62, according to Bloomberg. Takeyour pick. Compare those levels with the 16.1 average over the past 50 years—
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or, again, some other number of your choice. You might well ask how it ispossible to conclude anything about so mercurial a financial ratio.There is no easy solution to the problem of such discrepancies in P/Edata. Many companies on a calendar year don’t report results until mid-April.As a result, it is often difficult to determine whether a particular P/E numberreflects the past 12 months of reported earnings or calendar-year earnings.Moreover, it is uncertain whether companies that lost money (and hence have“negative earnings”) are included in the overall market’s P/E calculation. Yetanother problem is that the earnings may be revised subsequently, so thatdata originally reported are quite different from what eventually appears insummaries, price records, and data sources many years thereafter.Looking back in time, the P/E-returns link is nebulous. The P/Es of 30that prevailed in 1929 and the poor returns in subsequent years are alwayscited as evidence of a predictive relation. But at the beginning of 1970, theS&P 500 P/E was 16 and the subsequent five-year annualized return was −6percent per year. At the beginning of 1994, the P/E was 21.3 and the subsequent five-year annualized return was 21 percent.How can we determine, in a systematic, scientific fashion, the actual relation of P/Es and returns, instead of just relying on anecdotes and vague impressions? The first step in discovering what relations exist, if any, is to usethe information that would have been available to an investor when makingthe decision to buy or sell. We use the printed past copies of the Standard &Poor’s Price Index Record for this purpose.3 The data considered were from1974 to 2001.Next, it is necessary to examine scatter diagrams. Figures2.4, 2.5, and 2.6 show the relation between P/E levels at theopening of a year to S&P 500 returns in subsequent years one,five, and nine.The charts show the shakiness and time-sensitivity of the P/E-returns relation. In Figures 2.4 and 2.6, which illustrate one-year and nine-year returns,the line slopes down from left to right, showing a slight inverse relationship.In other words, high P/Es have a slightly negative, but statistically insignificant, and almost certainly random, impact on the market in the next one- andnine-year time frames.In Figure 2.5, the five-year returns chart, the line is horizontal, showingno association between P/Es and returns for the next five years. For that timeperiod, P/Es had no predictive value.In his 2000 book, Irrational Exuberance, Robert Shiller omitted to showthe five-year chart or those of any other time frames that showed a positiverelationship. Those charts would not have shown irrational exuberance. A
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SPX 1-Year Return (%)
0.30.20.10.0–0.1–0.2–0.3
10
20P/E Level at the Open of Year #1
30
y = 15% – 3⁄1000 (x)R2 = 2%
Figure 2.4 P/E Level at Open of Year One as Predictor of One-Year SPXReturn. Source: Standard & Poor’s Security Price Index Record.
further problem with his work is that in a century, you only get 10 nonoverlapping 10-year periods (years 1–10, 11–20, etc.), and thus, statistically there areonly 10 data points even though a century of returns is included. As any statistician will tell you, fewer than 30 points is too few to reach a judgment given the variability involved.In sum, our studies show the relation between P/Es and returns from 1950 to 2001 is completely consistent with randomness.We are not alone in our conclusion about the lack of a strong relation between P/Es and market returns. Kenneth L. Fisher and Meir Statman, in a definitive study covering the years 1872 through 1999, also concluded that P/Esprovide unreliable forecasts of future returns. “There is no statistically significant relation between P/E ratios at the beginning of the year and returns during the following year, or during the following two years,” they wrote.4In an e-mail to us, Fisher alluded to the “weird assumptions” underlyingShiller’s conclusions. “The Shiller stuff is largely a data mine,” he wrote. “Itmakes no real difference how you redefine high and low P/E, regardless. P/Ehas no significant predictive power for markets so far into the future that it isenough to drive most folks crazy, that is, longer than five years.”
SPX Annualized 5-Year Return (%)
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0.2
0.1
1⁄3 (x)
0.0
10
1520P/E at Open 5 Years Ago
25
y = 9% + 0 (x)R2 = 0.1%
Figure 2.5 P/E Level at Open of Year One as Predictor of Annualized FiveYear SPX Return, 1974–2001. Source: Standard & Poor’s Security PriceIndex Record.
Because of the way P/Es are calculated, there is a strong bias for the data toshow a positive relation. The bias hinges on the little-noted fact that earnings ofcalendar-year-reporting companies are not released as of year-end. They’re released from a month to three months later. If there is a nice positive surprise inthese earnings, then the return that year will get a head start. That introduces abias in favor of the negative correlation that Shiller wished to show.For example, assume that the P/E for the market is always 10. Thus, onDecember 31 of each year, the price of a particular stock is 100 and prospective earnings are 10. Assume that in March, surprisingly good earnings of $12are reported. The price will move to 120 once the earnings are reported. Butthe P/E in the data files, retrospectively calculated with year-end prices andthe earnings announced in March, would be 100 / 12, or 8.5. The stock’s “return” that year would already be 20 percent at the time of the earnings report.Thus, low P/Es are associated with high returns. Similarly, high P/Es willtend to be associated with low returns.We have brought this bias up in meetings with many academics whohave studied these relations, including Professor Shiller. Invariably, the professors respond that they adjust for this bias when they can by using price
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0.2
0.1
0.010
1520P/E at Open 9 Years Ago
25
y = 12% – 2⁄1000 (x)R2 = 3%
Figure 2.6 P/E Level at Open of Year One as Predictor of Annualized NineYear SPX Return, 1978–2001. Source: Standard & Poor’s Security PriceIndex Record.
data on announcement dates to as great an extent as possible. But adjustments are only possible in recent years. The professors always add somethingto the effect that the whole thing is nebulous because the only companies thatare included in their data are those that reported positive earnings in the yearsunder consideration.There are so many things wrong with using data such as these that nomeeting of the minds is possible between the academics and skeptics like us.As mentioned, there are other biases, such as the look-back bias, that makeconclusions based on historic files even more tenuous. No wonder that almost all the practical applications of low P/E/high return funds have shownsuch dismal performance. Even with all the biases that would tend erroneously to support the P/E-return relation posited by Shiller, the actual datashow a correlation close to zero.The only way that academics have had of supporting such relations is touse numerous overlapping data points in their studies and, in the case of certain academics, to leave out recent data that shows a completely opposite relation from the one that started the war.Considering that the relation is so weak, why do so many people believe it?Fisher and Statman believe that the answer lies in a psychological phenomenon
Spotting Corporate Earnings PropagandaTo an economist, earnings represent the recurring cash flows that can bepaid out to stockholders without reducing the value of the firm. But theearnings reported to stockholders are accounting earnings,subject to numerous conventions and assumptions that permit wide latitude. Furthermore, accounting practices are always evolving. The best minds among accountants, consultants, andmanagers unfortunately have strong incentives to use their knowledgeand talents to develop more dynamic, sophisticated, and opaque accounting techniques. As Darwin and Wallace pointed out with numerous examples, the end result of an adaptation is far removed from its originalexpression. As a result, explanations of earnings quality contained inbooks tend to be dated and incongruous.For example, Haim Levy’s excellent text, Introduction to Investments,first published in 1980, advises the reader that high-quality earnings areconservative, distributable, stable, ongoing, domestic, understandable,operating, and normal. Low-quality earnings are said to be volatile, liberal, unpredicted, nonrecurring, unrealistic, overstated, complex, offshore, and related to financial transactions. While all these examples aresensible, they lack the compelling sharpness of a firing-line study ofcurrent accounting practices such as the Wall Street Journal and the better financial publications are always documenting. It is as though a current book on manufacturing were to rely on a study of mid-19th centurydivision-of-labor practices.Levy’s list of “red flags,” including long audit reports, reductions indiscretionary costs, and changes in accounting practices, seems moreappropriate for the new millennium. All the specific examples of overstated assets and understated liabilities, however, can be subsumedunder the rubric of excessive accruals relative to cash earnings, as described in this chapter.To keep the stock price ball in the air, companies must strive to constantly meet analysts’ expectations. Accountants often seem to act aspromoters of the desired earnings picture rather than as watchdogs orindependent checkers. To guard against naïve digestion of earnings reports, good analysts maintain checklists to sort out the good from thebad. We compiled our own list of some currently popular accountingtechniques that obscure the picture of a company’s financial health.(continued)55
1. Front-end income loading. Reporting income from a job immediately although the work will take an extended period of time.2. Borrowing. Using leverage to give the appearance of growth.3. Capitalizing costs. Some companies capitalize costs as assets,then amortize the deferred expenses over future periods.America Online, for example, capitalized the expense of sending out its software to potential future customers rather thanexpensing the costs as incurred. Firms have substantial discretion as to software development costs, start-up costs, and soforth. Investors should look out for sudden increases in capitalized costs.4. Timing costs. Manipulating discretionary costs such as advertising and R&D to smooth earnings.5. Timing sales. Accelerating or decelerating sales activities tosmooth earnings.6. Acquisitions Accounting I: Writing off R&D. When one companybuys another company, any excess paid above the acquired company’s assets is allocated between specifically designated intangible assets and goodwill. Some firms allocate a large portion of theexcess purchase price to an intangible asset called R&D in progress. After the purchase, they write it off and incur a one-timeloss. From then on, any benefits derived from such research arenot offset against any R&D costs. To get a better overall picture ofthe company, a good analyst will ignore the write-off, keep R&D asan asset on the balance sheet, and amortize it.7. Acquisitions Accounting II: Fuzz. Combining big acquisitionswith cloudy disclosures that make it difficult to compare earnings with previous periods.8. Acquisitions Accounting III: Goodwill. Amortizing goodwillover a long period of time will not affect earnings as much asamortizing it over a short period. Thus companies that can writeoff goodwill over a longer period have an advantage.9. Restructuring charges. The costs involved in a restructuring areusually expensed immediately. In a “big bath” strategy, companiescan “accidentally” overestimate the size of the restructuring reserve, then gradually reverse this error over time, generating anice stream of noncash income for the future.
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10. Consolidating results. The widely used “equity” method lets acompany report its entire share of a subsidiary’s income as partof its own income, without having to report the subsidiary’s assets or liabilities on the parent’s balance sheet.11. Asset impairment charges. The Financial Accounting StandardsBoard’s Rule 121 requires firms to write down the value of assetson their balance sheets whenever the present value of the projected cash flows to be generated by those assets is less than theirbook value. This gives management a lot of leeway, because it ismanagement that estimates future cash flows. Managers maywrite down assets during years when earnings are poor anyway,hoping investors will ignore this as a one-off event. With futuredepreciation expenses thus reduced, future earnings will lookmuch better.12. Accounting for stock options. Companies have much leeway indeciding whether and how to report executive and employeestock options as an expense. FASB gives a choice of three methods to companies that voluntarily choose to expense options.13. Inventories and receivables. Manipulating reported earnings byplaying around with current assets such as accounts receivablesand inventory, with apt estimates of the salability of the formerand the collectability of the latter.14. The storehouse. Relying on reserves, one-time gains in marketable securities, or sales of assets to smooth earnings.15. Timing an accounting method switch. Adopting new accountingstandards early or late to maintain the earnings trend.16. Changing auditors. This can mean that the management wantsto use accounting trickery to maintain the earnings trend. Themarket generally punishes companies that change auditors, as itcan give the appearance of impropriety. In the wake of theEnron/Andersen scandal, many firms had the chance to switchfrom Andersen and be rewarded for it by the market.S&P’s New StandardThe Standard & Poor’s securities rating firm has introduced a method ofcalculating earnings that is designed to reduce earnings distortions. Thenew measure, called “core earnings,” adjusts net income to include:(continued)57
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• Expenses from stock-option grants.• Restructuring changes from ongoing operations.• Write-downs of depreciable or amortizable operating assets.• Pension costs.• R&D expense assumed through acquisitions.The measure excludes:• Gains or losses from asset sales.• Pension gains.• Unrealized gains or losses from hedging securities.In some cases, the change would be quite material. GE, for example,reported net income of $1.42 a share in 2001. If the company had excluded gains from pension investments, however, earnings would havebeen $1.11, according to S&P. Cisco Systems reported net income of 14cents a share in fiscal 2001, but if the company had included stock-optionexpenses, that would have been a 35 cent-a-share loss, S&P said.Between the list of modern techniques of manipulation highlightedhere and S&P’s core earnings concept, the reader should have a goodheads-up on the usual suspects in the early naughties. These might besupplemented with a foundation provided by the excellent books Quality of Earnings by Thornton L. O’glove,5 Financial Shenanigans byHoward Schilit,6 or The Dark Side of Valuation by Aswath Damodaran.7
known as the “illusion of validity.” People are prone to believe and rely on theaccuracy of their judgments much more than the facts warrant. Fisher alsospeculates that people believe in the P/E fantasy because our ancestors foundgreat survival value in being afraid of heights, and they passed along theirgenes to us. “Anything in a heights framework generates fear,” Fisher wrote.Even high P/Es.Our friend Dr. Brett Steenbarger, professor of psychiatry and behavioralsciences at the SUNY Upstate Medical University in Syracuse, New York,whose primary research interest is multivariate behavioral modeling of thestock market, suggested in a May 2002 e-mail to us that a second type of illusion might be at work:
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A group of researchers at the London Business School recently completed a studyin which they showed that traders who display a high degree of “illusion of control” also achieve subpar results in their trading.The way “illusion of control” was measured was by giving the traders a computer game that involved guessing numbers in a sequence and then assessingtheir confidence re: future success. The traders didn’t know that the numbers represented a random walk. So the confident traders were a bit like chart readers whoexpress confidence in reading patterns derived from coin flips.I would argue that traders and investors focus on earnings numbers for the same reason that dying people focus on the afterlife. It’salso the reason why the No. 1 search engine topic immediately after 9/11was “Nostradamus.” In the face of uncertainty, people have a need forunderstanding and control. They will latch onto any explanation ratherthan go without one. An illusion of control is better than no perceivedcontrol.This is why panic attack sufferers will construct elaborate hypotheses abouttheir illness. If their attack happens in a mall, they avoid malls; if the attack occurswhile thinking about a particular topic, they try to banish that topic from consciousness. The example I use in my book is the patient who had her first attackon the ramp of an interstate highway and who, thereupon, refused to drive onramps, including those of indoor garages and the like.Such avoidance caused practical problems for the patient (who stopped driving altogether), but also reinforced the illusion that she could control her anxiety.Seen from this perspective, when the media goes into a frenzy about the relation between earnings and future stock prices, this can be seen as a response tothreat and uncertainty. It provides information about the psychological state ofmarket participants. And that might even be tradable information, though not inthe way that the media pundits intend.Note how the financial news viewer ratings skyrocket in bull markets andduring market plunges. Those are the times viewers most feel a need to figure outwhat to do with their money. They are either missing opportunities or losingmoney. Latching onto technical and fundamental analysis is their way of searching for answers and gaining control.Ironically, one could probably use those viewer ratings as afairly accurate market timing tool!
Student QuestionerWhen we held our luncheon interview with Dr. Shiller, we expected the sparksto fly. Strangely, Shiller was tentative about the robustness and resilience of
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his results. He pointed out that one of his students, Bjorn Tuypens, had prepared a paper that questioned the accuracy of his conclusions. “Perhaps therelation has changed or is no longer valid,” he told us.Tuypens’ paper, “Stock Market Predictability: A Myth Unveiled,” provided further support for our conclusions:The use of overlapping data for long-term stock returns, combined with thenonstationary behavior of the dividend yield, gives rise to spurious regressionproblems when regressing long-term stock returns on dividendyields. . . . This regression (dividend yield versus subsequent one-yearand two-year returns) provides additional evidence for the argumentthat the strong long-run forecasting power of the Campbell-Shiller regressions is a myth, due to the use of overlapping data in too small a data set.8
On the other hand, Shiller told us that he remains confident that the market is in for a period of abnormally low returns. He also expressed confidencethat “econometric studies will verify the significance of the negative P/E relationships” that he and his colleagues have found. He appeals here to an ito process, a highly complicated, almost impossible-to-test relation involving what iscalled stochastic calculus. Since the essence of such results is that current P/Esinfluence returns in distant years much more than they influence currentyears, the relation seems to us to be completely implausible. Furthermore,such topsy-turvy relations relative to time are completely opposite to any thatwe have found in real-life applications involving the calculation and testing oftens of thousands of such relations.It seems more likely, for example, that the P/E of the market as of yearend 2002 will have a much stronger influence on 2003 returns than the P/Ethat prevailed in 1993. Only a professor could argue against this.Shiller emphasized to us that his current interests are in other fields.
How Earnings Propaganda WorksThe adherence of investors and academics to causal relations thatare completely opposite from the empirical facts raises some deepwhy and how questions.Our explanation draws on lessons learned from the study of propaganda.The propagandists of the market, who specialize in fear and greed to the samedegree as advertising pros and political propagandists do, make efficient useof these spurious relations. When we first reported in 2002 in our column forCNBC Money that the relation between P/Es and returns was almost entirely
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random—contrary to the standard paradigm that guarantees that the publicwill always be leaning the wrong way—our ideas generated considerable skepticism. Incredulous readers of our columns checked our credentials andwrote in to say that Laurel, who earned a bachelor’s degree in fine arts, shouldgo back to playing the piano and that Vic should stick to racquet sports, as hiseconomics analysis was as bad as his hedge fund management. We were toldthat we had completely misconstrued what the academics say about earnings:that it is expectation that matters, not realization. The kindest thing said aboutour theory was that we had simply rediscovered and put in convoluted, abstract prose the simple maxim that you should buy when there is blood in thestreets and sell when the trumpets are sounding.Still other readers objected that stock prices are determined by expectationsof earnings rather than the actual earnings themselves. As earnings come in,they might provide little information about future expectations and thus wouldnot be expected to have an impact.We do not buy that for a minute. Revisions in expectations must behighly correlated with the actual reported comparisons of the earningsthemselves. Furthermore, numerous academic studies of the impact ofearnings revisions on the S&P 500 have been made, and none of thesehave found any relationship between revisions in earnings and future returns. (One curious result that has been found is that the variability of therevisions in earnings expectations has a weak positive relation to returnsseveral years later.)The article also brought a deluge of invective from the bearish camp. Thefollowing was typical:I think you guys are liers [sic] or just bad reporters. If you are a lier, you are a badreporter. So you must be both a bad reporter and a bad lier. Get a conscience.You sound like you are long on your investments. . . . One can only concludeyour extreme irrational almost military-like bias can only mean that you arelong, you lost lots of money, and are holding on till death do you and yourmoney part.
The irony is that on April 1, the day we received this letter, we had a massive short position in the market, which we memorialized in a CNBC Moneydispatch that day.The kind of name-calling employed in that message is a typical propaganda technique. Propaganda induces individuals to take actions that benefitthe messenger more than the listener. The Fine Art of Propaganda,a 1939 classic on the topic published by the Institute of Propaganda Analysis, outlined seven basic techniques to disseminate
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false information.9 To simplify the ideas enough for young students in publicschools, the book gave each technique a catchy name: “name-calling,” “glittering generality,” “transfer,” “testimonial,” “plain folks,” “card stacking,” and“bandwagon.”Here is our take on how each technique is used to disseminate the fallacies involving the relation of earnings and P/E to returns:Name-calling: “Only a blindfolded bull would buy stocks at these levels.”Glittering generality: “There’s no value in the market with these stratospheric P/Es.”Transfer (invokes a name or symbol): “Until P/Es fall to Graham & Doddlevels, we’re forecasting a Dow of 100.”Testimonial: “The oldest and canniest investor I know is waiting for P/Esto fall by another 50 percent before he considers buying.”Plain folks: “I don’t know much, but the last time P/Es were this high anddividend yields were this low was year-end 1928.”Card stacking: “P/Es were above 20 at the beginning of 1929 and stocksfell 40 percent in the next two years.” (Forget that P/Es were the exactsame level at the beginning of 1950, when prices rose 40 percentover the next two years.)Bandwagon: “None of the hedge fund managers at the conference in BarHarbor will touch these high P/Es with a 10-foot pole.”How frequently is misinformation on the relation of earnings to marketreturns transmitted? Millions of articles contain variants of the misleading belief that the better the market earnings, the better the market return. Our ownsearch, using the Internet search engine www.google.com, found 2.7 millionarticles containing the words “U.S. stocks,” with about 1.3 million also containing the word “earnings” or “profit.” Of those, 323,000 contained “optimism” or synonyms thereof. Some 75,000 articles contained a combinationof the words “earnings” or “profit” and “pessimism” or a synonym. No doubt,some of these word conjunctions had nothing to do with our topic. But we canmake a rough estimate that the lie appears in half of all stories that mentionearnings and the market.
Why Do the Beliefs Persist?Regardless of the propaganda techniques, rational people usually have amechanism to overturn false beliefs that hinges on the prospering of thosewho can differentiate truth from falsehood. In this particular field, however, itis hard to make such a distinction because the things that people observe
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most clearly are P/Es and returns of individual stocks. They know that whenearnings are bad for companies they own stock in, that they suffer losses, andconversely, when earnings are good, they enjoy gains. This is true. The problem comes when they try to generalize this to the broad market.Such generalizations suffer from logical errors: the fallacy ofcomposition, the fallacy of aggregation, and the ecological fallacy.The following trains of thought show the fallacy of composition:• “Since I can see the concert better by standing on my seat, it followsthat if everybody stood on their seats, we would all have a better view.”• “Phil and Mary are excellent singers. They will form an excellent duo.”• “The person who gets a gold medal is happy. If everyone got gold medalsthey would all be happy.”This error crops up in investors’ thinking as a confusion between whatpeople know about individual stocks and what they know about the market:“If good earnings are good for my stock, and bad earnings are bad, then whenearnings for companies that make up the broad market are generally good,that’s bullish and when earnings are generally woeful, that’s bearish.”The fallacy of aggregation is the assumption that what holds true on asmall scale is also true on a large scale. The fallacy is usually illustrated bypointing out the error of the statement that a six-foot man cannot drown in apond with an average depth of one foot. For our purposes, a better example isthat of the isolated miner who picks away at a mountain trying to find gold. Itis true that the more he picks away, the less the size of that mountain. However, without taking into account soil erosion, weather patterns, landslides,and sloughing, as well as the feedback that occurs between the mountain andefforts of hundreds of similar miners, we cannot make any assumptionsabout the relation of one miner’s activity to the size of the mountain.Similarly, everyone knows that individual stock prices are related in somedirect way to the favorability of earnings. But to generalize from that to thesystem of the stock market and total profits in the economy requires hundreds of leaps that ignore effects just as great as landslides down a mountain;for example, the landslides of interest-rate rises and declines, tax policychanges, and Federal Reserve actions.A related error is the ecological fallacy—the assumption that what istrue on the large scale is true on the small scale. This mistake is commonto most studies of diet in a given population. A typical study will conclude,for example, that the amount of fiber intake is positively related to longevity.The finding, however, cannot be particularized to the recommendationthat an individual in a particular country should eat more fiber to live alonger life.
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Time to Get Out (Artist: Susan Slyman, 2001).Our finding that earnings changes and stock prices are inversely relatedbrings disbelief because of the ecological fallacy. Those who hear it particularize the finding. They say that, if true, this inverse relationship would mean thatindividual stock returns are also inversely related to earnings changes, just asthe health studies fail to note differences between the activities and eatinghabits of individuals within the individual countries. Victims of the ecologicalfallacy fail to take into account industry differences and time differenceswithin the stock market. Thus, because they cannot accept that our inverse relation could possibly be true, they reject it out of hand as antithetical to whatthey know is true.Another reason for the longevity of these mistaken notions undoubtedlyis that earnings are defined so vaguely as to defy scrutiny of any supposed relation to market returns. Should the investor look at year-over-year comparisons or reported earnings relative to expectations? Current expectations, orinitial expectations? Official expectations or whisper numbers? Earnings relative to the stage in the business cycle, or relative to industry peers? And whichearnings are key? Operating? Pro forma? GAAP? Cyclically adjusted? Net?The vagueness about precisely which earnings are being discussed barelyhints at the problem. Our friend Larry Leeds provided some insight into the
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complexities involved. Larry has been running a hedge fund specializing instocks of retailers and has managed to garner a seven-year annual return of 42percent as of year-end 2002. He likes to buy stocks of companies that reportpoor first-quarter numbers. Often, their Christmas season was so good thatthey have nothing in stock to sell, and so they miss their comparisons. Retailersthat report good first quarters still had plenty of good winter merchandise tosell because their Christmas was terrible.Furthermore, companies have developed multiple ways to paint the rosiestpossible picture of their finances. Chief executives who guide research analysts’earnings estimates down so that their firms can beat them later are practicing anice form of card stacking. Such “positive surprises” have the virtueof triggering the systems and recommendations of quants who havefound, based on stale studies, that such earnings surprises have predictive significance.
The Escalation of Hide-and-SeekCorporate earnings propaganda has long been part of Wall Street routine, andreporters love to catch companies at the game. As a wire service editor, Laurelobserved firsthand the corporate art of timing an earnings announcement. IfGAAP earnings are up, the company releases its statement just before or afterthe close, and schedules a telephone conference an hour later so executivescan issue “guidance” on the next quarter