by Reinhold P. Lamb
Reinhold Lamb is the Jody & Layton Smith Distinguished Professor of Finance at the University of North Florida. He is the director of Osprey Financial Group, a special program that enables a select group of students to manage of portion of the endowment. His research specializes in how the markets interpret and value new information.
- Beta can be a misunderstood measure of risk, especially since there exists a wide range of beta values on various websites, like Yahoo!Finance, in published sources, like Value Line Investment Survey, and from news services, like Thomson Reuters and Standard & Poor's.
- For financial planners and advisers with clients of varying sophistication, the inconsistency in reported beta values can produce confusion for the client when trying to validate that the account is being managed properly in terms of accepted levels of risk.
- A scenario is presented whereby a client becomes disgruntled with a new financial planner because it appears that the risk exhibited in one of the securities selected by the planner is in violation of the risk the client is comfortable with.
- A solution is offered that permits the planner to educate the client about the interpretation of beta values, misunderstandings about published betas, and portfolio risk using the very example on which the client's concerns are based.
- A sensitive confrontation has been turned into an educational moment that can strengthen the confidence the client has in the new relationship.
While research questions the usefulness of a stock's beta, its widespread availability implies continued use. Whether in an investment portfolio context or in a capital budgeting scenario, beta and its inputs must be clearly understood in order to properly integrate risk into decision-making. What follows is the solution to a scenario between financial planner and disgruntled client to provide an understanding that beta is more than a simple number. In fact, beta will be misunderstood or incorrectly interpreted if that number is not decomposed to expose the nuts and bolts of the calculation. What follows demonstrates that the only way to understand and interpret the beta value is to understand how that value was calculated.
Risk Establishment With the Client
You are a financial planner who has been hired by a client to design a portfolio or distribute the assets in a way that reflects the risk the client is willing to bear. The client is willing to bear some risk but is not a bungee jumper when it comes to investing money. The acceptable level of risk is around the middle of the scale; that is, the client is comfortable with average risk but becomes very uncomfortable quickly as risk rises above average. The client is quite resolute that above-average risk is outside the comfort zone and that average risk or slightly below-average risk is the only acceptable level. You indicate that the client has been very clear on how much risk is acceptable and that you understand how to construct and manage the portfolio given the risk parameters.
Confrontation With Client About the Risk in the Portfolio
After the first quarter (or year) of management, you prepare a performance report for the client. Each of the positions comprising the account is presented with the corresponding performance. The overall performance is also presented. The client is savvy enough to scrutinize the report, especially since it is the first one from you-the new financial planner. In the process, the client utilizes mainstream websites to judge the composition of the portfolio and the performance of the manager.
Yahoo!Finance shows several statistics for each ticker symbol entered and some of them are unfamiliar to the client. The client sees beta on a webpage, searches for information about what it means, and learns that it is a measure of risk whereby a value of 1.0 represents average risk. Values greater (less) than one indicate greater (less) than average risk. After noting the betas for each of the companies (exchange traded funds, mutual funds) in the account, the client is surprised to learn that several of the positions have a beta substantially exceeding 1, indicating a level of risk above that expressed to you.
For example, Yahoo!Finance shows the beta for eBay (EBAY), one of the holdings, is 1.56. The outraged client calls you for an immediate meeting to resolve the trouble. At the meeting, the client presents a copy of the webpage with the EBAY beta and date circled and asks for an explanation for why the desired risk level was not respected. Exhibit 1 is the page of evidence.
Exhibit 1: eBAY (EBAY) Key Statistics from Yahoo!Finance, February 1, 2011
The question to you is how to respond now? What do you tell the client? The client clearly articulated that the acceptable level of risk is average to slightly below average, yet the client has produced evidence that at least one of the positions in the portfolio is in violation of the established risk parameters. As this relationship is still young, the client may begin to develop doubts or suspicions about you as planner following instructions and managing the account as desired. Your credibility and competence is being question and, since the client is visibly upset, a continuation of the relationship may be dependent on how you respond to this confrontation.
This scenario requires tact and patience. It also requires you to educate the client about risk and beta in order to preserve the relationship and the account. What follows is a series of responses that should convince the client that you do, indeed, understand the risk preferences of the client and customizing a personalized account, that you are knowledgeable about portfolio management, and that you are an excellent communicator of complex information. Credibility should be restored.
Betas are not consistent. You look at the Yahoo!Finance printout of the EBAY beta (1.56) and then begin to explain that beta is a mathematical calculation that uses the returns of the company and the returns on some market index, like the S&P 500 Index. The beta value is the slope of the regression line between those two inputs and that the client is correct in interpreting the Yahoo beta for EBAY as riskier than average and, consequently, seemingly in violation of the risk communicated.
However, you should then proceed in describing how the beta value is sensitive to the inputs in that regression calculation and that the details of those inputs are subjectively determined by whoever is making the calculation. The subjective inputs involve (a) index choice, (b) calendar period of interest (number of years), and (c) return time frame (daily, weekly, monthly). Since there are many choices within each input, beta values for the same company can be very different. Yahoo!Finance describes that their beta is calculated using the S&P 500 Index and three years of monthly data. That is from what the EBAY beta is calculated, and it is mathematically correct. The slope of the regression line using those inputs is 1.56, indicating greater than average risk.
You can then open your notebook computer to a Thomson Reuters stock report (via E*Trade or many other online brokerage firms that subscribe to Thomson Reuters research). The most recent report on EBAY, dated within the same week as the Yahoo!Finance page from the client, shows a beta value of 1.02, indicating risk is about average and consistent with the desires of the client.
Exhibit 2: eBAY (EBAY) Stock Report from Thomson Reuters, January 28, 2011
Source: Thomson Reuters, 2011
Exhibit 2 presents the Thomson Reuters page. How can this be? One service reports beta risk higher than average at 1.56 while another service reports it at 1.02? And if they are both correct because they both involve a mathematical operation, what good is beta if it can vary so much?
The answer to that question is that the only way to properly interpret beta and integrate it into decision-making is to understand how it is calculated through the collection of subjective inputs. Otherwise, the application of the beta value for framing future expectations must be done with great caution at best. The Thomson Reuters beta of 1.02 was calculated using the S&P 500 Index and daily returns over 12 months. You could further refer the client to research that reports the instability of beta across other popular websites and publications (Reilly and Wright, 1988), (Lamb and Northington, 2001), Agrrawal and Waggle, 2010).
Furthermore, you could present evidence of beta inconsistency by producing the Standard & Poor's stock report for EBAY dated the same week as the other two sources. Exhibit 3 shows an even higher beta of 2.12, indicating more than double average risk.
Exhibit 3: eBAY (EBAY) Stock Report from Standard & Poor's, January 29, 2011
Source: The McGraw Hill Companies, Inc., 2011
Interpretation: All three beta values are correct in a mathematical sense over the history of behavior for EBAY given the inputs. However, you believe the Thomson Reuters beta value of 1.02 is a better measure of the risk of EBAY because it spans a period that you believe to be more reflective of the future. The Yahoo!Finance and Standard & Poor's betas are much higher because they include a period that was very volatile. The financial crisis of 2009 is included in that beta calculation and it distorts the risk value by overstating it going forward, unless it is believed that the economy (and EBAY) will experience another 2008-2009 behavior in the near future.
Because the application of beta is to predict future risk based on a historical risk calculation, it is important to select a historical period that represents the belief of how the stock will perform going forward. If you believe the recent past includes a period that the stock will likely not experience in the future, then including that period in a forward-looking application can be misleading.
You conclude by stating that although all three beta calculations are correct, the one-year beta from Thomson Reuters is more reflective of the risk expectation of EBAY going forward and, therefore, is the more appropriate one to integrate into the client's portfolio because the portfolio is going forward. The lesson learned by the client in this presentation is that betas are not consistent and one must understand from where the inputs come from in the calculation to apply the beta properly in decision-making like portfolio construction.
Betas are not stable. A stable beta implies that the systematic risk of a firm does not change; that the relationship between the stock and the market is continuous. A company (fund) is a like a living entity that changes through time, bringing in managers with a higher(lower) risk appetite, developing new products, expanding into new markets, and being exposed to new regulations and new competition. Consequently, the firm is not static and should not be expected to behave and perform at a constant measureable level.
For example, the beta for AT&T (T) reported on smartmoney.com on November 11, 2008 was 1.17. The same website with the same inputs reported about three years later, on February 2, 2011 a T beta of 0.66. The same company (T), the same website and index and return time frame parameters produced two very different values for risk when the calendar period changed. Such evidence of instability in beta values should produce caution in the client in putting too much weight into identifying and applying any beta value without the knowledge of the period over which it represents.
Exhibit 4: AT&T (T) Snapshot on SmartMoney.com, November 11, 2008
Exhibit 5: AT&T (T) Snapshot on SmartMoney.com, February 2, 2011
After the consistency and stability of beta are described to the client, it would then be good to reinforce that it is a portfolio being managed, not a collection of individual securities. In managing risk, a portfolio provides benefits of diversification through the interaction of individual securities. Each pair of securities is correlated to some degree, and an active and engaged manager constructs the portfolio to satisfy the risk and expectation of the client. That is what you have done for the client. In a way, it is the portfolio as a whole that represents the risk to the client, not the individual risks manifested in the lineup of individual securities comprising the portfolio. It would be naïve for a client to select one security, identify the risk of that security, and jump to the conclusion that it represents the risk of the entire portfolio.
You would emphasize that although EBAY, with a Yahoo!Finance beta of 1.56, may be riskier than the average security given the respective inputs, the risk of the portfolio is the weighted average of the risks of all the individual securities. Perhaps the weight of EBAY is low and so the impact of a 1.56 beta is small. Perhaps most of the other securities have betas in the 0.7-0.9 range and easily counterbalance EBAY and any other securities with betas greater than 1.0. When considering the portfolio as a whole, the risk is indeed lower than average and is within the spirit of what the client desired, despite at least one of the securities exhibiting higher than average risk.
A frustrated client confronts a new financial planner questioning competence and credibility in the mismanagement of the risk adverse portfolio by investing in a security with a beta greater than 1.0. Such questioning is realistic and could jeopardize the relationship between client and planner. The root of the trouble is an insufficient understanding of how beta is calculated and what it represents on both an individual scale and within the context of a portfolio. At the same time, it provides an opportunity for the planner to regain trust by educating the client that the only way to properly interpret beta is to understand how it is calculated. Financial professionals are called upon to understand how risk is calculated and to thoughtfully select a beta that reflects the inputs they believe are most relevant for the client going forward. Consequently, a potentially uncomfortable misunderstanding can be diffused and turned into a positive outcome if the planner will take the time to educate the client.
Agrrawal, Pankaj and Doug Waggle, 2010, "The Dispersion of Betas on Financial Websites," Journal of Investing, 19(1), 12-24.
Lamb, Reinhold and Kathryn Northington, 2001, "The Root of Reported Betas," Journal of Investing, 10(3), 50-53.
Reilly, Frank K. and David J. Wright, 1988, "A Comparison of Published Betas," Journal of Portfolio Management, 14, 64-69.