The traditional thinking in the world of finance is that to increase returns you need to increase risk. This view is quite logical. Let’s consider an investor who wants a minimum of risk. She can buy certain blue-chip stocks such as Wal-Mart, Home Depot [[hd]] , and GE [[ge]]. The stocks offer low risk because they are all giant companies with dominant market positions; I think it is a fair bet that all three companies will still be around in one form or another 50 or 100 years from now. For such low risk our investor will get a relatively low return because these companies are so huge and have less ability to grow than they had in the past. Now, with such great blues chip stocks available why would our investor choose to buy shares in a company such as DayStar technology [[DSTI]] or Cheniere Energy [[LNG]]? Neither of these companies currently makes a profit nor has any significant revenue. In owning such companies an investor has significantly more risk of losing her capital. Therefore, no rational investor would buy the stock of such companies without being assured that those investments offer the potential of very great reward.
This thinking underlies the Capital Asset Pricing Model (CAPM). Now, for the most part this works quite well. However, there are some problems with the capital asset pricing model. One huge problem is that in this model risk is defined as the stock’s volatility. Volatility is of course a measure of how much a stock’s price changes each day, week, and year. For those of us who are long-term investors, however, volatility is an inadequate measure of risk. What matters more for us is the stability of the future earnings of a company.
For financial analysts and portfolio managers, volatility is most commonly measured by something they call beta. Simply put, beta is a measure of the correlation of the stock’s price to the broader stock market as a whole. Therefore, an index fund would have a beta of 1.0. Let’s say we have a stock that has a beta of 2.0; this means that in general, when the market goes up 10% the stock will go up 20%, conversely, when the market goes down 10% the stock will go down 20%.
Since we’re already talking about beta and financial analysts, I might as well mention alpha. Alpha is a measure of a portfolio’s performance. An alpha of zero indicates that a portfolio matched the market’s return. An alpha of one would indicate that a portfolio outperformed the market by 1% annually.
The goal of a professional portfolio manager, at least according to the capital asset pricing model, is to construct a portfolio with the desired amount of alpha in order to maximize returns without exceeding a certain level of risk (beta). According to the model, it is impossible to consistently beat the market because the market is efficient. This aspect of the model is known as the efficient market hypothesis and I obviously believe it to be wrong. I will deal with why this is wrong in a later article. For now let’s return to risk.
One finding that has been problematic both for the efficient market hypothesis and for beta is the finding that low P/B stocks outperform high P/B stocks. According to the CAPM, this could not happen without low P/B stocks being more risky than high P/B stocks. However, low P/B stocks do not have higher betas than high P/B stocks. The creator of the efficient market hypothesis himself, Eugene Fama, realized then that beta do not adequately measure risk. He and his collaborator Eric French argued that low P/B stocks are more risky than high P/B stocks. I disagree with this but the important point is that as of their paper in 1992 (unfortunately not available free online), beta was officially dead or at least dying.
So how can we measure risk? There are no easy ways to do so. We must rely on sound fundamental analysis. Risk obviously decreases the more products the company makes and the more customers to which it sells. Thus, GE and Berkshire Hathaway are less risky than almost all other companies because their revenue streams are so diverse. Conversely, ExpressJet [[xjt]] and the other regional airlines are very risky because they all have only one or two customers. Similarly, small defense contractors are risky if they sell only a few major products and to only one major customer: the United States government.
Another risk factor is debt. Companies with more debt are much less likely to be able to survive a recession or industry downturn because they would be unable to meet their debt obligations if their revenues drop more than slightly. For this reason, companies such as Fortune Brands [[fo]], Blockbuster [[bbi]], and Ford [[f]] have elevated risk due to high debt loads.
Another risk factor is obviously competition. Companies and highly competitive industries have greater risk than companies with monopolies or that for other reasons do not have much competition. There are many ways that a company can avoid too much competition, including patents, trade secrets, operating in a niche market, and effective branding. Ceteris paribus, a dollar of earnings that is at lower risk from competition is worth more than a dollar of earnings that comes from a highly competitive industry.
This is not to say that companies in highly competitive industries cannot be great investments. Those companies that are wildly successful in competitive industries usually have some key advantage that gives them an edge in that is not easily copied. This advantage is not always easy to identify. For example, Southwest Airlines [[luv]] had the important advantage over legacy carriers of not having an established business prior to airline deregulation. This meant that Southwest was not burdened with the same costs that hindered the larger airlines. In addition, Southwest’s fares were simple and did not penalize travelers for arbitrary reasons such as not staying over a weekend. Another good example of a successful company in a competitive industry is Wal-Mart [[wmt]]. What did Wal-Mart offer that Kmart [[shld]] and other discounters could not? One thing it offered was everyday low prices. By avoiding sales Wal-Mart gained both the reputation as the low-price leader and it gained more consistent profitability. Wal-Mart has also been known for some time for the effectiveness of its distribution system. In an industry with low profit margins and high inventory requirements, any improvement in logistics drops straight to the bottom line.
The last important risk factor is the elasticity of demand for a company’s products. The business cycle is a fact of life; any company that suffers less during recessions, whether because it sells products that are always in demand or because it sells to people who are not greatly affected by recessions, has lower risk than the average company. Big industrial companies such as auto manufacturers and aircraft manufacturers are usually very cyclical. Cyclicality of earnings is not in and of itself a black mark against a business. However, combined with high debt and stiff competition, a cyclical company in an industry downturn can be a very risky bet. See, for example, General Motors [[gm]] or Northwest Airlines [[nwa]].
While it is not possible to exactly quantify risk, it can still be approximated. Any decision to invest in a company should come only after carefully weighing the possibility for reward against the risk that company presents. In certain circumstances, adequate calculation of risk and reward cannot be made, such as with development stage companies with no revenues. In such cases, the conservative investor would do well to watch from the sidelines unless she is an expert in the field and is sure that she is not paying too much.
On a related note, I urge you to read Richard Russell’s article on the perfect business, which discusses the ideal business from the standpoint of a small-business owner. The points Russell brings up are also important to large publicly traded companies.
Disclosure: I have no position in any stock mentioned above. I have a full disclosure policy.