Stock-Price Beta Estimation for Google, Inc. (Case Study)
This case study examines stock-price beta as a risk indicator, using Google (GOOG) to discuss estimation methods and the factors that can affect beta estimates.
Case Study Questions
A. Describe some of the attributes of an ideal risk indicator for stock market investors.
B. On the Internet, go to Yahoo! Finance (or MSN Money) and download weekly price information over the past year (52 observations) for GOOG and the Nasdaq market. Then enter this information into a spreadsheet like Table 16.6 and use these data to estimate GOOG’s beta. Describe any similarities or dissimilarities between your estimation results and the results depicted in Figure 16.8.
C. Estimates of stock-price beta are known to vary according to the time frame analyzed; the length of the daily, weekly, monthly, or annual return period; the choice of market index; the bull or bear market environment; and other nonmarket risk factors. Explain how such influences can undermine the usefulness of beta as a risk indicator. Suggest practical solutions.
Case Study Solution
A. Attributes of an Ideal Risk Indicator
An ideal measure of stock market risk would be simple to derive, accurate, and consistent from one year to another. With an ideal risk measure, investors would be able to control the risk exposure they face during volatile markets through well-targeted and well-timed investment buy/sell decisions.
For example, suppose an elderly investor wants to maintain exposure to the equity markets during retirement but wants to limit risk to reduce the possibility of devastating losses. With an ideal risk measure, retired investors could precisely tilt their portfolio allocations toward securities with low risk characteristics. Alternatively, if an investor anticipated a surge in stock prices following a decline in interest rates, precise risk measures could help that investor tilt an investment portfolio toward more volatile stocks.
The usefulness of stock market risk indicators diminishes to the extent that they fail to provide accurate and consistent measures of risk exposure from one year to another. In fact, an important limitation of risk estimators derived from the capital asset pricing model (CAPM) is that they vary from one period to another in ways that prove highly unpredictable. When betas vary from one year to another in ways that are essentially random and unpredictable, they fail to provide investors with a risk assessment tool that can be used to manage portfolio risk effectively.
B. Estimating GOOG’s Stock-Price Beta
It can be a real eye-opener for students to estimate stock-price beta for GOOG over a more recent time period using weekly returns and compare those results with the beta estimate derived from the monthly returns reported in Table 16.6 for the 52-week period shown in Figure 16.8.
Stock-price beta estimates often vary markedly depending on the time frame analyzed and the daily, weekly, monthly, or annual return interval examined. Such differences, if severe, can undermine the credibility of stock-price betas as useful risk indicators.
C. Limitations of Beta and Practical Solutions
Empirical estimates of stock-price beta are known to vary according to the time frame analyzed; the length of the daily, weekly, monthly, or annual return period; the choice of market index; the bull or bear market environment; and other nonmarket risk factors.
For example, estimates of beta tend to be imperfect risk measures because return volatility for the overall market is very difficult to measure. On the nightly news, when commentators talk about the market being up or down, they often refer to moves in the Dow Jones Industrial Average (DJIA). Whereas the DJIA offers good insight into changes in the prices of large blue chip companies, it offers little insight into volatility in the returns earned by investors in smaller high-tech stocks.
From the perspective of many individual and institutional investors, the S&P 500 Index gives superior insight into moves in the overall market. Like the DJIA, however, the S&P 500 is dominated by large blue chip companies. Although the Nasdaq and Russell 2000 indexes are popular measures of high-tech and smaller stocks, they are much less informative about changes in the overall market. While there is a high degree of correlation among the rates of return earned on the DJIA, S&P 500, Nasdaq, and Russell 2000 indexes, slight differences can have big effects on beta estimates.
From a theoretical perspective, the most appropriate benchmark would be a market index that included all capital assets, including stocks, bonds, real estate, collectibles, and so on. Unfortunately, no such market index is available. To a greater or lesser degree, this affects the accuracy of all beta estimates and undermines confidence in beta as an accurate measure of security risk.
Another important problem in obtaining consistent and reliable beta estimates is their sensitivity to the length of time over which stock return data are measured. When beta estimates differ according to daily, weekly, monthly, or annual returns, the usefulness of stock-price beta as a consistent measure of risk is greatly diminished.
The presence of market index bias and return interval bias, among other problems, makes it imperative that beta comparisons among individual companies use identical estimation periods, return intervals, and appropriate market benchmarks.