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Measuring Beta for Turbot-Charged Seafoods

Suppose we look back at the trading history of Turbot-Charged Seafoods and pick out 6 months when the return on the market portfolio was plus or minus 1 percent.

Look at Figure 4.7, where these observations are plotted. We`ve drawn a line through the average performance of Turbot when the market is up or down by 1 percent. The slope of this line is Turbot`s beta.You can see right away that the beta is .8, because on average Turbot stock gains or loses .8 percent when the market is up or down by 1 percent. Notice that a 2-percentage-point difference in the market return ( Ј1 to +1) generates on average a 1.6-percentage-point difference for Turbot shareholders ( Ј.8 to +.8). The ratio, 1.6/2 = .8, is beta.

In 4 months, Turbot`s returns lie above or below the line in Figure 4.7. The distance from the line shows the response of Turbot`s stock returns to news or events that affected

Turbot but did not affect the overall market. For example, in Month 2, investors in Turbot stock benefited from good macroeconomic news (the market was up 1 percent) and also from some favorable news specific to Turbot. The market rise gave a boost of .8 percent to Turbot stock (beta of .8 times the 1 percent market return). Then firm-specific news gave Turbot stockholders an extra 1 percent return, for a total return that month of 1.8 percent.

This figure is a plot of the data presented in the table from Example 1. Each point shows the performance of Turbot-Charged Seafoods stock when the overall market is either up or down by 1 percent. On average, Turbot- Charged moves in the same direction as the market, but not as far. Therefore, Turbot- Charged`s beta is less than 1.0. We can measure beta by the slope of a line fitted to the points in the figure. In this case it is .8.

As this example illustrates, we can break down common stock returns into two parts: the part explained by market returns and the firm`s beta, and the part due to news that is specific to the firm. Fluctuations in the first part reflect market risk; fluctuations in the second part reflect unique risk.

Of course diversification can get rid of the unique risks. That`s why wise investors, who don`t put all their eggs in one basket, will look to Turbot`s less-than-average beta and call its stock ¬defensive. ­

Real life doesn`t serve up numbers quite as convenient as those in our examples so far. However, the procedure for measuring real companies` betas is exactly the same:

1. Observe rates of return, usually monthly, for the stock and the market.

2. Plot the observations as in Figure 4.7.

3. Fit a line showing the average return to the stock at different market returns. Beta is the slope of the fitted line.

This may sound like a lot of work but in practice computers do it for you. Here are two real examples.

(a) Each point in this figure shows the returns on MCI common stock and the overall market in a particular month. Sixty months are plotted in all. MCI`s beta is the slope of the line fitted to these points. MCI has a relatively high beta of 1.3. (b) In this plot of 60 months`returns for Exxon and the overall market the slope of the fitted line is much less than MCI`s beta in (a). Exxon has a relatively low beta of .61

BETAS FOR MCI WORLDCOM AND EXXON

Each point in Figure 4.8a shows the return on MCI WorldCom stock and the return on the market index in a different month. For example, the circled point shows that in the month of May 1997 MCI stock price rose by 23 percent, whereas the market index rose by 5.9 percent. Notice that more often than not MCI outperformed the market when the index rose and underperformed the market when the index fell. Thus MCI was a relatively aggressive, high-beta stock.

We have drawn a line of best fit through the points in the figure.2 The slope of this line is 1.3. For each extra 1 percent rise in the market MCI stock price moved on average an extra 1.3 percent. For each extra 1 percent fall in the market, MCI stock price fell an extra 1.3 percent. Thus MCI`s beta was 1.3.

Of course, MCI`s stock returns are not perfectly related to market returns. The company was also subject to unique risk, which shows up in the scatter of points around the line. Sometimes MCI flew south while the market went north, or vice versa. Figure 4.8b shows a similar plot of the monthly returns for Exxon. In contrast to MCI, Exxon was a defensive, low-beta stock. It was not highly sensitive to market movements, usually lagging when the market rose and yet doing better (or less badly) when the market fell. The slope of the line of best fit shows that on average an extra 1 percent change in the index resulted in an extra .61 percent change in the price of Exxon stock. Thus Exxon`s beta was .61.

You may find it interesting to look at Table 4.9, which shows how past market movements have affected several well-known stocks. Exxon had the lowest beta: its stock return was .61 times as sensitive as the average stock to market movements. Microsoft was at the other extreme: its return was 1.33 times as sensitive as the average stock to market movements.