Calling In the Chips

Figures 6-3a and 6-3b show the effect of negative 8 8 on "best," "worst," and middle groups by price-to-cash flow, and price-to-earnings. Out-of-favor stocks again win in a breeze.* Lets start by looking at price-to-cash flow (Figure 6-3a). Negative su rises in analysts forecasts have a minimal impact on the lowest 20% of stocks in the 8 8 quarter, resulting in this group falling below the market by only 8/1 Oth of 1%. Moreover, the market shrugs off the 8 8 by the end of the year, with the out-of-favor group outperforming the market by 2/10 of 1%. The results for the lowest P/Es (Figure 6-3b) and price-to-book value (not shown) are similar.

Negative 8 8 8 are Hke water off a ducks back for this group. Investors have low expectations for what they consider lackluster or bad stocks, and when they do disappoint, few eyebrows are raised. The bottom line is that a negative 8 8 is not much of an event in the 8 8 quarter and is a non-event in the nine months following the news.

Consider the "best" companies, however. Investors expect only glowing prospects for these stocks. After all, they confidently-ovrconfi-dently-believe that they can divine the future of a "good" stock with precision. These stocks are not supposed to disappoint; people pay top dollar for them for exactly this reason. So when the negative su rise arrives, the resuhs are devastating.

Figure 6-3a shows how "best" stocks, by price-to-cash flow, react to negative eamings 8 8 8. In the quarter that investors receive the news, the stocks unde erform the market by a startUng 4.8%. They do six times as badly as the lowest price-to-cash flow group, when receiv-

* Although not shown, the effect to price-to-book value is very similar.

Maybe these companies are not as bad as analysts and investors believed. Out-of-favor stoclcs, therefore, do not just move up in the quarter of the 8 8 and then drop baclc again, as do the favorites. Instead, they continue to move steadily higher relative to the market in the year following the 8 8 .

We have seen three distincdy different reactions to earnings 8 18 by the high, low, and middle stock groups using three of the most important value measurements. Like the weather, however, all days cant be sunny-and all news cant be good. Negative 8 5 8, which normally send chills down investors spines, are the other side of the coin we need to examine.

Figure 6-3a

Price/Cash Flow Negative Surprises

Compustat 1500 1973 - 1996

<

-10%

-12% 14

Surprise Quarter

Full Year

I Low P/CF Quintile Middle Quintiles □ High P/CF Quintile

0% = Market Return (3.6% quarterly, 15.6% annually) All figures are market adjusted.

ing "bad" . Worse yet, wiiile tiie most out-of-favor stocics outperform the market sUghtly in the next nine months, the favorites continue to drop. At the end of the year, they are 11.3% under the averages. Favorite stocks with negative 8 8 8 unde erform the markets retum by a shocking 72% annually, on average, over the 24 years of the study. As Figure 6-3a also shows, the lowest price-to-cash flow group outperforms the highest by a remarkable 11.5% in years when both groups suffer negative 8 18 8.

Figure 6-3b, which measures negative 5 8 by price/eamings ratio, shows similar results. Negative 8 18 8 on the highest 20% of stocks drop the stocks 8 1 in the 8 18 quarter, followed by a much larger decline in the next nine months.

What do we make of numbers like these? Its apparent that investors are shaken when companies they expect to excel disappoint. The disappointment doesnt have to be large. You may remember that we purposely used a very small analyst forecast error-one cent and over-to

Figure 6-3b

Price/Earnings Negative Surprises

Compustat 1500 1973 - 1996

Pi

<

Surprise Quarter

Full Year

i Low P/E Quintile

E Middle Quintiles

□ High P/E Quintile

0% = Market Return (3.6% quarterly, 15.6% annually) All figures are market adjusted.

see iiow precise estimates have to be. From the major declines of high-visibility stocks on even nominal forecast errors, it appears the accuracy demanded of eamings forecasts is far too high.

We saw in the last chapter (Table 5) that the probability of avoiding a negative 8 18 of more than 5% was one in 110 for 10 quarters, and one in 12,000 for 20 quarters. The current study indicates that investor tolerance for negative 8 18 8 on popular stocks is even lower than this. If we blithely overlook these results and believe a wider forecast error range of plus or minus 10% is tolerable, then there is still only a 1 in 35 chance of dodging a negative in 10 quarters-with the odds going up to one in 1,250 for 20. Considering the devastating effects of negadve su rises on favorite stocks, these are odds no rational person should want to face.

Too, we observed in the last chapter that analysts are, on the whole, overoptimistic in their forecasts. The combination of large forecast er-