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Security Analysis and Business Valuation on Wall Street,: A ... - lib

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CHAPTER 11Financial Projecti<strong>on</strong> PointersMost research reports incorporate sales <str<strong>on</strong>g>and</str<strong>on</strong>g> earnings projecti<strong>on</strong>s of the companyunder study. Before jumping into the business of making projecti<strong>on</strong>s,the analyst should know popular approaches <str<strong>on</strong>g>and</str<strong>on</strong>g> comm<strong>on</strong> pitfalls. Moderatingoptimistic assumpti<strong>on</strong>s with reality checks is an important part ofthis work.C<strong>on</strong>structing accurate financial projecti<strong>on</strong>s is a difficult task. As the top-down approachin Chapter 5 illustrated, so many variables affect a firm’s performance—<str<strong>on</strong>g>and</str<strong>on</strong>g> they originate in so many sectors of the ec<strong>on</strong>omy, the industry, <str<strong>on</strong>g>and</str<strong>on</strong>g> the companyitself—that the forecasting process appears well nigh impossible. The academicliterature is full of studies showing the inaccuracy of earnings estimates. Even <strong>on</strong>eyearforecasts have a mean error of 25 to 30 percent, but what choice do we have?Every<strong>on</strong>e knows the Graham <str<strong>on</strong>g>and</str<strong>on</strong>g> Dodd approach of picking cheap stocks <strong>on</strong> thebasis of low price/earnings (P/E) <str<strong>on</strong>g>and</str<strong>on</strong>g> low price/book ratios, so these opportunitiesare scarce. Relative value analysis identifies pricing inefficiencies, but the investorrisks plunging into an already overvalued sector. Notwithst<str<strong>on</strong>g>and</str<strong>on</strong>g>ing the problem offorecasts, the basis for stock prices tends to be forward looking, <str<strong>on</strong>g>and</str<strong>on</strong>g> there remainrati<strong>on</strong>ales for why this should be the case. That’s why secti<strong>on</strong> 6 of the research reportis critical.Practiti<strong>on</strong>ers aren’t seers, so it’s fortunate that no <strong>on</strong>e seeks perfecti<strong>on</strong> in securityanalysis. As noted earlier, the analyst who is right 60 to 70 percent of the time isc<strong>on</strong>sidered a superstar. And being right doesn’t mean predicting earnings per sharedown to the penny year after year. Just detecting when the c<strong>on</strong>sensus forecast fallsout of the bounds of comm<strong>on</strong> sense is a great service to investors, who then use thisinformati<strong>on</strong> as a buy or sell signal.In this chapter, we cover projecti<strong>on</strong> methodology at the company-specific level<str<strong>on</strong>g>and</str<strong>on</strong>g> review principles that make you a better forecaster. The nuts <str<strong>on</strong>g>and</str<strong>on</strong>g> bolts of projecti<strong>on</strong>s,such as assigning growth percentages to revenues <str<strong>on</strong>g>and</str<strong>on</strong>g> applying inventoryto-salesratios, are covered in Chapter 8 (the Neiman Marcus case), this chapter (theHuntsman Chemical case <str<strong>on</strong>g>and</str<strong>on</strong>g> the William Wrigley case), Chapter 15 (the TemporaryStaffing Services case), <str<strong>on</strong>g>and</str<strong>on</strong>g> Chapter 19 (the Ruddick Corporati<strong>on</strong> case).181

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