Predicting Betas
Adjusted betas are a simple way to recognize that betas estimated from past data may not
be the best estimates of future betas: Betas seem to drift toward 1 over time. This suggests
that we might want a forecasting model for beta.
One simple approach would be to collect data on beta in different periods and then esti-
mate a regression equation:
Current beta
5 a 1 b (Past beta)
(8.30)
Given estimates of a and b, we would then forecast future betas using the rule
Forecast beta
5 a 1 b (Current beta)
(8.31)
There is no reason, however, to limit ourselves to such simple forecasting rules. Why not
also investigate the predictive power of other financial variables in forecasting beta? For
example, if we believe that firm size and debt ratios are two determinants of beta, we might
specify an expanded version of Equation 8.30 and estimate
Current beta
5 a 1 b
1
(Past beta)
1 b
2
(Firm size)
1 b
3
(Debt ratio)
Now we would use estimates of a and b
1
through b
3
to forecast future betas.
Such an approach was followed by Rosenberg and Guy,
17
who found the following
variables to help predict betas:
1. Variance of earnings.
2. Variance of cash flow.
3. Growth in earnings per share.
4. Market capitalization (firm size).
5. Dividend yield.
6. Debt-to-asset ratio.
Rosenberg and Guy also found that even after controlling for a firm’s financial charac-
teristics, industry group helps to predict beta. For example, they found that the beta values
of gold mining companies are on average .827 lower than would be predicted based on
financial characteristics alone. This should not be surprising; the 2 .827 “adjustment factor”
for the gold industry reflects the fact that gold values are inversely related to market returns.
Table 8.4 presents beta estimates and adjustment factors for a subset of firms in the
Rosenberg and Guy study.
17
Barr Rosenberg and J. Guy, “Prediction of Beta from Investment Fundamentals, Parts 1 and 2,” Financial
Analysts Journal, May–June and July–August 1976.
Compare the first five and last four industries in Table 8.4 . What characteristic seems to determine whether
the adjustment factor is positive or negative?
CONCEPT CHECK
8.5
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