is reflective of the investor making the analysis about the company. Most information sources calculate a stock's beta based on the S&P 500, which is a large-cap index. If an investor's portfolio is small cap in nature, however, a beta based on the Russell 2000 index would be more useful.

Finally, there's the R-squared, which ties into index choice. R-squared is a measure of how close all the data points are to the line itself. One can always fit a straight line to scattered data points. But the line is more meaningful -- and thus, the beta is, too -- if the data points tend to cluster around the line rather than being all over the place. An R-squared of 1 (or 100%) means all the points are exactly on the line. An R-squared of 0 means that the points are totally random and there is no correlation. One will get a very poor R-squared if one uses a non-relevant index. For instance, the price of gold has a very poor correlation to the S&P 500 index and, thus, a very low R-squared -- the average R-squared for gold index funds versus the S&P 500 is about 0.03. In such a circumstance of extremely low R-squared, beta loses all usefulness in predicting price movement.

People familiar with modern portfolio theory (MPT) will point out here that a high R-squared is important. For MPT, that is true. A fund with an R-squared of 0.90, for instance, is said to have 90% of its price volatility occur due to the market and, therefore, is a well-designed fund for tracking that particular index.

We aren't discussing MPT, though. For individual companies, the R-squared value can vary wildly and does not have to be greater than the accepted 0.75 that MPT defines as being the threshold number for a useful beta number. Individual companies do not, generally, track very closely with the market as a whole, unless they are very big and very diversified. Thus, an R-squared value of 0.34, as in the above calculation of Boeing's beta, is perfectly valid. Nevertheless, it's true that an extremely low R-squared value should indicate a lack of faith in the calculated beta, maybe because of poor index choice.

Are there other types of risk besides beta?
For many people, a wildly swinging stock price (e.g., JDS Uniphase) is perceived to be more risky than one that plods along (Altria). This perception has led many investors to equate beta with overall risk. So people who don't want a lot of exposure to risk choose lower-beta stocks as their investments of choice.

In reality, however, there are other kinds of risk -- not just those associated with the overall market. Think of company-specific risk. Take the popular restaurant chain Cheesecake Factory (Nasdaq: CAKE  ) , with its beta of 0.70. Less variable than the market seems all right, doesn't it? But if that is the only consideration of risk you make, then you're ignoring the possibilities that the popularity of this chain will wane or that the company will saturate its locations and lose profitability. Is The Cheesecake Factory still a popular restaurant? Can the company open multiple locations in the same city without cannibalizing other locations? The answers are not found by looking at the beta.

How do you take into account these other risks? As a previous article pointed out, the answer is "information." By digging into a company's annual and quarterly reports, by looking at other companies in the same industry, and by reading press releases and news articles about the company, you can amass a wealth of knowledge that will give you a sound basis for assigning different levels of probability to different scenarios.

Note that in a diversified portfolio, company-specific risk is muted since factors that affect one company specifically would not likely affect another one. Thus, the best way to guard against company-specific risk is to diversify one's portfolio across many stocks in different industries.

In addition, a stock's correlation with the overall stock market is not the only measure of correlation an investor needs to know about. One can also mute overall wild swings in a portfolio by choosing equities that are not highly correlated with each other.

Most investors should probably have a portion of their portfolio in conservative companies with lower betas -- that is, stocks with a low-price volatility. But beta shouldn't be your only look into the risk of investing in each company. Take advantage of the information out there, whether it be here at The Motley Fool or at other sites such as Yahoo! Finance, MSN Money, or the company's own website. Armed with this knowledge and a healthy appreciation of the other risks present at a company, one can make intelligent investment choices and move even further away from the image that investing is no more than gambling.

Related statistical Foolishness:

Fool contributor Jim Mueller doesn't really use beta in his own investing decisions, but he does look at company- and industry-specific risks. Besides, he likes to learn about different aspects of investing. He does not own shares in any company mentioned here. Check out the Fool's fascinating disclosure policy!


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