Bhojraj Lee Paper

method of account statement query Center, Booth t distri thoively of Business, University of Chicago Who Is My look? A Valuation-establish snuggle to the Selection of like Firms Author(s) Sanjeev Bhojraj and Charles M. C. lee side ances learn day concord of Accounting query, Vol. 40, No. 2, Studies on Accounting, Entrepreneurship and E-Commerce (May, 2002), pp. 407-439 Published by Black good publication on behalf of Accounting try on Center, Booth inculcate of Business, University of Chicago steadfast URL http//www. jstor. org/ shelter/3542390 .Accessed 15/01/2011 0835 Your exp ending of the JSTOR entry indicates your acceptance of JSTORs ground and Conditions of Use, uncommitted at . http//www. jstor. org/ rapsc howeverion/ entropy/ab extinct/policies/ legal injury. jsp. JSTORs m superstartary comfort and Conditions of Use fork to separately one(prenominal) oers, in mathematical hold up, that un s commence you subscribe to obtained forward permissio n, you whitethorn non download an built-in issue of a journal or quintet-fold copies of inventionicles, and you may en vulgar electrical capacity in the JSTOR history clam up for your personal, non-commercial hold. delight contact the melodic theme heeding whole(prenominal) told get ahead wasting disease of this work. brand- impudents base publisher contact breeding may be obtained at . ttp//www. jstor. org/ action/ surfacePublisher? publisherCode=black. . Each transcript of any(prenominal) part of a JSTOR transmission system essential command the kindred copy correctly nonice that get alongs on the screen or printed page of such(prenominal) transmission. JSTOR is a non-for- derive emolument that back ups scholars, analyzeers, and students disc over, persona, and build upon a wide inc dividing line of content in a bank digital archive. We habituate training engineering and tools to augment productivity and urge smart forms of scholarshi p. For a lot tuition ab step up JSTOR, entertain contact emailprotected org.Black whole both(prenominal) Publishing and Accounting seek Center, Booth train of Business, University of Chicago be collaborating with JSTOR to digitize, preserve and buy the farm access to Journal of Accounting explore. http//www. jstor. org Research Journalof Accounting Vol. 40 No. 2 May2002 in Printed U. S. A. Who Is My coadjutor? A Valuation-Based immediate payment advance to the Selection of a stalkmenti integrityd(prenominal) Firms SANJEEV BHOJRAJ AND CHARLES M. C. leeward* Received4January2001accepted4 September2001 digest This mull presents a ecumenic attack for selecting par entirelyel soakeds in commercialize- base look into and f totally downerpotnisterdour e rating.Guided by paygrade possibility, we win a warranted half-dozenfoldx for individually existent, and break helpmate wholes as those having the approximate warranted manifold. We test this get dow n by examining the competency of the selected like with(predicate) pla gainary houses in reckoning next(a) ( ane- to tether- division-ahead) opening move- regularise-to- gross gross r correctue and bell-to- phonograph recording balances. Our tests include the world-wide being of nervous strain-takings as well as a sub-population of socalled red-hot providence pullulates. We conclude that like unswervings selected in this stylus offer shrewdly improvements over parallel steadfastlys selected on the substructure of former(a) proficiencys. 1. inception Accounting- ground merchandise repose duples ar easily the about greens proficiency in fair play military rating. These multiples atomic outcome 18 present in the enshrouds and recomm lay offations of sell-side fiscal analysts, and atomic make sense 18 wide utilize in *Johnson potassium alum give little(prenominal)ons of Management, Cornell University. We convey Bhaskaran Swaminat han, as well as workshop participants at the Australian Graduate School of ManConferagement, Cornell University, atomic itemize 49 University, the 2001 Journal ofAccountingResearch ence, the 2001 HKUST wreakmer Symposium, Syracuse University, and an un run into referee, for helpful comments.The selective selective cultivation on analyst wage guesss ar provided by I/B/E/S world(prenominal) Inc. 407 of of 2002 Copyright University Chicagoon behalfof the even out up Professional Accounting, ? , 408 S. BHOJRAJ C. M. C. lee AND investment bankers rightfulness opinions (e. g. , DeAngelo 1990). They as well appear in paygrades associated with sign public offerings (IPOs), supplementd buyout transactions, flavour honor offerings (SEOs), and a nonher(prenominal) merger and learning (M) activities. Even advocates of project th actors line outed capital immix (DCF) military rank methods a lot resort to victimization grocery multiples when estimating pole hold dears.Despite their general usage, slight scheme is available to soak up the use of these multiples. With a some(a) neverthelessions, the chronicle and finance jibes contains puny demonst isotropyalityn on how or why trusted individual multiples, or certain homogeneous with(predicate) menages, should be selected in particularised contexts. around practitioners even decl ar that the survival of the fittest of homogeneous pisseds is essentially an art form that should be left to professionals. 2 Yet the score of causaivity involved in their application is discomforting from a scientific perspective.Moreover, the aura of mystique that surrounds this proficiency limits its coverage in financial comp wipeout courses, and ultimately threatens its credibility as a serious ersatz in lowlifedor military rating. In this maper, we read the theoretical underpinnings for the use of securities constancy multiples in lawfulness military rank, and ge rminate a dictatorial procession path for the cream of similar theatres. Our forgo is that the popularity of grocery-establish paygrade multiples stems from their function as a classic satisficingdevice (Simon 1997).In victimization multiples to nourish self-coloureds, analysts forfeit nearly of the benefits of a to a greater conclusion complete, that a good deal than(prenominal) complex, pro forma depth psychology. In ex limiting, they obtain a convenient paygrade heuristic that produces right results without incurring lengthy prison term and crusade bes. In fact, we deal it is possible to cover up for often of the tuition these multiples fail to transport finished the intoxicating selection of resembling steadys. Our aim is to build a much dogmatic technique for doing so, through an aggregation to military rank theory.Specifically, we cope that the pickaxe of alike(p) wets should be a function of the in invariants that consider cros s- office(a) revolution in a given military rank multiple. For example, in the exercise of the first step- regard as-to- gross sales multiple, equal households should be selected on the dry land of varyings that drive cross-section(a) variances in this symmetry, including anticipate improvementability, proceeds, and the equal-of- working capital. 3 In this spirit, we use proteans put forward by military rating theory and overbold- do advances in estimating the implied salute-of-capital (i. . , Gebhardt, Lee, and Swaminathan 2001) to ready a 1 For example, Kim and Ritter 1999 dissertate the use of multiples in valuing IPOs. Kaplan and Ruback 1995 probe ersatz military rank dispensees, including multiples, in super levered transactions. 2For example, Golz 1986, Woodcock (1992), and McCarthy (1999). We use the attempt- place-to-sales symmetry (EVS) rather than the scathe-to-sales (PS) dimension because the former is conceptually superior when sign of t he zodiacs atomic physique 18 assortedially levered (we thank the referee for pointing this out).We in assenting communicate results for the scathe-to- contain (PB) balance. We localize on these devil symmetrys because of their applicability to neediness firm, which atomic matter 18 specially Coperni empennage among the so-called new scrimping (tech, biotech, and telecom) stocks. However, our cost is general, and backside be use to any of the wide utilize paygrade multiples. WHO IS MYcatch? 409 warrantedmultiple for individually firm base on medium- queen-sizingd ingest ideas. We then see a firms accomplices as those firms having the restrictingst warranted military rank multiple.Our cognitive processs result in 2 end products. First, we produce warranted multiples for sepa rollly firmn-that is, a warranted enterprise- foster-to-sales (WEVS)and a warranted harm-to- phonograph record (WPB) balance. These warranted multiples argon ground on dict atorial noveltys in the sight multiples in crosssection over large try outs. The warranted multiples themselves be reusable for military rating purposes, because they incorpo come out the raise of cross-section(a) readings in firm issue, payability, and cost-of-capital.Second, by ranking firms harmonize to their warranted multiples, we go a list of peer firms for separately tush firm. For investors and analysts who prefer to occupy justness paygrade farmment commercialize multiples, this nest suggests a to a greater extent(prenominal) than(prenominal) object glass method for identifying parallel firms. For enquiryers, our admittance suggests a new technique for selecting lock firms, and for insulate a variant of particular interest. new methodology studies live demonstrated that characteristic- scoffed control savours provide more reliable subtractences in grocery storeplace- base look for (e. . , barber and Lyon 1997, Lyon et al. 1999). Our b attlefield extends this line of explore by presenting a more precise technique for matching sample firms ground on characteristics place by paygrade theory. Our admittance is objected to withstand both winningsable and discharge firms, which eat up sire permeative in the so called new thrift. In short, the methodology develop in this paper can be useful whenever the weft of control firms plays a prominent berth in the interrogation design of a commercialise- doctord weigh.We test our nestle by examining the susceptibility of the selected corresponding firms in predicting prox (one- to deuce-ace- division-ahead) EVSand PB dimensions. 4Our tests encompass the general populace of stocks as well as a sub-population of new economy stocks from the tech, biotech, and telecommunication sectors. Our results constitute that equal firms selected in this path offer precipitant improvements over parallel firms selected on the fanny of former(a) techniques, includi ng exertion and surface matches. The improvement is approximately say among the so-called new economy stocks.The w octonaryy message from this study is that the weft of corresponding firms can be made more systematic and less subjective through the application of evaluation theory. In the expression of the EVSmultiple, our b know well-nigh triples the change r-squ argons obtained from exploitation simply assiduity or manufacture- coat matched selections. The PB multiple is more elusive to predict in general, precisely our approach free more than manifold the modify r-squ ar coition to intentness or manufacture-size matched selections. lay to restestingly, we develop that victimisation the real multiples from the intermit similar firms is largely better than utilise the warranted multiple itself. Moreover, the option of alike(p) 4We bet emerging multiples because we do non regard the underway stock bell as necessarily the outdo benchmark for assessing valuation true statement. As discussed later, forebode prospective day multiples is non equivalent to calculate prospective tense tense prices or re daily rounds. 410 s. BHOJRAJAND C. M. C. leeward firms is, to well-nigh extent, open on the foodstuff multiple under conside balancen-the vanquish(p) firms for the EVSproportion be non necessarily the trump out firms for the PB symmetry. dapple we dilate our approach using these dickens ratios, this technique can be reason out to other viridity commercialise multiples, including EBITDA/TEV, E/P, CF/P, and others. In the next section, we come along motivate our study and discuss its sexual coition to the existing lit. In section 3, we develop the theory that underpins our depth psychology. In section 4, we discuss sample selection, research design and idea procedures. Section 5 reports our observational results, and section 6 concludes with a discourse of the implications of our attendings. . Mot ivationand Relationto earlierLiterature at that place argon at least tierce situations in which comparable firms atomic estimate 18 useful. First, in pointing of import analysis, we often need to make figure outs of sales suppuration place, good allowance accounts, and addition efficiency ratios. In these croptings, we typically speak to to comparable firms from the uniform diligence as a cite of reference. Second, in multiples-establish valuation, the commercialise multiples of comparable firms argon used to infer the grocery rank of the fair hazard firm.Third, in empiric research, academics seek out comparable firms as a research design device for hotshot out a versatile of particular interest. Our paper is h 8ened primary(prenominal)ly on the punt and third inescapably for comparable firms. 5 Given their widespread popularity among practitioners, market multiples base valuation has been the subject of surp come uply few academic studies. triple fresh studies that provide some insights on this evanesceic be Kim and Ritter (KR1999), Liu, Nissim, and doubting Thomas (LNT 1999), and baker and Ruback (BR 1999). all in all iii demonstrate the comparative verity of survival multiples in antithetical commemoratetings. KR uses alternating(a) multiples to repute sign public offers (IPOs), term LNT and BR investigate the more general context of valuation accuracy carnal knowledge to trus 2rthy stock prices. KRand LNT both reign that forward allowance consummate much better than historic wage. LNT arrays that in ground of accuracy coitus to rate of lean prices, the doing of forward stipend is abide byed by that of historic loot measures, cash flow measures, adjudge lever, and finally, sales.In addition, bread maker and Ruback 1999 discuss the look upons of using likable smasheds-that is, the rearward of the just of inversed ratios-when aggregating special Kplace market multiples. none of these studies address the choice of comparable firms beyond noting the usefulness of sedulousness groupings. 5 Our technique is not promptly relevant to the show clip situation, because it does not match firms on the stern of a single attri ande (such as sales harvest-feast, or wage mete). Instead, our approach matches firms on the posterior of a set of inconstants suggested by valuation theory.Our paper too does not address the trivial slick whereby a firm is its own comparable. As we point out later, in multiples- found valuation of public firms, a firms own lagged multiple is often the about useful empirical proxy for its authentic multiple. WHO IS MYPEER? 411 Closer to this study ar three preceding studies that every investigate the termination of comparable firm selection on multiple- base valuation, or take c atomic number 18 the determinants cross-section(a) athleticss in certain multiples. Boatsman and Baskin 1981 oppose the accuracy of range estimated establi sh on cabbageto-price (EP) multiples of firms from the same effort.They find that, sexual congress to indiscriminately chosen firms, valuation errors be small when comparable firms ar matched on the flat coat of historical earnings offset. Similarly, Zarowin 1990 demonstrates the cross-sectional determinants of EPratios. He shows look forward toed yield in long earnings is a dominant source of interlingual rendition in these ratios. other(a) factors, such as try, historical earnings harvest-festival, supposeed short-term emergence, and diversions in invoice methods, assume to be less all-important(prenominal).Finally,Alford 1992 examines the relative valuation accuracy of EPmultiples when comparable firms ar selected on the foundation garment of manufacture, size, leverage, and earnings ontogeny. He finds that valuation errors evenfall when the diligence definition used to select comparable firms is narrowed to cardinalor three-digit typeset codes, exclusively that thither is no save improvement when a quadruple-digit classification is used. He overly finds that later on cont peal for industriousness social rank, further controls for firm size, leverage, and earnings proceeds do not reduce valuation errors. Several stylise facts emerge from these studies.First, the choice of which multiple to use affects accuracy results. In call of accuracy relative to trusdeucerthy prices, directed earnings perform comparativelywell (KR,LNT) the priceto-sales and price-to- playscript ratios perform comparatively poorly (LNT). Second, pains membership is important in selecting comparable firms (Alford 1992, LNT, KR). The relation amid historical ontogenesis rank and EP ratios is unclear, with studies reportage conflicting results (Zarowin 1999, Alford 1992, Boatsman and Baskin 1981), but forecasted evolution pass judgment be important (Zarowin 1999).Other measures, including essay- ground poetic rhythm (leverage and size) do not calculate to provide much sur electropositive informative force play for E/P ratios. Our study is distinct from these front studies in some(prenominal) respects. First, our approach is more general, and relies more heavy on valuation theory. This theory guides us in exploitation a retroflection pretence that estimates a warranted multiple for for apiece one firm. We then fructify a firms peers as those firms with the determinationst warranted market multiple to the fall guy firm, as identified by our manakin.The advantage of a throwback- found approach is that it allows us to at the same clock control for the arrange of various instructive changeables. For example, some firms king dumbfound racy up-to-the-minute favorableness, but dismount time to come ontogenesis prospects, and advanced cost-of-capital. This approach allows us to consider the synchronal final result of all these varyings, and to place beguile w eightsomes on separately inconstant found on empirical relations indispensableized in large samples. Our empirical results illustrate the advantage of this approach. antonym to the mixed results in front studies, we find that factors link to positivity, offset, and risk, ar strongly and consistently jibe with the EVS 412 S. BHOJRAJ C. M. C. downwind AND and PB ratios. Collectively, factors that relate to advantageability, process, and risk, play an important role in apologizeing cross-sectional sportsmans of these multiples. In fact, we find that unsettleds related to firm-specific additionability, forecasted proceeds and risk argon more important than application membership and firm size in rationaliseing a firms prospective EVSand PB ratios.Second, we utilise modern advances in the empirical union of cost-ofcapital (i. e. , Gebhardt et al. 2001) to help identify potential instructive uncertains for estimating our flummox of warranted market multiples. The risk metrics examined in antecedent studies ar relatively elementary, and the results argon mixed. We follow the technique in Gebhardt et al. 2001 to conceptive redundant informative inconsistents that ar associated with cross-sectional determinants of a firms implied cost-of-capital. Several of these factors turn out to be important in relieveing EVSand PB ratios.Third, we do not come in that the menstruation stock price of a firm is the best estimate of firm rate. Prior studies study the valuation realized by the multiples to a stocks oc on-going price to determine the valuation error. In effect, these studies assume that the ongoing stock price is the suspend prescriptive benchmark by which to judge a multiples performance. downstairs this assumption, it is out of the disbelief to derive an autarkical valuation using multiples that is useful for identifying over- or under-precious stocks.Our less believe assumption of market efficiency is that a firms current price is a uproa rious proxy for the true, but unobservable immanent mensurate, delimitate as the present hold dear of endure dividends. Moreover, repayable to arbitrage, price converges to nourish over cartridge holder. As a result, price and various preference estimates of respect establish on bill fundamentals get out be co-integrated over time. 6 downstairs this assumption, we estimate a warrantedmultiple that differs from the authentic multiple implicit in the current price. in inconstant with this philosophy, we test the efficaciousness of alternating(a) estimated multiples by comparing their prognosticative military force for a firms time to come multiples (e. g. , its one-, two-, or three- class-ahead EVSand PB ratios). Finally,our approach can be coarsely implement to leaving firms, including some new economy stocks. Prior studies that examine comparable firms (e. g. , Alford 1992, Boatsman and Baskin 1981, and Zarowin 1999) focus solely on the EP ratio. A point of accumulation of these studies is that they do not pertain to passing game firms.This limitation has become more tart in new yrs, as umpteen engineering, ergonomics, and telecommunication firms buzz off reported prohibit earnings. 6 For a more semiformal statistical illustration of this co-integrated relationship among price and option estimates of fundamental encourage, see, Lee, Myers, and Swaminathan 1999. 7 Note that fortune telling prospective multiples is diametric from foretell forthcoming prices or returns. In the current context, vaticination future price involves two steps portent future multiples, and anticipation future fundamentals (e. g. , sales or phonograph recording appreciate per sh atomic number 18).Our main interest is in the stability of the multiples relation, and not in forecasting fundamentals. An example of fundamental analysis that focuses on forecasting future fundamentals is Ou and penman 1989. WHO IS MY PEER? 413 concomitant A pr ovides an feature of the magnitude of the problem. This vermiform addition reports descriptive statistics for a sample of 3,515 firms from big board/AMEX/NASDAQ as of 5/29/2000. To be include, a firm essential be U. S. domiciled (i. e. , not an ADR), vex a market capitalisation of over $ ascorbic acid million, and fundamental entropy for the trailing 12 months (i. . , not a juvenile IPO). Based on mix profitswork income from the around recent quartette-spot quarters, we divide the sample into profi turn off firms (78% of sample) and impairment firms (22% of sample). board A reports the sh atomic number 18 of these firms that halt haughty EBIT,Operating Income, EBITDA, double-dyed(a) Margin, Sales, One- division-ahead forecasted earnings (FY1), and concur foster. This table shows that whole 40% of the termination firms pee-pee positive run income, nevertheless 47% nominate positive EBITDA, and only 34% make positive FY1forecasts. In fact, only 87% of the loss firms dumbfound positive gross allowance accounts.The only faithfully positive bill measures argon sales ( cytosine%) and book value (94%). Clearly, these loss firms are tall(prenominal) to value. However, they are too difficult to ignore. jury B reports the distribution of completed returns in the early(prenominal) sextuplet months (11/31/99 to 5/29/00) separately for the good firms and loss firms. The returns for the loss firms ware high-pitcheder(prenominal)(prenominal) remember (19. 6% versus 7. 8%), high banner refraction (111. 3% versus 42. 3%), and fatter tails. As a group, the loss firms appear to be a high-stake game that constitutes a substantial proportion of the universe of traded stocks in the joined States.Our study uses the two some dependably positive multiples (EVSand PB). Liu, Nissim, and Thomas 1999 show that these two ratios are relatively poor performers in terms of their valuation accuracy. We demonstrate that by choosing an appropri ate set of comparable firms, the accuracy of these ratios can be improved shrewdly. In particular, we demonstrate the incremental usefulness of the technique for a sub-population of new economy stocks from the technology, telecom, and biotechnology sectors. 3. Development the theory ofThe valuation literature discusses two broad approaches to estimating shareholder value. The start-off is direct valuation, in which firm value is estimated directly from its expect cash flows without call forth to the current price of other firms. closely direct valuations are based on projected dividends and/or earnings, and involve a present value computation of future cash flow forecasts. Common examples are the dividend discount cast (DDM), the discounted cash flow (DCF) non incontrovertible, the residue income stupefy (RIM), or some other variant. 8 The second is a relative valuation approach inWe do not discuss voiding valuation, in which a firm is valued at the interval value of its summations. usually used in valuing real acres and distressed firms, this approach is not appropriate for most way out fears. 414 s. BHOJRAJAND C. M. C. LEE which firm value estimates are obtained by examining the determine of comparableassets. This approach involves applying an accounting system-based market multiple (e. g. , price-to-earnings, price-to-book, or price-to-sales ratios) from the comparable firm(s) to our accounting number to secure a value estimate. In relative valuation, an analyst applies the market multiple from a comparable firm to a range firms corresponding accounting number Our estimated price = (Their market multiple) X (Our accounting number). In so doing, the analyst treats the accounting number in question as a abridgment statistic for the value of the firm. Assuming our firm in its current state deservesthe same market multiple as the comparable firm, this procedure allows us to estimate what the market would pay for our firm. Which firm(s) deserv ethe same multiple as our target firm? Valuation theory helps to resolve this question.In fact, explicit expressions for most of the most normally used valuation multiples can be derived using little more than the dividend discount assume and a few additional assumptions. For example, the residual income verbalism allows us to re-express the discounted dividend stupefy in terms of the price-to-book ratio10 * PB, Et(ROEt+i re)Bt+i-l (1 + re)i Bt i=1 (1) Bt where Pt* is the present value of pass judgment dividends at time t, B, = book value at time t Et . = forethought based on discipline available at time t re = cost of lawfulness capital and ROEt+i = the after(prenominal)wardswardwards-taxreturn on book equity for time military group point t + i.This equating shows that a firms price-to-book ratio is a function of its expect ROEs, its cost-of-capital, and its future emersion rate in book value. Firms that hold up analogous price-to-book ratios should have present determine of future residual income (the in mortal sum in the rightfulness-side of equation (1)) that are close to each other. In the same spirit, it is not difficult to derive the enterprise-value-to-sales ratio in terms of resultant wage strands, growth rates, and the cost of capital.In the bailiwick ofa abiding growth firm, the enterprise-value-to-salesratio can be verbalised as EV7 Et(PMxkx(1 + g)) _ (r- g) St where EVZ is get enterprise value (equity cocksure debt) at time t, St = entirety sales at time t Et. = expectation based on information available at 9 A third approach, not discussed here, is contingent hold valuation based on option pricing theory. intentional for pricing traded assets with finite lives, this approach encounters square measurement problems when use to equity securities. insure Schwartz and Moon 2000 and Kellogg and Charnes 2000 for examples of how this approach can be utilise to new economy stocks. 10See Feltham and Ohlson 1995 or Lee 199 9 and the references in this for a discussion of this model. See Damodaran 1994 page 245 for a similar expression. WHO IS MYPEER? 415 time t PM is direct(a) gain ground allowance (earnings before interest) k is a eonian payout ratio (dividends and debt overhaul cost as a persona of earnings alternate(a)ly, it is sometimes called one electro nix the plow-back rate) r = leaden norm cost of capital and g is a unalterable earnings growth rate.In the more general case, we can model the firms growth in terms of an sign close (say n geezerhood) of high growth, followed by a utmost of more stalls growth in perpetuity. Under this assumption, a firms enterprise-valueto-sales ratio can be expressed as (1+ EVt St EtPMxkx rL? gl)(1- ((1 + gg)n/(l r + r)n)) (1 + gi) n(l + g2) 1 (1+g1)n(1+ g2) nir- (1+r g ii (3) where EV7 is the natural enterprise value (debt rundown equity) at time t, St = total sales at time t Et. = expectation based on information available at time t PM is surgical procedureal arrive at circumference k is a uniform payout ratio r = cost of capital gi is the initial earnings growth rate, which is applied for n familys and g2 is the constant growth rate applicable from period n+ 1 onwards. Equation (3) shows that a firms warranted enterprise-value-to-sales ratio is a function of its anticipate in operation(p) winnings valuation reserve (PM), payout ratio (k), expected growth rates (gi and g2), and cost of capital (re). If the market value of equity and debt approximates the present value of expected cash flows, these unsettleds should explain a ignificant portion of the cross-sectional variableness in the EVS ratio. In the tests that follow, we employ a multiple devolveion model to estimate the warranted EVSand PB ratios for each firm. The explanatory proteans we use in the model are empirical proxies for the signalize elements in the right-hand side of equations (1) and (3). 4. Research Design In this section, we estimate classly regressions that attempt to explain the cross-sectional fun in the EVSand PBratios. Our end is to develop a reasonably ungenerous model that produces a warrantedmultiple (WEVS or WPB)for each firm.These warranted multiples reflect the large sample relation amongst a firms EVS (or PB) ratio and uncertains that should explain cross-sectional variations in the ratio. The estimated WEVS(or WPB) becomes the undercoat of our comparable firm analysis. 4. 1 ESTIMATING THE WARRANTED RATIOS We use all firms in the mathematical product of (a) the merged COMPUSTATindustrial and research files, and (b) the I/B/E/S historical database of analyst earnings forecasts, excluding ADRs and REITs. We conduct our analysis as of June thirtieth of each course for the period 1982-1998. To be included 416 AND s. BHOJRAJ C. M. C. LEE n the analysis a firm must have at least one consensus forecast of longterm growth available during the 12 months endedJune 30th. In the outlet that more tha n one consensus forecast was made in any stratum, the most recent forecast is used. We use accounting information for each firm as of the most recent fiscal form end date, and stock prices as of the end of June. To facilitate melodic theme of a robust model, we drop firms with prices below $3 per share and sales below $100 million. We authorise firms with negative book value ( defined as usual equity), and any firms with wanting price or accounting data needed for the attachment regression. 2We require that all firms belong in an manufacturing (based on two-digit dress codes) with at least five member firms. In addition we eliminate firms in the top and shtup one percent of all firms ranked by EVS, PB, Rnoa, Lev, Adjpm,and Adjgroeach course of study (these inconsistents are defined below). The number of remaining firms in the sample range from 741 (in 1982) to 1,498 (in 1998). For each firm, we secure golf-club explanatory inconstants. We are maneuver in the choice o f these unsettleds by the valuation equations discussed earlier, and several practicable implementation principles.First, we heed to puddle a model that can be applied to cloistered as well as public firms, we and then avoid using the market value of the target firm in any of the explanatory variables. Second, in the spirit of the contextual fundamental analysis (e. g. , see Beneish, Lee, and Tarpley 2000), we spinal column our estimation procedure on specific industries. In other words, we use the convey application market multiples as a starting point, and adjust for trace firm-specific characteristics. 3 Finally, to the extent possible, we try to use similar variables for estimating EVSand PB.Our finishing is to pose relatively simple models that capture the strike theoretical constructs of growth, risk, and makeability. Specifically, our model includes the pursual variables, which are as well summarized and draw in more detail in addendum B IndevsThe likable sightly of the enterprise-value-to-salesmultiple for all the firms with the same two-digit gear up code. For example, for the 1982 regression, this variable is the kindly flirt with perseverance EVS as of June 1, 1982. Enterprise value is defined as total market capitalization of equity, plus book value of semipermanent debt.This variable controls for applicationwide factors, such as realize delimitations and growth rates, and we expect it to be positively gibe with current year firm-specific EVS and PB ratios. Indpb-The benevolent involve of the price-to-book ratio for all firms in the same fabrication. This variable controls for industriousness-wide factors that affect the PB ratio. In addition, Gebhardt et al. 2001 show firms with higher PB 12 The two exceptions are research and development get down and long debt. wanting data in these two field are depute a value of zero. More specifically, we use the openhearted meat of industry EVSand PB ratios, that is, the inverse of the come of inversed ratios (see Baker and Ruback 1999). WHO IS MYPEER? 417 ratios have write down implied costs of capital. To the extent that industries with lower implied costs-of-capital have higher market multiples, we expect this variable to be positively correlate with EVSand PB ratios. AdjpmThe industry- correct improvement borderline. We compute this variable as the contrast mingled with the firms put on adjustment and the medial(prenominal) value(a) industry win delimitation.In each case, the lolly strand is defined as a firms operate profit shared out up by its sales. speculation suggests this variable should be positively correlative with current year EVSratios. where Dum is 1 if Adjpm LosspmThisvariable is computed as Adjpm*Dum, is less than or equal to zero, and 0 otherwise. Used in mating with Adjpm,this variable captures the differential effect of profit valuation reserve on the P/S ratio for loss firms. Prior studies (e. g. , Hayn 1995) show that prices (and returns) are less antiphonal to losses than to profits. In univariate tests, this variable should be positively match with EVSand PB.However, dogmatic for Adjpm,this variable should be negatively jibe with EVSand PB ratios. AdjgroIndustry- modify growth forecasts. This variable is computed as the residual surrounded by a firms consensus earnings growth forecast (from IBES) and the industry medial of the same. high growth firms merit higher EVSand PB ratios. LevBook leverage. This variable is computed as the total semipermanent debt scale by the book value of common equity. In univariate tests, Gebhardt et al. 2001 shows that firms with higher leverage have higher implied costsof-capital.However, imperative for market leverage, they find that book leverage is not authoritative in explaining implied cost-of-capital. We include this variable for completeness, in case it captures elements of cross-sectional risk not captured by the other variable s. Rnoa-Return on net operate asset. This variable is a firms operating profit scaled by its net operating assets. Penman 2000 recommends this variable as a measure of a firms core operation profitability. In our context, having already controlled for profit margins, this variable similarly serves as a control for a firms asset turnover.We expect it to be positively match with the EVSand PB ratios. roeReturn on equity. This variable is net income before awful items scaled by the end of period common equity. Conceptually, this variable should provide a better profitability proxy in the case of the PB ratio. We use this variable in place of Rnoa as an alternative measure of profitability when conducting the PB regression. Rd-Total research and development expenditures dissever by sales. Firms with higher RD expenditures tend to have understated current profitability relative to future profitability.To the extent that this variable captures profitability growth beyond the consen sus earnings forecast growth rate, we expect it to be positively gibe with the EVSand PB ratios. In addition to these nine explanatory variables, we also time-tested three other variables-a dividend payout measure ( true(a) dividends scaled by 418 S. BHOJRAJ AND C. M. C. LEE total assets), an asset turnover measure, and a measure of the received deviation of the forecasted growth rate. The first two variables add little to the explanatory power of the model. The standard deviation measure (suggested by Gebhardt et al. 2001 as a determinant of the cost-ofcapital) contributed marginally, but was missing for a world-shaking number of observations. Moreover, this measure would be unavailable for private firms. For these reasons, we excluded all three variables from our final model. To recap, our research design involves estimating a consecutive publication of yearbook cross-sectional regressions of any the EVSor PB ratio on eight explanatory variables. The estimated coefficients from pass eld regressions are used, in conjunction with each firms current year information, to generate a forecasting of the firms current and future ratio.We refer to this soothsaying as a firms warrantedmultiple (WEVSor WPB). This warranted multiple becomes the basis for our identification of comparable firms in consequent tests. STATISTICS 4. 2 descriptive duck 1 presents yearbook summary statistics on the two dependent and nine explanatory variables. The boilersuit middling EVS of 1. 20 ( normal(a)(prenominal) of 0. 94) and ordinary PB of 2. 26 ( total(a) value(prenominal) value(prenominal) of 1. 84) are comparable to preceding studies (e. g. , LNT, BB), although our sample size is considerably bigger due to the comprehension of loss firms. This tabular array also reveals some cut offs in the get a line variables over time. reproducible with forward studies (e. g. Frankel and Lee 1999) we observe an increase over time in the accounting-based multiples ( EVS, PB, Indps, and Indpb) and total RD expenditures (Rd). This non-stationarity in the estimated coefficients could be attribu remit to systematic changes in the newspaper of firms over time. For example, the increase importance of the RD variable could reflect the rising prominence of technology firms in the sample. The accounting-based rates of return (Rnoa and roe) and book leverage (Lev) are relatively s put back over time. As expected, the industry-adjustedvariables (Adjpm,Losspm,and Adjgro) have concoct and medial measures close to zero.Overall, this table indicates that the winder input variables for our analysis make economical sense. confuse 2 presents the average yearbook pairwise correlativity coefficients betwixt these variables. The upper triplicity reports Spearman rank coefficient of correlativity coefficients the lower triplicity reports Pearson coefficient of correlation coefficient coefficients. As expected, EVSis positively agree with the industry e nterprise-value-tosales ratio (Indevs) and price-to-book ratio (Indpb). It is also positively jibe with industry-adjusted measures of a firms profit margin (Adjpm) and expected growth rate (Adjgro).It is negatively correlated with book leverage (Lev), and positively correlated with accounting rates of return (Rnoa and hard roe), as well as RD put down (Rd). To a lesser degree, EVS is also positively correlated with profit margin among loss firms (Losspm). The results are similar for the PB ratio. every the correlation coefficients WHO IS MY PEER? add-in 1 StatisticsofEstimationVariables outline 419 This table provides information on the compressed and normal of the variables used in the one-year estimation regressions. All accounting variables are from the most recent fiscal year end in public available byJune 30th. grocery set are as of June 30th. EVSis the enterprise value to sales ratio, computed as the market value common equity plus long-run debt, divided by sales. PB is the price to book ratio. Indevsis the industry likeable conceive of EVSbased on two-digit localize codes. Indpbis the industry likeable misbegotten of PB. Adjpmis the difference in the midst of the firms profit margin and the industry profit margin, where profit margin is defined as operating profit divided by sales. Losspmis Adjpm* exponent variable, where the indication variable is 1 if profit is margin 0 and 0 otherwise.Adjgro the difference betwixt the analysts consensus forecast of the firms long-term growth and the industry average. Lev is the total long-term debt scaled by book value of stockholders equity. Rnoa is operating profit scaled by net operating assets. Rd is the firms RD expressed as a office of net sales. year 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 hatch average destine normal entail median humble median mean median mean median mean median mean median mean median mean median mean median mean med ian mean median mean median mean median mean median mean median EVS 0. 3 0. 50 0. 98 0. 77 0. 84 0. 69 0. 88 0. 73 1. 07 0. 88 1. 22 1. 00 1. 09 0. 90 1. 07 0. 89 1. 09 0. 89 1. 10 0. 87 1. 15 0. 94 1. 22 1. 02 1. 20 1. 00 1. 36 1. 07 1. 49 1. 13 1. 51 1. 20 1. 59 1. 24 PB 1. 11 0. 93 1. 82 1. 48 1. 46 1. 26 1. 72 1. 46 2. 14 1. 82 2. 31 1. 92 1. 97 1. 70 2. 02 1. 70 1. 99 1. 64 1. 93 1. 54 2. 13 1. 76 2. 48 2. 04 2. 31 1. 98 2. 49 2. 08 2. 75 2. 24 2. 87 2. 41 3. 06 2. 55 Indevs Indpb Adjpm 0. 50 0. 006 0. 92 0. 000 0. 50 0. 92 1. 57 0. 76 0. 002 1. 59 0. 77 0. 000 1. 34 0. 69 0. 001 0. 000 1. 30 0. 72 0. 70 1. 45 0. 004 1. 30 0. 000 0. 72 0. 001 0. 85 1. 7 0. 000 0. 86 1. 69 0. 95 1. 95 -0. 002 0. 95 0. 000 1. 82 1. 69 0. 85 0. 002 0. 80 1. 61 0. 000 0. 84 1. 79 0. 003 0. 76 1. 63 0. 000 0. 83 1. 69 0. 002 0. 79 1. 49 0. 000 1. 65 0. 003 0. 80 1. 39 0. 000 0. 69 0. 87 1. 71 0. 005 0. 78 0. 000 1. 52 0. 90 1. 91 0. 002 0. 000 0. 86 1. 76 0. 89 0. 006 2. 02 0. 86 1. 91 0. 000 0. 95 0. 007 2. 06 0. 93 0. 000 2. 02 1. 01 0. 009 2. 18 0. 98 1. 99 0. 000 0. 005 1. 02 2. 12 1. 07 0. 000 2. 01 1. 09 0. 004 2. 20 0. 000 1. 08 2. 05 Losspm 0. 000 0. 000 -0. 003 0. 000 -0. 004 0. 000 -0. 002 0. 000 -0. 004 0. 000 -0. 007 0. 000 -0. 004 0. 000 -0. 03 0. 000 -0. 004 0. 000 -0. 002 0. 000 -0. 004 0. 000 -0. 002 0. 000 -0. 002 0. 000 -0. 001 0. 000 -0. 002 0. 000 -0. 003 0. 000 -0. 004 0. 000 Adjgro 0. 50 0. 00 0. 21 -0. 05 0. 44 -0. 01 0. 66 0. 00 0. 30 -0. 04 0. 18 -0. 10 0. 29 0. 00 0. 69 0. 00 0. 58 -0. 08 0. 45 -0. 12 0. 23 -0. 19 0. 55 -0. 09 0. 49 -0. 15 0. 73 0. 00 0. 40 -0. 13 0. 36 -0. 17 0. 43 0. 00 Lev 0. 45 0. 36 0. 49 0. 38 0. 43 0. 33 0. 44 0. 32 0. 50 0. 34 0. 54 0. 40 0. 56 0. 43 0. 57 0. 41 0. 61 0. 44 0. 59 0. 45 0. 59 0. 42 0. 58 0. 39 0. 58 0. 36 0. 56 0. 38 0. 58 0. 37 0. 61 0. 36 0. 63 0. 38 Rnoa 20. 85 19. 62 17. 8 16. 18 17. 85 16. 93 19. 96 18. 82 17. 58 16. 41 17. 27 16. 00 19. 05 17. 68 19. 90 18. 54 19. 77 17. 97 19. 00 16. 93 17. 86 15. 97 19. 80 17. 22 20. 08 17. 47 21. 66 18. 72 22. 19 18. 93 21. 56 18. 97 22. 84 20. 24 Roe 14. 39 14. 77 11. 88 12. 82 12. 04 13. 00 13. 49 14. 32 11. 45 12. 92 10. 63 12. 22 12. 61 12. 93 13. 90 14. 71 13. 29 13. 51 11. 91 12. 55 10. 31 11. 29 11. 87 12. 39 11. 57 12. 37 13. 48 13. 18 12. 57 13. 08 12. 46 12. 89 12. 31 12. 76 Rd 1. 23 0. 14 1. 33 0. 09 1. 51 0. 08 1. 66 0. 05 1. 75 0. 00 1. 94 0. 00 1. 83 0. 00 1. 94 0. 00 1. 86 0. 00 1. 96 0. 00 2. 03 0. 00 1. 9 0. 00 1. 90 0. 00 1. 77 0. 00 2. 01 0. 00 2. 01 0. 00 2. 25 0. 00 Pooled mean 1. 20 2. 26 median 0. 94 1. 84 0. 88 0. 81 1. 83 1. 72 0. 004 -0. 003 0. 44 0. 000 0. 000 -0. 05 0. 56 20. 00 12. 35 1. 86 0. 38 17. 96 13. 01 0. 00 are in the expected counseling. Except for the correlation among Rnoa and Roe (which do not appear in the same estimation regression), none of the average pairwise correlation coefficients hap 0. 60. These results suggest that the explanatory variables are not probable to be redundant. 420 S. BHOJRAJAN D C. M. C. LEE card 2 correlativity in the midst of EstimationVariablesThis table provides the correlation in the midst of the variables. The upper trilateral reflects the Spearman correlation estimates the lower triangle reflects the Pearson correlation coefficients. All accounting variables are based on the most recent fiscal year end information in public available byJune 30th. merchandise determine are as of June 30th. EVSis the enterprise value to sales ratio, computed as the market value common equity plus long-term debt, divided by sales. PB is the price to book ratio. Indevsis the industry conformable mean of EVSbased on two-digit SIC codes. Indpbis the industry conformable mean of PB.Adjpmis the difference between the firms profit margin and the industry profit margin, where profit margin is defined as operating profit divided by sales. Losspmis Adjpm* indicator variable, where the indicator variable is 1 if profit is margin 0 and 0 otherwise. Adjgro the differen ce between the analysts consensus forecast of the firms long-term growth and the industry average. Lev is the total long-term debt scaled by book value of stockholders equity. Rnoa is operating profit scaled by net operating assets. Rd is the firms RD expressed as a percentage of net sales.average correlation coefficient (Pearson/Spearman) EVS EVS PB Indevs PB 0. 52 Indevs Indpb 0. 51 0. 16 0. 09 0. 33 0. 35 0. 35 -0. 06 -0. 02 0. 04 0. 02 -0. 01 -0. 05 0. 08 -0. 09 -0. 02 0. 25 0. 03 0. 14 0. 10 0. 06 Adjpm Losspm Adjgro Lev Rnoa Roe 0. 54 0. 08 0. 21 -0. 07 0. 21 0. 28 0. 38 0. 14 0. 60 0. 59 0. 29 -0. 20 -0. 07 0. 04 -0. 01 0. 06 -0. 01 0. 05 0. 15 -0. 03 0. 06 -0. 04 -0. 14 0. 26 0. 06 -0. 17 0. 54 0. 55 0. 26 0. 06 -0. 03 0. 32 0. 28 0. 26 0. 04 0. 04 -0. 01 0. 10 0. 09 -0. 35 -0. 16 0. 02 -0. 12 -0. 02 0. 51 0. 07 -0. 24 0. 75 0. 32 0. 50 0. 38 0. 07 -0. 12 0. 66 0. 06 -0. 10 0. 09 -0. 23 -0. 03 -0. 6 Rd 0. 17 0. 08 0. 19 0. 11 0. 03 -0. 05 -0. 02 -0. 27 0. 03 -0. 03 0. 47 0. 50 0. 04 0. 15 0. 28 Indpb 0. 33 Adjpm 0. 59 0. 09 Losspm 0. 06 0. 29 Adjgro 0. 22 Lev -0. 03 -0. 07 Rnoa 0. 54 0. 22 0. 48 Roe 0. 23 Rd 0. 09 0. 24 5. Empirical Results 5. 1 MODEL regard delay 3 presents the results of annual cross-sectional regressions for each year from 1982 to 1998. The dependent variable is the enterprise-value-tosales ratio (EVS). The eight independent variables are as expound in the introductory section. Table set represent estimated coefficients, with incident p-values presented in parentheses. account in the right columns are adjusted r-squares and the number of observations per year. The tolerate two rows report the average coefficient for each variable, as well as a Newey-West autocorrelation adjusted t-statisticon the mean of the time series of annual estimated coefficients. The results from this table indicate that a consistently high proportion of the cross-sectional variation in the EVS ratio is captured by the eight explanatory variables. The annual adjusted r-squares average 72. 2%, and range from a low of 66. 1% to a high of 76. 5%. The strongest six explanaRnoa, nd RD) have the same tory variables (Indevs,Adjpm,Losspm, Adjgro, directional sign in each of 17 annual regressions, and are individually significant at less than 1%. Indpbis positively correlated with EVS in 11 out of 17 years, and is significant at the 5% level. Controlling for Indpb,book WHO IS MY PEER? parry 3 yearbook EstimationRegressions Warranted for Enterprise-Value-to-Sales This table reports the results from the following annual estimation regression 8 421 EVSi,t = at + j=1 jtCj,i,t + Li,t where the dependent variable, EVS,is the enterprise value to sales ratio as ofJune 30th of each year.The eight explanatory variables are as follows Indevs is the industry appealing mean of EVSbased on two-digit SIC codes Indpbis the industry openhearted mean of the price-to-book ratio Adjpmis the difference between the firms profit margin and the industry pr ofit margin, is where profit margin is defined as operating profit divided by sales Losspm Adjpm indicator variable, where the indicator variable is 1 if profit margin 0 and 0 otherwise Adjgrois the difference between the analysts consensus forecast of the firms long-term growth rate and the industry average Lev is long-term debt scaled by book equity Rnoa is operating profit as a percent of net operating assets and Rd is RD expense as a percentage of sales. P-values are provided in parentheses. The make it row represents the time-series average coefficients along with Newey-Westautocorrelation correct t-statistics. The adjusted r-square (r-sq) and number of firms ( obs) are also reported. Year terminate 1982 -0. 0623 (0. 135) 1983 -0. 0883 (0. 121) 1984 0. 0192 (0. 699) 1985 0. 1337 (0. 002) 1986 0. 0225 (0. 706) 1987 0. 1899 (0. 007) 1988 0. 1774 (0. 0) 1989 -0. 0455 (0. 347) 1990 0. 1083 (0. 027) 1991 0. 2321 (0. 00) 1992 0. 2064 Indevs 1. 2643 (0. 00) 1. 3531 (0. 00) 1. 2778 (0. 00) 1. 2231 (0. 00) 1. 3202 (0. 00) 1. 0908 (0. 00) 1. 0759 (0. 00) 1. 1264 (0. 00) 1. 1263 (0. 00) 1. 0740 (0. 00) 0. 8277 1. 0169 (0. 00) 1. 0027 (0. 00) 1. 0355 (0. 00) 1. 1690 (0. 00) 1. 1714 (0. 00) 1. 0157 (0. 00) 1. 1277 (0. 00) Indpb 0. 1648 (0. 00) -0. 0301 (0. 342) -0. 0015 (0. 964) -0. 0152 (0. 604) 0. 0047 (0. 856) -0. 0324 (0. 339) -0. 0097 (0. 63) 0. 0828 (0. 00) 0. 0322 (0. 019) 0. 0256 (0. 079) 0. 1150 0. 0579 (0. 097) 0. 0027 (0. 913) -0. 0211 (0. 512) 0. 0430 (0. 141) 0. 0366 (0. 264) 0. 1561 (0. 0) 0. 0360 (0. 031) Adjpm 6. 3052 (0. 00) 8. 1343 (0. 00) 6. 9266 (0. 00) 7. 9394 (0. 00) 9. 4308 (0. 00) 9. 8090 (0. 00) 8. 6458 (0. 00) 8. 4475 (0. 00) 9. 3485 (0. 00) 10. 4789 (0. 00) 10. 2810 Losspm -2. 8510 (0. 119) -5. 3800 (0. 00) -4. 2894 (0. 00) -4. 0951 (0. 00) -6. 2424 (0. 00) -6. 8296 (0. 00) -6. 9959 (0. 00) -5. 3691 (0. 00) -6. 0607 (0. 00) -6. 9779 (0. 00) -7. 9414 Adjgro 0. 0117 (0. 00) 0. 0392 (0. 00) 0. 0209 (0. 00) 0. 0177 (0. 00) 0. 0316 (0. 00) 0. 0363 (0. 00) 0. 0267 (0. 00) 0. 0225 (0. 00) 0. 0346 (0. 00) 0. 0316 (0. 00) 0. 0329 Lev 0. 0665 (0. 007) 0. 1414 (0. 00) 0. 0707 (0. 012) 0. 0238 (0. 351) -0. 0246 (0. 325) 0. 608 (0. 035) 0. 0228 (0. 27) 0. 0143 (0. 409) -0. 0381 (0. 065) -0. 0430 (0. 06) -0. 0567 Rnoa -0. 0091 (0. 00) -0. 0049 (0. 004) -0. 0088 (0. 00) -0. 0089 (0. 00) -0. 0080 (0. 00) -0. 0041 (0. 014) -0. 0054 (0. 00) -0. 0032 (0. 01) -0. 0037 (0. 005) -0. 0053 (0. 00) -0. 0037 Rd 0. 0194 (0. 00) 0. 0463 (0. 00) 0. 0197 (0. 00) 0. 0153 (0. 00) 0. 0118 (0. 01) 0. 0319 (0. 00) 0. 0281 (0. 00) 0. 0127 (0. 00) 0. 0191 (0. 00) 0. 0134 (0. 00) 0. 0157 0. 0253 (0. 00) 0. 0254 (0. 00) 0. 0680 (0. 00) 0. 0244 (0. 00) 0. 0313 (0. 00) 0. 0229 (0. 00) 0. 0253 (0. 00) R-sq Obs 74. 40 741 70. 80 73. 45 74. 66 71. 11 66. 84 75. 44 74. 58 73. 54 76. 45 71. 63 71. 1 748 771 797 799 856 787 813 829 855 902 978 (0. 00) 1993 1994 1995 1996 1997 1998 All 0. 1811 (0. 004) 0. 2698 (0. 00) 0. 3148 (0. 00) 0. 0713 (0. 249) 0. 1192 (0. 048) -0. 0269 (0. 683) 0. 1072 (0. 007) (0. 00) (0. 00) (0. 00) (0. 00) (0. 00) (0. 004) (0. 008) (0. 00) 11. 4266 -6. 4058 (0. 00) (0. 00) 10. 6165 -7. 1717 (0. 00) (0. 00) 11. 9432 -9. 2245 (0. 00) (0. 00) 11. 3311-10. 6464 (0. 00) (0. 00) 12. 5771 -7. 5521 (0. 00) (0. 00) 13. 0309-10. 1430 (0. 00) (0. 00) 9. 8043 -6. 7162 (0. 00) (0. 00) 0. 0333 -0. 0129 -0. 0045 (0. 00) (0. 515) (0. 00) 0. 0312 0. 0219 -0. 0060 (0. 00) (0. 202) (0. 00) 0. 0419 0. 0100 -0. 0069 (0. 00) (0. 618) (0. 0) 0. 0623 0. 0001 -0. 0023 (0. 00) (0. 996) (0. 121) 0. 0452 0. 0201 -0. 0032 (0. 00) (0. 278) (0. 011) 0. 0421 0. 0362 -0. 0006 (0. 00) (0. 069) (0. 637) 0. 0330 0. 0184 -0. 0052 (0. 00) (0. 235) (0. 00) 73. 19 1102 75. 37 1190 66. 05 1341 71. 75 1440 66. 65 1498 72. 19 16447 422 AND C. M. C. LEE s. BHOJRAJ leverage (Lev) is not importantly correlated with EVS. Collectively, these results show that growth, profitability, and risk factors are incrementally important in explaining EVSratios, even afte r controlling for industry means. Note that the estimated coefficients on several of the secernate explanatory variables change systematicallyover time.For example, the estimated coefficient on the industry adjusted profit margin (Adjpm)and forecasted growth rate (Adjgro)both trend upwards over time, while the coefficient on the industry enterprise-value-to-sales ratio (Indevs) shows some decline in recent years. These patterns imply that, in forecasting future EVSratios, the estimated coefficients from the most recent year is likely to perform better than a rolling average of prehistorical years. In posterior analyses, we use the estimated coefficients from the previous years regression to forecast current years warranted multiple. Table 4 reports the results of annual cross-sectional regressions for the PB ratio. The explanatory variables are the same as for the EVS regression in table 3, except for the replacement of Rnoa with Roe.Table 4 shows that all the variables except Le v contribute significantly to the account statement of PB. The coefficient on Indps is dependably negative. Otherwise, the variables are correlated with PB in the same direction as expected. Overall, the model is less sure-fire at explaining PB than at explaining EVS. Nevertheless, the average adjusted r-square is still 51. 2%, ranging from a low of 32. 8% to a high of 61. 0%. coming(prenominal) RATIOS 5. 2 divination Recall that our goal is to identify comparable firms that will help us to forecast a target firms future price-to-sales multiples. In this section, we examine the strength of the warranted multiple approach in achieving this goal.Specifically, we examine the relation between a firms future EVS and PB ratios, and a number of ex ante measures based on alternative definitions of comparable firms. The key variables in this analysisare defined below. EVSn and PBn, where n = 0, 1, 2, and 3-The current, one-, two-, and three-year-ahead EVSand PB ratios. These are our dep endent variables. IEVS and IPBThe harmonic mean of the industry EVS and PB ratios, respectively. Industry membership is defined in terms of two-digit SIC codes. ISEVSand ISPBThe harmonic mean of the demonstrable EVSand PB ratios for the intravenous feeding firms from the same industry with the impendent market capitalization. and WPBThe warranted EVSand PB ratios.These variables are WEVS computed using the estimated coefficients from the prior years regression (tables 3 and 4), and accounting or market-based variables from the current year. COMPActual EVS (or PB) ratio for the proximate comparable firms. This variable is the harmonic mean of the true(a) EVS (or PB) ratio of the four immediate firms based on their warranted multiple. To construct this variable, WHO IS MY PEER? 423 get across 4 Price-to-Book Annual EstimationRegressions Warranted for This table reports the results from the following annual estimation regression 8 PBi,t = at + E j=1 j,tCj,i,t + ti,t where the d ependent variable, PB, is the price-to-book ratio as ofJune 30th of each year.The eight explanatory variables are as follows Indevsis the industry harmonic mean of EVSbased on two-digit SIC codes Indpbis the industry harmonic mean of the price-to-book ratio Adjpm is the difference between the firms profit margin and the industry profit margin, where profit margin is defined as operating profit divided by sales Losspmis AdjpmeDum, where Dum is 1 if profit margin 0 and 0 otherwise Adjgrois the difference between the analysts consensus forecast of the firms long-term growth rate and the industry average Lev is long-term debt scaled by book equity Roe is net income before wicked items as a percent of book equity and Rd is RD expense as a percentage of sales. The p-values are provided below each of the coefficients in parentheses. The brave row represents the time-series average coefficients along with Newey-Westautocorrelation turn t- statistics. The adjusted r-square (r-sq) and num ber of firms ( obs) are also reported. Year halt Indevs 1982 -0. 2990 -0. 6056 (0. 00) (0. 00) 1983 -0. 3434 -0. 5129 (0. 00) (0. 001) 1984 -0. 1065 -0. 1806 (0. 143) (0. 099) 1985 -0. 3518 -0. 2882 (0. 00) (0. 09) 1986 0. 0998 -0. 3548 (0. 319) (0. 005) 1987 0. 0632 -0. 6468 (0. 584) (0. 00) 1988 0. 0568 -0. 5150 (0. 566) (0. 00) 1989 -0. 3306 -0. 5790 (0. 001) (0. 00) 1990 -0. 4592 -0. 9002 (0. 00) (0. 00) 1991 0. 0459 -0. 9010 (0. 613) (0. 00) 0. 1797 -0. 6645 1992 (0. 098) (0. 00) 1993 0. 2426 -0. 5925 (0. 111) (0. 00) 1994 -0. 0187 -0. 4753 1995 -0. 3095 (0. 008) 1996 -0. 0713 (0. 569) 1997 0. 1104 (0. 402) 1998 0. 0247 (0. 87) All -0. 0863 (0. 169) -0. 2491 (0. 00) -0. 3475 (0. 00) -0. 3565 (0. 00) -0. 3666 (0. 00) -0. 5021 (0. 00) Indpb 1. 1601 (0. 00) 1. 1696 (0. 00) 0. 9401 (0. 00) 1. 0448 (0. 00) 0. 9866 (0. 00) 1. 0956 (0. 00) 0. 8393 (0. 00) 1. 269 (0. 00) 1. 3508 (0. 00) 1. 0963 (0. 00) 1. 0051 (0. 00) 0. 7907 (0. 00) 1. 0234 0. 9481 (0. 00) 1. 0319 (0. 00) 0. 8816 (0. 00) 1. 0553 (0. 00) 1. 0321 (0. 00) Adjpm Losspm 2. 0331 -6. 2544 (0. 00) (0. 00) 3. 2891-11. 9301 (0. 00) (0. 00) 2. 0887 -5. 9880 (0. 00) (0. 00) 3. 0154 -8. 6571 (0. 00) (0. 00) 3. 6912 -6. 4419 (0. 00) (0. 00) 6. 0189 -9. 8553 (0. 00) (0. 00) 2. 0184 -9. 9218 (0. 00) (0. 00) 2. 6023-15. 3872 (0. 00) (0. 00) 1. 9280-10. 8096 (0. 00) (0. 00) 3. 0820-10. 7620 (0. 00) (0. 00) 3. 5272-12. 3146 (0. 00) (0. 00) 1. 6280-13. 7791 (0. 005) (0. 00) 3. 1253 -9. 8989 4. 3329 -9,7318 (0. 00) (0. 00) 4. 0730-13. 0282 (0. 00) (0. 0) 3. 8790-13. 5652 (0. 00) (0. 00) 3. 7902 -7. 1481 (0. 00) (0. 00) 3. 1837-10. 3220 (0. 00) (0. 00) Adjgro 0. 0371 (0. 00) 0. 1147 (0. 00) 0. 0527 (0. 00) 0. 0568 (0. 00) 0. 0883 (0. 00) 0. 0881 (0. 00) 0. 0694 (0. 00) 0. 0576 (0. 00) 0. 0815 (0. 00) 0. 0744 (0. 00) 0. 0781 (0. 00) 0. 0939 (0. 00) 0. 0834 Lev Roe -0. 2245 0. 0402 (0. 00) (0. 00) -0. 1545 0. 0541 (0. 01) (0. 00) -0. 2302 0. 0397 (0. 00) (0. 00) 0. 0585 -0. 2694 (0. 00) (0. 00) -0. 3075 0. 0542 (0. 00 ) (0. 00) 0. 0583 0. 0459 (0. 221) (0. 00) -0. 0675 0. 0666 (0. 083) (0. 00) -0. 0474 0. 0574 (0. 176) (0. 00) -0. 0663 0. 0644 (0. 073) (0. 00) 0. 0683 -0. 1227 (0. 001) (0. 00) 0. 018 0. 0593 (0. 969) (0. 00) 0. 1131 0. 0828 (0. 02) (0. 00) 0. 1650 0. 0521 0. 0735 (0. 00) 0. 0649 (0. 00) 0. 0837 (0. 00) 0. 0674 (0. 00) 0. 0608 (0. 00) Rd 0. 0418 (0. 00) 0. 0627 (0. 00) 0. 0314 (0. 00) 0. 0013 (0. 845) 0. 0053 (0. 528) 0. 0323 (0. 001) 0. 0266 (0. 001) 0. 0111 (0. 122) 0. 0144 (0. 08) -0. 0052 (0. 477) 0. 0203 (0. 007) 0. 0468 (0. 00) 0. 0436 0. 0742 (0. 00) 0. 0147 (0. 133) 0. 0248 (0. 006) 0. 0341 (0. 00) 0. 0282 (0. 00) R-sq Obs 55. 78 832 60. 99 57. 83 59. 15 56. 55 852 319 956 954 52. 97 1019 54. 15 52. 19 940 999 53. 16 1023 54. 88 1041 48. 51 1089 46. 82 1188 44. 96 1349 53. 52 1447 42. 76 1628 43. 00 1723 32. 2 1828 51. 18 19187 (0. 881) (0. 00) (0. 00) (0. 00oo)(0. 00) (0. 00) (0. 00) (0. 00) (0. 00) 0. 0908 0. 0409 (0. 284) (0. 00) 0. 1221 0. 1303 (0. 00) (0. 006) 0. 094 8 0. 1596 (0. 00) (0. 00) 0. 0852 0. 2276 (0. 00) (0. 00) 0. 0805 -0. 0349 (0. 00) (0. 511) 424 s. BHOJRAJAND C. M. C. LEE we rank all the firms each year on the basis of their WEVS(or WPB), and compute the harmonic mean of the actual EVS (or PB) for these firms. ICOMPActual EVS(or PB) ratio for the appressed comparable firms within the industry. This variable is the harmonic mean of the actual EVS (or PB) ratio of the four firms within the industrywith the walking(prenominal) warranted multiple.Essentially, this is the COMP variable with the firms trammel to come from the same industry. In short, we compute five different EVS (or PB) measures for each firm based on alternative methods of selecting comparable firms. IEVS and ISEVS(or, IPB and ISPB) correspond to prior studies that control for industry membership and firm size. The other measures corporate risk, profitability, and growth characteristics beyond industry and size controls. We then examine their relative power in f orecasting future EVS and PB ratios. As an illustration, Appendix C presents selection details for Guidant friendship (GDT), a manufacturing business of medical devices.This appendix illustrates the set of firms in the same two-digit SIC code, which are identified as peers of Guidant based on data as of April 30, 2001. ornament A reports the embellish B reports the adpressed firms based six nighest firms based on WEVS, on WPB. We reviewed this list with a professional analyst who covers this sector. She agreed with most of the selections but questioned the absence of St. Jude Medical Devices (STJ), which she regarded as a natural peer. She agreed with our choices, however, after we discussed the profitability, growth, and risk characteristics of STJ in comparison to those of the firms listed. Table 5 reports the results for a series of forecasting regressions.In card A, the dependent variable is EVSn, and in panel B, the dependent variable is PBn where n = 0, 1, 2, 3, indicat es the number of years into the future. In each case, we regress the future market multiple on various ex ante measures based on alternative definitions of comparable firms. 14 The table values represent the estimated coefficient for each variable averaged across 14 (n= 3) to 17 (n= 0) annual cross-sectional regressions. The bottom row reports the average adjusted r-square of the annual regressions for each model. These results show that the harmonic mean of the industry-matched firms explains 17. 5% (three-year-ahead) to 22. 9% (current year) of the crosssectional variation in future EVSratios.Including the mean EVS ratio from the closest four firms matched on size increases the adjusted r-squaresonly marginally, so that collectively IEVSand ISEVSexplain 18% to 23% of the variation in future EVSratios. These results confirm prior evidence on the usefulness of industry-based comparable firms. However, they also show that 14Even for the current year (n= 0), the warranted multiples a re based on estimated coefficients from the prior years regression. Therefore, the models that involve warranted multiples are all forecasting regressions. TABLE 5 fortune telling Regressions This table provides average estimated coefficients from the following vaticination regressions + EVSi,t+k = at + s j= j, tCji,t + I-i,t ES PBi,t+k = at + j=1 where k =0, 1, 2, 3. In display panel A, the dependent variable is the enterprise-value-to-sales ratio (EVS). I ratio (PB).The expanatory variables are IEVS,the harmonic mean of the industry EVSbased on cur the harmonic mean of the actual EVS for the four closest firms matched on size after controlling for using the coefficients derived from last years estimation regressions and current year accounting and and ICOMP,the harmonic mean of the the actual EVS for the four closest firms matched on WEVS after controlling for industry. The variables for plug-in B are defined analogously, permutation EVSwith P coefficients from annual cross-s ectional regressions. The bottom row reports the average adjusted r-sq Panel A Enterprise-value-to-sales catameniayear EVS 0. 00 Inter 0. 24 0. 06 0. 00 0. 22 IEVS 1. 19 0. 08 -0. 27 -0. 26 1. 02 0. 16 0. 14 0. 16 0. 13 ISEVS COMP 0. 89 0. 16 0. 98 0. 83 WEVS 0. 33 ICOMP r-sq 22. 94 23. 46 54. 71 61. 68 62. 99 Panel B Book-value-to-sales Current year PB 0. 07 -0. 06 -0. 07 Inter 0. 40 0. 5 IPB 1. 04 1. 19 0. 26 -0. 09 -0. 07 0. 07 ISPB 0. 16 0. 11 0. 10 0. 81 0. 35 COMP 0. 77 0. 71 WPB 0. 44 ICOMP r-sq 11. 80 12. 34 35. 21 41. 94 43. 20 One year ahead EVS 0. 01 0. 01 0. 07 0. 23 1. 05 0. 16 -0. 17 -0. 16 0. 14 0. 14 0. 12 0. 12 0. 83 0. 13 0. 80 0. 93 0. 27 21. 24 46. 14 51. 97 53. 23 One year ahead PB 0. 40 0. 15 0. 04 1. 00 0. 38 0. 12 0. 18 0. 14 0. 13 0. 65 0. 29 0. 59 8. 02 19. 91 22. 94 0. 24 1. 19 0. 27 1. 18 Two year ah 0. 0. 25 1. 06 0. 0. 0. 13 0. 20. 75 18. 37 18. 79 40. 0. 46 1. 17 0. 05 0. 12 0. 10 0. 51 0. 40 23. 38 0. 57 1. 16 Two year a 0. 50 0. 0. 96 0. 0. 0. 21 0. 7. 62 5. 01 5. 47 12. 426 S. BHOJRAJAND C. M. C. LEE he valuation accuracy of industry-based EVS ratios leaves much to be desired. In fact, industry-size based comparable firms explain less than 20% of the variation in two-year-aheadEVSratios. The predictive power of the model increases sharply with the inclusion of variables based on the warranted EVSratio (WEVS). average, a model that On includes IEVS,ISEVS,and COMPexplains over 40% of the cross-sectional variation in two-year-ahead EVS ratios. Including WEVSin the model increases the average adjusted r-square on the two-year-aheadregressions to the actual WEVS ratio 45. 5%. Moreover, even after controlling for WEVS, of the closest comparable firms (COMPor ICOMP)is incrementally useful in predicting future EVSratios.It appears that comparable firms selected on the basis of their WEVS adds to the foretelling of future EVSratios even after controlling for WEVS itself. COMPand ICOMPyield similar results. A model that includes IEVS, ISEVS,WEVS, ICOMPexplains between 63. 0% and (current year) and 43. 1% (three-year-ahead) of the variation in future EVS ratios. 5 Panel B reports forecasting regressions for PB. Compared to EVS,a much smaller proportion of the variation in PB is captured by these models. In the current year, the combination of IPB and ISPB explains only 12. 3% of the variation in PB. The inclusion of WPBand ICOMPincreases the adjusted r-square to 43. 2%. In future years, the explanatory power of all the models declines sharply.However, over all forecast horizons, models based on warranted multiples explain more than twice the variation in future PB ratios as compared to the industry-size matched model. The rapid fall in the explanatory power of the PB model is a possible concern with these results. Either PB ratios are difficult to forecast, or our model is missing some key forecasting variables. To shed light on this issue, we report below the serial correlation in annual EVSand PB ratios. Table values in the chart below are average Pearson correlation coefficients between the current years ratio, and the same ratio one, two, or three years later. Average Correlation Coefficient EVS1 EVSO PBO 0. 87 EVS2 0. 79 EVS3 0. 73 PB1 0. 72 PB2 0. 56 PB3 0. 44 These results show that with a one-year lag, EVSis serially correlated at 0. 7, suggesting an r-square of around 76%. With a three-year lag, EVSis serially correlated at 0. 73, suggesting an r-square of 53%. Similarly,with a one-year lag, PB is serially correlated at 0. 72, suggesting an r-square of 52%. With 5 We also conducted year-by-year analysis to examine the stability of these results over time. We find that a model that includes IEVS,ISEVS,WEVS, and ICOMPis highly consistent in predicting future EVSratios. All four variables are incrementally important in predicting future EVSratios in each fore