ࡱ> Root Entryormation9:;<=> FHI$!NDatamentSummaryInformation def;s1Tablej.WordDocumentdd  !"#$%&'()*+,-./<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstRoot Entryormation9:;<=> FHI!NDatamentSummaryInformation def;s1Tablej.WordDocumentdd0  !"#$%&'()*+,-./123456789:u<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstvwxyz{|}~ @&5622 Heading 3 @&622 Heading 4 @&6D@D Heading 5$&d@& CJ22 Heading 6 @&6<A@<Default Paragraph Font6*@6Endnote ReferenceH*22TOC 6 X !22TOC 3 X !22TOC 2 X !..TOC 1 X !, @B,Footer  !,@R,Header  !<&@a<Footnote ReferenceCJEH2@r2 Footnote TextCJ&)@& Page Number..Times12 OJQJkH'8C@8Body Text Indent(U@( Hyperlink>*B*n+\G:y     GGyyy MM\t/tZt       chnology firms. Services such as Morningstar and Value Line categorize firms into various industries, though the categorization can vary across services. Morningstar has a technology category that includes firms such as Cisco and Oracle, but does not include internet firms like Amazon. Value Line has separate categories for computer hardware, software, semiconductors, internet firms and telecommunication firms The Shift to Technology The shift in emphasis towards technology in financial markets can be illustrated in many ways. Look at three indicators. In figure 1.1, note the number of firms that were categorized as technology firms each year from 1993 to 1999.  Source: Bloomberg, Standard and Poor's The number of firms increases almost ten-fold from 1993 to 1999 The growth in the number of firms is matched by the increase in market capitalization of these firms, also shown in Figure 1.1. While the overall market has also gone up during the period, technology stocks represent a larger percentage of the market today than they did five years ago. Figure 1.2shows the percent of the S&P 500 represented by technology stocks:  Source: Standard and Poor's In 1999, technology stocks accounted for almost 30% of the S&P 500, a more than three-fold increase over the proportion six years earlier. The growth of technology firms can also be seen in the explosive growth of the market capitalization of the NASDAQ, an index dominated by technology stocks. Figure 1.3 graphs the NASDAQ from 1990 to 2000, and contrasts it with the S&P 500.  While both indices registered strong increases during the 1990s, the NASDAQ increased at almost twice the rate as the S&P 500. In fact, the effect of technology is probably understated in this graph, because of the rise of technology in the S&P 500 itself. Finally, the growth of technology is not restricted to the United States. Exchanges such as the JASDAQ (for Japan), KASDAQ (for Korea) and EASDAQ (for Europe) mirror the growth of the NASDAQ. In an even more significant development, the conglomerates and manufacturing firms that had conventionally dominated Asian and Latin American markets were displaced by upstarts, powered with technology. In India, for instance, InfoSys, a software firm with less than 2 decades of history, became the largest market capitalization stock in 1999. Old Tech to New Tech While there has been a significant shift to technology in the overall market, there has been an even more dramatic shift in the last few years toward what are called new technology firms. Again, while there is no consensus on what goes into this categorization, new technology firms shared some common features. They were younger, tended to have little revenue when they first come to the market and often reported substantial losses. To compensate, they offered the prospect of explosive growth in the future. The surge in public offerings in these firms coincided with the growth of internet use in homes and businesses, leading many to identify new technology firms with dot.com businesses. The growth of new technology firms can be seen in a number of different measures. While there were no firms categorized as internet companies by Value Line in 1996, there were 304 in that category by 2000. Second, the increase in market value has been even more dramatic. Figure 1.4 graphs the  HYPERLINK mailto:Inter@ctive Inter@ctive Week Internet Index, an index of 50 companies classified as deriving their business from the Internet from its initiation in 1996 to June 2000.  This index, notwithstanding its ten-fold jump over the four-year period, actually understates the increase in market value of internet companies because it does not capture the increase in the number of new internet companies going into the market in each of the quarters. At their peak, these internet companies had a value of $ 1.4 billion in early 2000. Even allowing for the decline in market value that occurred in 2000, the combined market value of internet companies in June 2000 was $682.3 billion. What did these firms have to offer that could have accounted for this extraordinary increase in value? By conventional measures, not much. The combined revenue of internet firms in 1999 was $18.46 billion, about one third of the revenues in 1999 of one old economy firm, General Electric. The combined operating income for internet firms was 6.7 billion in 1999, and only 23 of the 304 firms had positive operating income. In contrast, GE alone had operating income of about $ 10.9 billion in 1999. In summary, then, these were firms with very limited histories, little revenue and large operating losses. Stretching the Valuation Metrics While there are dozens of valuation metrics in existence, there are two that have been widely used over time to measure the value of an investment. One is the price-earnings ratio, the ratio of the market price of a security to its expected earnings, and another is the price to sales ratio, the ratio of the market value of equity in a business to the revenues generated by that business. On both measures, technology firms, and especially new technology firms, stand out relative to the rest of the market. Consider, first, the price earnings ratio. The price earnings ratio for the S&P 500 stood at 33.21 in June 2000, while Cisco traded at 120 times earnings at the same point in time. Figure 1.5 compares the price earnings ratios for three technology sectors (computers, semiconductors and computer software) with the price earnings ratios for three non-technology sectors (automobiles, chemicals and specialty retailers).  The average PE ratios for the technology sectors are much higher than the ratios for non-technology sectors. In fact, the price earnings ratio for the entire S&P 500, an index that, as noted in Figure 1.2, has an increasingly large component of technology stocks that have increased over the last decade from 19.11 in 1990 to 33.21 today. Some, or a large portion, of that increase can be attributed to the technology component. The new technology stocks cannot, for the most part, even be measured on the price earnings ratio metric, since most report negative earnings. To evaluate their values, look at the price to sale ratio. Figure 1.6 summarizes the price to sales ratio for the six sectors listed above, as well as for internet firms.  Technology firms, and especially new technology firms, therefore command much higher multiples of earnings and revenues than other firms. Can the difference be attributed to the much higher growth potential for technology? If so, how high would the growth need to be in these firms to justify these large price premiums? Is there an appropriate assessment being made for the risk associated with this growth? These are the questions that have bedeviled investors and equity research analysts in the last few years. The Implications for Valuation When valuing a firm, you draw on information from three sources. The first is the current financial statements for the firm. You use these to determine how profitable a firms investments are or have been, how much it reinvests back to generate future growth and for all of the inputs that are required in any valuation. The second is the past history of the firm, both in terms of earnings and market prices. A firms earnings and revenue history over time lets us make judgments on how cyclical a firms business has been and how much growth it has shown, while a firms price history can help us measure its risk. Finally, you can look at the firms competitors or peer group to get a measure of how much better or worse a firm is than its competition, and also to estimate key inputs on risk, growth and cash flows. While you would optimally like to have substantial information from all three sources, you may often have to substitute more of one type of information for less of the other, if you have no choice. Thus, the fact that there exists 75 years or more of history on each of the large automakers in the United States compensates for the fact that there are only three of these automakers. In contrast, there may be only five years of information on Abercombie and Fitch, but the firm is in a sector (specialty retailing) where there are more than 200 comparable firms. The ease with which you can obtain industry averages, and the precision of these averages, compensates for the lack of history at the firm. What makes technology firms, and especially new technology firms, different? First, they usually have not been in existence for more than a year or two, leading to a very limited history. Second, their current financial statements reveal very little about the component of their assets expected growth that contributes the most to their value. Third, these firms often represent the first of their kind of business. In many cases, there are no competitors or a peer group against which they can be measured. When valuing these firms, therefore, you may find yourself constrained on all three counts, when it comes to information. How have investors responded to this absence of information? Some have decided that these stocks cannot be valued and should not therefore be held in a portfolio. Their conservatism has cost them dearly as technology stocks powered the overall markets to increasing highs. Others have argued that while these stocks cannot be valued with traditional models, the fault lies in the models. They have come up with new and inventive ways, based upon the limited information available, of justifying the prices paid for them. New Paradigms or Old Principles: A Life Cycle Perspective The value of a firm is based upon its capacity to generate cash flows and the uncertainty associated with these cash flows. Generally speaking, more profitable firms have been valued more highly than less profitable ones. In the case of new technology firms, though, this proposition seems to be turned on its head. At least on the surface, firms that lose money seem to be valued more than firms that make money There seems to be, at least from the outside, one more key difference between technology firms and other firms in the market. Technology firms do not make significant investments in land, buildings or other fixed assets, and seem to derive the bulk of their value from intangible assets. The simplest way to illustrate this divide is by looking at the ratio of market value to book value at both technology and non-technology firms. Like the price earnings and the price to sales ratios, the price to book value ratio at technology firms is much higher than it is for other firms. Figure 1.7 compares the price to book value ratio for technology sectors to that of non-technology sectors:  The negative earnings and the presence of intangible assets is used by analysts as a rationale for abandoning traditional valuation models and developing new ways that can be used to justify investing in technology firms. For instance, internet companies in their infancy were compared based upon their value per site visitor, computed by dividing the market value of a firm by the number of viewers to their web site. This search for new paradigms is misguided. The problem with technology firms, in general, and new technology firms, in particular, is not that they lose money, have no history or have substantial intangible assets. It is that they make their initial public offerings far earlier in their life cycles than firms have in the past, and often have to be valued before they have an established market for their product. In fact, in some cases, the firms being valued have an interesting idea that could be commercial but has not been tested yet. The problem, however, is not a conceptual problem but one of estimation. The value of a firm is still the present value of the expected cash flows from its assets, but those cash flows are likely to be much more difficult to estimate. Figure 1.8offers a view of the life cycle of the firm and how the availability of information and the source of value changes over that life cycle: Start-up: This represents the initial stage after a business has been formed. The product is generally still untested and does not have an established market. The firm has little in terms of current operations, no operating history and no comparable firms. The value of this firm rests entirely on its future growth potential. Valuation poses the most challenges at this firm, since there is little useful information to go on. The inputs have to be estimated and are likely to have considerable error associated with them. Expansion: Once a firm succeeds in attracting customers and establishing a presence in the market, its revenues increase rapidly, though it still might be reporting losses. The current operations of the firm provide useful clues on pricing, margins and expected growth, but current margins cannot be projected into the future. The operating history of the firm is still limited, and shows large changes from period to period. Other firms generally are in operation, but usually are at the same stage of growth as the firm being valued. Most of the value for this firm also comes from its expected growth. Valuation becomes a little simpler at this stage, but the information is still limited and unreliable, and the inputs to the valuation model are likely to be shifting substantially over time. High Growth: While the firms revenues are growing rapidly at this stage, earnings are likely to lag behind revenues. At this stage, both the current operations and operation history of the firm contain information that can be used in valuing the firm. The number of comparable firms is generally be highest at this stage, and these firms are more diverse in where they are in the life cycle, ranging from small, high growth competitors to larger, lower growth competitors. The existing assets of this firm have significant value, but the larger proportion of value still comes from future growth. There is more information available at this stage, and the estimation of inputs becomes more straightforward. Mature Growth: As growth starts leveling off, firms generally find two phenomena occurring. The earnings and cash flows continues to increase rapidly, reflecting past investments, and the need to invest in new projects declines. At this stage in the process, the firm has current operations that are reflective of the future, an operating history that provides substantial information about the firms markets and a large number of comparable firms at the same stage in the life cycle. Existing assets contribute as much or more to firm value than expected growth, and the inputs to the valuation are likely to be stable. Decline: The last stage in this life cycle is decline. Firms in this stage find both revenues and earnings starting to decline, as their businesses mature and new competitors overtake them. Existing investments are likely to continue to produce cash flows, albeit at a declining pace, and the firm has little need for new investments. Thus, the value of the firm depends entirely on existing assets. While the number of comparable firms tends to become smaller at this stage, they are all likely to be either in mature growth or decline as well. Valuation is easiest at this stage. Is valuation easier in the last stage than in the first? Generally, yes. Are the principles that drive valuation different at each stage? Probably not. In fact, valuation is clearly more of a challenge in the earlier stages in a life cycle, and estimates of value are much more likely to contain errors for start-up or high growth firms, the payoff to valuation is also likely to be highest with these firms for two reasons. The first is that the absence of information scares many analysts away, and analysts who persist and end up with a valuation, no matter how imprecise, are likely to be rewarded. The second is that these are the firms that are most likely to be coming to the market in the form of initial public offerings and new issues, and need estimates of value.  Illustrative Examples The estimation issues and valuation challenges are different for firms at different stages in the life cycle. Consider five technology firms that span the life cycle, from idea or start-up to mature growth. Motorola, a company that started off manufacturing televisions and then found success making semiconductors is one example. In recent years, Motorola has found success in telecommunications with its cellular phone venture, though it has had its share of disappointing ventures (such as Iridium). As technology firms go, Motorola is an old firm that is still viewed as having growth potential. In early 2000, Cisco, for a brief period, became the largest market capitalization firm in the world, an astonishing feat given its short history. In many ways, Cisco is the growth firm that young start-ups would like to emulate, and, as such, is an example of a high growth firm. Amazon.com became a symbol for the new technology firms, both because of its visibility and because it operates a business that is easy to understand it sells books. Are the drivers of value different for a dot.com than they are for a brick and mortar firm? To answer this question you will value Amazon as a firm that is in rapid expansion. Ariba, is also a new-technology/internet firm that offers business solutions to other businesses. There is more of a technology component to Ariba than there is to Amazon, and valuing it allows you to examine whether firms that sell to other businesses (b2b) are different, from a valuation perspective, than firms that sell to the final consumer. It is also a younger firm than Amazon, and has barely made the transition form the idea stage to producing revenues. As a final example, you look at Redifff.com, an initial public offering at the time this book was written. Rediff.com is a portal serving the Indian market that chose to go public on the NASDAQ. Coverage of this firm is intended to illustrate several points. The valuation of a firm very early in its life cycle, the effects of country risk on value and the consequences of having limited historical information are all examined in the valuation of Rediff.com. Summary Technology stocks account for a larger percent of the market capitalization of stocks than ever, mirroring the increasing importance of technology to the economy. As more and more technology firms get listed on financial markets, often at very early stages in their life cycles, traditional valuation methods and metrics often seem ill suited to them. While the estimation challenges are different for these firms, eyou will discover through this book that the fundamentals of valuation do not and should not change when you value technology firms.  The six firms were Cisco, Microsoft, Oracle, Intel, IBM and Lucent. Of these only IBM and Intel had were publicly traded firms in 1975. Microsoft went public in 1986, Oracle in 1987 and Cisco in 1990. Lucent was spun off by AT&T in 1996.  The Bloomberg categorization of technology firms is used to arrive at these numbers.  In other words, a large portion of the increase in the S&P 500 can be attributed to the growth in market value of technology stocks like Microsoft and Cisco.  The Value Line categorization of internet firms is used to arrive at this value.  General Electric reported revenues of $51.5 billion in 1999.  The big three auto makers are GM, Chrysler and Ford. In fact, with the acquisition of Chrysler, only two are left. PAGE  PAGE 17  )  wx"#ABCNO "#n#|#&&((h++i,,--//:6jtWCJOJQJUmHjPCJOJQJUmH>*j0CJOJQJUmH0Jj/U jUjpCJOJQJUmHjCJH*OJQJUmHCJOJQJmHjCJOJQJUmH * j0JU5CJ2         G/!$R)053: CKMMT\     r )E  o rt[GIe1/ !!!!E"#$$&&*,]/h11@35558;f<? CE=HMMMMxNPQ&STWWYYY\\!<!!!!!!!!!!*9!!!!*9!!!!*9!!!!!*9!!!!!!*9!!!!!!*9!! !!!!!!!!*9! ! !! ! ! !!!!!!!!!!! !!!!!!! o &*,]/h158;f<? CE=HJMMMMMxNPQ&STWWYYY\\\\\&&&&h1h1h1 h1 h1 h1 h1 h1h1`h1@h1h1h1 M M M M VV :/3Dd?SGOS@\0256789:\14<UnknownAswath Damodaran Crocker Liu Marissa RyanStern School of BusinessValued Gateway 2000 CustomerSharon Gadayev Champa ChozomMS OFFICE WIN95WILLIAM H. GREENE Avijit Ghosh PC OperationsStern Mike UretskyDiane Belleville David BackusEric and Amy Kolchinsky Stern NYUQueen Elizabeth Ramirez Xavier Martin Ranjay Gulati kim lampaPreferred Customer Alan ShapirogdalyElliot M. BergerProf. E GilmanElaine LengyelSuzette LemsonFelicia ShutterVictor Clark MullinsShaaron M. GomesEditors Gary Simon Norman WhiteL & N JankovicNT Workstation James Cheng Paola DubiniRete SDA Bocconi Davide ContiCustomerURSProf. Giacomo De LaurentisDaniela FaccioAndrea LorenzoniInformation TechnologyPatrizia Trivellato Adam SosinskyPaul, Mel, Marilyn, and Dave Bill Starbuck Paul B. BrownMike Kao Russ HallHedi M. Bergsohn Hedi BergsohnRizzo, PatrickDLJ Administratorisadayan\X !!8@0(  B S  ? j u 7+A+++++++&S+SSSVVWWYZZ\\,4go" ' P V C K LU]eGOzS[$$L%M%X,\,:3?36688H<O<AFPFKKQRRSSSY[\x\\\\Aswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4MaciDd\5|$xx<  C ABMTh0X)Dfd0T!Th0Xvܠʩ'pXa\ 4[Zxo\Ɵsw;Fk҄f+B67эn,]FjYݽfƵ-AR7i&_"*D$(@ ~+`@, IY43\sg.vaX3}NZ]Kٿ<#8R3.ipkmn}KM\ʍ-ws4S4O4W9]>ҮWx:"~lg\^:okth>_Xwffvmh<1/c105{9m]:?#Ɨs/ߐ.欄91vSƜ7m;fӸ[oLqs y[jm[3ݦ>1y;ovޞys}1;W2qӾ_1ܿn<\63ΓhTVbtWznhM&nO?g"+753'=xlϓSSco9nvYm2¬EE>-ֶlؽllƝп5}0s\mwm>p׶?8J3v+㿚r6ģ9l}x񪿣]+~yF3W)gy->X($bjPPPPPP>>>>>>>IOD$>IOX8>cX8Du9pԓԓԓԓԓ˟BA[zCJ/^f^RzãI/H)ᨤ?^pԓԓԓԓԓRzCJ/H)^RzCJ/H)!?^s4ԓԓԓԓԓRzCJ/H)!?^$=)!?KzCJ/HSOROROROROJ/H)!?^RzCJ/H)!?^RzCߴ @z @? @? @? @=+NOgfQqdD{{>3#Ɍ$3H2#Ɍ$3H2#ɌٳSč8:*}}bo/ql/ql/-`]|XKt-%ѽ=kauQc6\kvR&tS|AiI`E\e6B,hf(- LIt /5PoB ŬW<ܖn/;sJW[a:JX. Uhʎ}=umU=QwvkoSM=kP_qq>8laVjeV7Bzw&3{әo2٩'NNZo#*Ѩŕy~^y~^+_o n0@'_XX@EvN v:oIUmuuX6T ~ݺDٛ3ƑЗ_fhb3 kǯs8,}?1X}OjE\[~״RyC4MM{maY.ĴHk=ZKD;?N;=-5hE7x>v.(\ZV+c|Z\?Wiڞ ]{z/mʯuh[r͊fEU[E!͐׎vTD{IDkϻ>Sk&G}$)e56YE{]EX4WPvbJF%܁ѰW̽{JkVփTZYS|T_+Xr}qZY7鴒o!ыF/0V[[iڢ[wUjQe"Ki3>)u>:F蔚O^*:};R8FEAmhE!͐׎v\.Z]]:"興?JDKDKDHDHD$"jHD<"1+1+Q "}{{3r'Gtwo!Bܯ|ۻ*b|v!m*^B,qSj!rA,8uo; (.D]bo]"lP~ϧnSCrK^kr8/<<دg&oP+@}pe횵wWvlmʎg ʹzf>M3߇AO^6}yŎ|CGw.KrqvW-طC5<||^wvOs?u1|qeJI1@$lbO(ٔlo67uz]~.^_ˏcq,?DZ8H~ɏ"Q$?G|v"ztI$}>)_4ʇ)_pT!+Raʇ|HʇW|Hʇ|*ʇ|HʇO'I|CW>|CW>|Wʇ|Hʇ|Hʇ|Hʇ|Hʇ|H\ }>IO'+R!+R!+R!+RcWʇg)_gW>|CW>NO'Iʇ|Hʇ|Hʇ|Hʇ|Hʇ|Hʇ|*_)_𿴕|(@P>|(@P>|(@P>|(@P>|峾|UqeE\ZYqfFTĉ4gV$YdEIV$YdEIV$YQ\_UqeE\ZYqfFTĉ e~ٸ_6e~ٸ_6e~3)o_ȷd6JhľZ7AhX fMp,o_m6[6JEݞ͑F'ŞKjk(%a1=Kضaudvz*hݳ{nJLx4ܦiĶ~~ou(a~$aw_;mpP?.o'>| H߬ZBu}'c~͡8^FY*ޟӅ^M[{I]sGHnc[n38n0CmǣMyOz\'}$JEw wѼå m am/?%whN[t"14 4[ZxMh\Uy3Ӵi)ņjh˴j ZBeHsJC % o5MP"\Yv!H-40Zxyݹ3{97Lۈ‡MƄl֎{"Văv[sfp)h=Me>Q` XMKNgډsaLS4N@h jiOt1,,`35V#ȴ19촲RݥB[vڲN;miܛoO'4rGޤ'v]uouK.zA]=I*==;S - &A,0)A,0)5A,0|[ AM[X-Loah 2FX`$0@ L?A,0&H EB ە6eqO\ez[T%'s 4`quZ[[UZYY%Z\\iQRtZNkyuu Bc:6HKc<8o)HljTt}|yzGS nǏ9پZҷ`#QdHʽ8_|)cn6&_o&ŌuLw͊7&ĸF5rEN%߾f+D]R䬈V+)$uVwYDA-=ȣӹsP~JyZu{kσuτ}='<ϕo0VoDd\5|$xx<  C ABΎa N!\Efd0TΎa N!\EpB!b|$4[Zx_hϝ啥\XR&\#yCFj ӒCh Ѵ?ىZZj$"6[hi7'\L`ySYCbZ@)$}P,iܱV;ik{̙{ϮvgKa-ч5fc'vWхBշs[oYKOq4NLP JX mHCv̟혊y4bC5s6^ UW:NvŠ9xuŪ+^]WV-z5kլWqvf7vXgs]K'M۞ O_3ꡦus;bRI9lHa<G)j+##g#U3Ys>ba0ȹG5c:g?]\Ô_>8ݟڶ;F֌m `6]3gFkrc}Ju-~? Ix:T[O[6R]žp6ǜgou_D89ou_{0~e\pX6R]+:baͯm+Ne̋8mwxrzTuчOfo\n ^<;S#mҿŷ}5*wXbU6YK_K_K_K_K_K_I_I_I_I_I_Iy.}KY&}IegY&}Ion맄^ʇ+Rzý+RzCJ|"!W>ʇg^+RzYI|H)'''''W>ʇ^+RzW)!W>ʇ^+RzCJ|H)!l'''''W>ʇ^+RzCJ|H)sW{+RzCJ|xʇ^+SOROROROROJ|H)!W>ʇ^+RzCJ|H)!W>|^+RzC¿|(@P>|(@P>|(@P>|(@P>|峼|˗Ņq~^''aq`ș$I:t$Hґ#IG$5eqiI|Y<^\XiqrR^6ezٸ^6ezٸ^6mfv_Ɲvqۈ5ۮc]\obӮaMޭ6Ʀ{֑XcGXo{؎·ɶP|kkaߪZmp UvиjZ|%D;g9-Gv{?n&i6JZ>7~79n޵6ٍ+?1]fݵ { FPgň3P1> ےZ!O%*ɟd۞b9qY<(~eSHt ~5,iG{{nmxؔk?lpB!b|$4[ZTx_hϹ3ZKwcV]8IDH%*Y[ u& YVMN]jK%Kpa.edhMC@!:<ԭ=ܳZ>993;L/7uQK+A=Z}#˛Ϗ'aN ڃMŘD!z*1/)gڌ'RQG(gF03C*>3_lL٘^eeȲ[n)k*k*k(k(V6LTH'Q*˧9 ;s͕Ցcn?/{YJޅ PQ$V+b*Y;n6&SCzr첲|e1ecz*G/J[vK-eMeMe e eʦՕ)?omr~?GĶ|ƿ)~뼟܄Ķ3~?gW -1[yHK,k`,wRb;V" YޯQ(uV:˖Py;WwZRֹPIYvgyU;JͲyTpf f vyes?pYoo`YP}&qe1\y,,)pu\YvWx~].ڏ"ˆYޯ`R٩J9ء,w~)7p!ɲSNH}{L3-F{ios7O]aO\<}?Mԭ+}~uϣq=T{7WR=hԶ+ 짾N3I[n^nx'ϵtRnnmrg.:*ngvU*ӣѸO\?]:ί'_iStb=7i\d037EmbLH DoIJ˽ ymp(|ȃHay:SCC)!IH>m(|#)vаӴ1dpmó yȇ<N  tDA8)ȇ<8@>Ah p(|ȃx!Bhf$V!  CC     VEG"Y3yAsQ6;_X:UIʉl%kԌj9IDnؕЫV21Zy2vAwQkκQnw9}{SWPϰYs n9[.zڕ9+m|$~ KNy'ls`k,Něe.=ႾfY\_[R2DyK  Inter@ctiveyK &mailto:Inter@ctiveG Dd\5|$xx<  C AB0j0R0fd0T0j0RӤ&R $$k<4 4[Z>xmTsٝ7h(";Z%*F[+"V]Eh$iJD&uY6&Kc+h ;;;=?w2 +sݸ9{o34R7rG^꠩%Fsk$w~?~GfGx{dlvʘ_ŒH_9+u5U*~|QQGq;jQsMC٭.g\h?S_ig;ѹ)ĺ|(J!q-NXm(js/8^J85&~4 5pz:}:?w9(˝N]\o=f_57B]."~~Uk_CƯpǢ}2n5&%qzK_a}=XE'noQ[ jc}4>a-/[[IyuՏe$nYoQG)ŹbX4%%qz>df&s9f5kՙ_(37`eY]"%qz=W^W~a~Iܲޢw̽槬ϛk9/[[n,7`}ú^/[[wyl7Xj^`n=/[[RIvONǢ_EqS^u4:d5bMz ϋ.> ~qܲޢ{hw?r̺=v8nYoQ܇ meLYnqzƽ]ݬ{qyۨ/4b;ͣh xt-. n0n;<-ݴ~u~#Gͯο^6ǺΧ93ZjQ;^Vo#VM$84FՎ6E      qqqqqqc1c1c1c1c1c1QQQQQQP'~݊_TEG~ GQQQ?# ?# ?#WO?# ?# ?#^E/ ?# ?# ?# ?# ?#_G~DG~DG~DG~DG~DG~DG~DG~DG~DG~D/FE/ ?# ?# ?# ?# ?# ?# ?# ?!?~GG~DG~DG~,QQ.~Q_T#?#?#?d!?DC!?DC!?DC!?DC!?DC!?DC!?DC!?DC!?DOWs0A};[@W.] ;:cg(*E%DQT"JDQ(*9Cݱe t ҥйs3f&+ܯlr&+ܯlr&+[1H|kԴ1+\}NJ7bf颱,CUviJIc^ ~fp5Θ?La8QHN B|bՏp,f!-&9E.G4~/E$*cvѷM;=|/?KQ'Se"Igifmz[2>!M5=LJw.CX75Hc)B/MimZեn߆)vME27Ym hAQ@R<6ݹiMzmzd*<ۄ"{7tҘҘҘҘҘҘX+v f?SW%- nap59_vña`'(܍0&/y4K[ ݲ4ƲO!KY5ؒW]ߚ=T<`޲f1MbR^*|3tg]̸uRLLLLLLl󔯛Vzןt=5 {M#TO1F l*8m`nal b!2OՃ֐[?f= v2z*R^)(+Yտ1Ĕ&uߴ'~M5FV'-ӕ.4iDM)Mubi\"Im]jߥ$.f~ߥk>Œ..ma;P)(ˉgvﲀmڌL666666Ig~aZiERgf(q9l7^VwY^'L9G.&w9lܬ&Ww z5TA,UX3;/+ 3̕LyLyLyLyLyLyLyK`XeN̤1_ N SE\dy̸lnOde_.1Qn벀n4fÔ*41mfU/ja<[)2LI@lSaJ]J]J]J]J]J]J]д#BTJji1[gҧ[n-bh2222222$z-ix2V+pJc =ը>߲dNqY@n#;W4ܔܔܔܔܔܔ&19jZiJ`1v[6z?2H_^iiߥҗҗҗҗҗҗW} -ָuºYn{e]bxj3%2%2%2%2%2%2%ʻ/K~oif$f*k3g\RKhQnf}D*͔͔͔͔͔͔*n1ު _Nfsu]9D8,\7`V؁Y]+LYkb]]]]]]]w`z+Mql.r1 bփYHiOo`*))))))Uރ1KDɕ^fQ+y;q]P˯֡ :#}?ljZy}{0Slc6ռyOwQ)mֹjsg))))))ݑT鮄R }H Ј1c$s+2s 2^m!BcA;">E%p.p[8V 2P3şl-1d,}S:h*P6&&R $$k<4[Zxmlǟg%g'!hL BA@)!$065MyK F j*H"D$e'T_1*/"P̎L |韙o?^3M"Jq#@ǿD-͍[SUcVIf2P6ap4;LD9P^"jгeKӿޕXhoVaQ+׋yƛga0i/4^h.uxOpKyl߾])JjO{Qўxi/w9($ow]x7x7LיQ5^hx]2^ک籋o6ovo7;dC2ސ>4އ6ްY{QMxR`x+x6 {x413GxwxE~,kt.3b-6޽ƻxx5و>q%*F7+0w)Oׄx;W>Z[*O׊^gkEo5OU#kEo _<]+zjZ?<]+zw>Z{_WOt蝥F5zVPtuR΃kEogͺM-$F|(ˀ.u$F~-4v W`-?#x]=$O|Ȭ{I\M,1ĕeƬ+y+ɭ\i],T|Ь[˱bcQ.7)W.,o32+_f뼝;UYn7N'Y\a,Ϛn>R,?6ڼ+O/˓fRo #t,uJz\^N"˕f][!%g&.MGB޿I؋*֗Aԭ'{B=#{+#ԵvҬ+\yͬ[6l-m^fkWwiRPڊå6^@'Q>1}>}q^0 _rhv&EW|Y./},+|Z {嫱Z^k>g<]1푍"+fh7Kwnqu?WubI ,ލ D"U/rI\#b8PbC!@> ‡B(|;S9P !k I\~!fMa!l:[B(| !lB(|;? Bc7BC$zXPB(|*PaP6@C!@>ȈވW*wPq>BC8  !tB(|>BCX)ҐI _>Dʕ1RP>BChPB(|@S 3$Gŗ/m*ޒ'jm%B"m .R&.b0!'J qi.wP_~'8tB=2h 4*|ӛѩStaڿ?ROO-[,YBs̡B {8C Yz$_rY|LLA$(%tℛaNYl+)-oqIr+e۩h/e qW Lkr#J`2{q.`e+ʉљg"LT[ЂQ2ZH_n{A]=-Z.b[Nl?eQͰDq/N 5Q ߓռ^xxxxmzRVYpt''x>Ek`AEk4+ܲ1eb&~ۂ卒>Mj}ԟ,$k#7c:96wDt}G$ ѝFܓ$oH>EU|%b= Du:W'}~‹TWHO1ѧ)eEVڢ%ע`nʚu{%c'@dzLNAz, >)6*}cEqFuD=nLS*yEE"4K$^Z$ [I|wďAXLT)3i_HHHHlxRF@@X"h EsgӦU<3Ԉi) )hP:k\o͖u^E:9͹yr.a'7[tnUt.*:OTM;6vL"K5#ջIvtvtvtF"iEh*:mjo6N^Xl[P;ANɹv.&5G ymG7tZϫ=$&zHu. <#U ;Q/7`YVQD:ҡ,y[o͏=H1ڦNͱssMj_?̐wDY"iU/(guԧ GSj7d~}ƻ q( ڑؑؑzP[[1bvQutCp>RXxߪp5:V3㏉98n;n;n;n fkbE>Ηd|,\f~2JD#q8^XXXXa=tv=3ѳeG/܃ 例߮q7'|r>j>+Yǿ >F~̤/hg DF6Ȉccc8Q5Uͯc̏~y>I>T3gmbbbqQs|\;<>/8 >5#׻.r?a̱e}Q@D9]Ñۑۑ{T>#c~x9޺)T#q,~c7,ڱررP?1'!B&z,5?{?wj91c####̏;W^zcc//IFι؈8Q1Ṵc ~ /)dcccc|rjlz2硎)c' B_skGhGhGhsB[9 mm}q@Ej9{IqɎ܎܎܎9 z6}Oikk:eޫ5@'Τ8;;;gUm5e}ʚT^ruG YÒDd\5|$xx<  C AB @rCѤQQfd0T@rCѤQ&5C9pIB ;Y4[Z{xkAlSi4)B+2I$VbU#$n6 JA/PЃ=s{*xf'դ!Nxfg޷ C_nҘQ;}Ihx>vh+i$FFY4i93`[5" * DGp.+XRm`^9;ho+ij^ZjkM+gL7Z*,|56\[>ӤAЩ{V4 a Q8=>\Hf'Uג3[r|`z#btSfu*V/s _}U͓k>Ou_߁4ooh}r z+u5 .Q/sMMr ׷/FsV;GUUS=tg(yɕmҵ<.X_51[&5C9pIB ;Y4[ZxKAǟgMraХZ!Y%ttuoO /z0f7(z%/0 Jffo43gggȭ@hBu̷G\cҊbCPbF + &#OwG1I1Z?ŜqFh XeR.vTB}Ov؂!VǒĒ81Nl| >++++3~dDZ\ !|>_|>ȗ|+r`lgeu<ढlIp\T$:'%וfׂ0b"p _)4oS(F\U|Ա-[ $$ƉqbA51I,A,{65ܻ5\&Ll1}Ym KuK~|jQڭž2WicNx՞|Jּ 画Zmx>|ԌnYkifyH;mAQjQ~FI. ]wk-ӊEB"! =^EH"9%Aicؼ93az&[S_} HYwy]]/aj.}A!eLikvN廈MXιi07gR;0!bl{j)K |֣:zT謳ҘάBfjޡ^-%;HE/b](!A' Zy O1+y)I?ȞT^7q|j&P.ACcϊ{/q;Mk}2j|V&h_h2~o*m564o}>\_&gf (# ɶOHr~u&͜e3oOia,- NMs3Mz#Usw)kcsKB f@z }2R 4[ZxKQϹc ah{(`17MYQ]UDA|ZP }7njB;3g'hs{?hӄjgձXb bZk1D SdJDB8{/Dd:%:ȉW|4A1L 7 fG?ȦDiE ƉqbM*UbEbEb1XV*i?io85mSMZ䑿&ٮ֤ѭ ڂ>+D;#N7M>rZlw>ҡbsYZE"Й+Xɛx4Ft3 ^}F'sCDԡO5̓ .C"{!\^A|jAP3kxz9"q=دhczHeInVfq #YQTV8k 1Dd\5|$xx<  C ABa.^wm M˧`^fd0TXa.^wm M˧{DHccW(4[ZxOA,P~EIb̀ )ŔR$5ume[C4$#1ɘx','{o Ӽ~?3wMwèAQ:pGOB&rqq~%xV /:@DT=R1E2GršXӎ^ E+.((S)@}ttȴ͔A0{>Wx4tb{N+wvdzYc'|ak,R cԨr5|.bc4{*Bp BĘ{soF_)_fDr's}eQýe*qo\oh1š5"U Ms}lpoc#s6m|ΞWKZGߐIvmNdƢ Bk^FGD~BO q7Oz|3혵Œ90ٹ3{3v}i: Fvd^9I é{%7oOos?Mrv#V%naxƱ$D Q&,1E8a.A`9Y{'C.qY 2HbRVY͒ĒbbFFBB,C,C,Nϑ~ ֊u{o\veak2׊uuYo {q%K&~e56 [ Y8*E5؄B mR,rYx\e, Y8!n讐Ud)Q! e,ŦIXpJhgw {22$$tYXXXXXXX֙Vq !tmqJl=bctVǨwwإ ])}kslCR y1;eaQ a]6;+y4M3s}\w]s9꼌y윶DrO+ksVf@ho#"GQ(q 0ڀe}w-Y~ߡ[y3yzc.2l z2|I(cthM;ҭMSkHQ5-h鸤`jKZ>ESZ3h?OI[v=w.K[k ?h$ PE"iaКOĘrOv: {}Hr xMZz^z-7fz4,:`ϓޡ^vzנi7~6E=ͧWNIMҮ-Em k(N)O*zj%V MWT[Z%h+_/PEB{fӸBI ^vV-K(FyR.BY_U"Zдc!NJd.m1DƟ'Q[%^#XyQ}WJ\۾2Vwrn>DЛ/;gTCtbģKlfgż'q3' 5}?!U{ 6mp=#L[Pޔ2i1r/ʉF3޲L9ZfY&\Q ":) [ K, hAs`ǥ/vLsQ%2j:dl[>yN o1~_M4پ4|N1ְ)!o4@a88RAr2nB!`Yr+QN)믁A~ 6*IB]ā GV}b6F2Q.Ԏ]l,'~,gYzvȍrr"SUڲ'`c +蹔LJ4KAw)wtF4~}LyFYVE/X,*ߟ䝒olGuyNT6 USv^5y{VӤ*KA/19\q~Y| 8]`+釉5; OхefMHU>t gPȰdG4@W ~Nʳ2l"X^\z wT{qG)e= ULE/WVk$SzyWxidmv)H^%*G T˓Fn/l9F6eo6hW-r2SP?$/ a'#~P x,@[]%O|KI lR7빁Bwa: Ib<:K`C%dLə*֢\zv?XհzVc>[/gϯ`_sPtɬ,OZ͓+mҊ̿0˵ 3d-zU\ u4&_xV]lU>gҖ_ "M(DJH "h1Ty213ܙnDDIyS҄oD$"1Cğ3wֺLz{ιs: @KiB7|O-(mU@Osssck9iBk#i1CN:m] a.TB}Pwc^InҸiywvIvp6>0njPѢSHմQ|Nc_?PO/}*rAwʃ}[舽IAӋ]a<ΦȂviutJJɒHs$7%u)Kg:J^'a"񓾳v8qPj^B^'^=68[mwz|clCwڰ9vӷ\ p̌ g{g+Ì'R[p~ _5p :al`/~ &~6 Xц+p=|eXe 'qg.OUK%| _$Yr,9 w}B;56A؃  k5Ț^ϓ%[6nD4^F5fxNf\ʰD W1HʛndzM9eyEq~dV8{4Q7~>Ԧ)s(i-p>GXngC,8""g796Az$p鑘JTMF{/3'MU^?zHLo䭀xƶBj~bTWVͰ'uM͋g9gKe:4w+qOVx9'p>g5-F1-F)ϓÜWw#(CĖk^4MAW6>y'xIJf2lj^P}.GƻeKA},\,z"NďD1z($PI(ܮW<Hm E^H`|ƪ&5egA/8%AkrUf=qB2fW6zrr)f%қb~SsogyqTeݢ>bɹ!UIWi^Ԏ@] d.&Yw,7o^FǟRƒK> ?"?S?^?_?g?o?z????? CE=HJxNPPQQQQQ&STUUU"UVVVV^WWWWWWWgYYY\\\\\\\@@A@A @Av@@A|Ab>@@p>@AzAY@AY@AzAZ@@Z@A|@&k@A|A}A}@w@@}@A`~@}@A~@Ab~A~AAA$A:A<ALA\ArAA2@@@@@@@@ @@ @@@@ A @A@AVAVA@<@@>@@@A@Aҫ@Aܫ@Aޫ@A@AA.A4A6A6AAڇAA@*@@,@@~@@@@@@j@@l@A@@@@@@GTimes New Roman5Symbol3 Arial9New York3Times"AsII&pG  YI%!+>0dZUCh16 PBV Multiples Russ HallAswath Damodaran`abcdefghijklmnopqrstvwxyz{|SummaryInformation( DocumentSummaryInformation8XCompObjX0Tablez [>@>Normal $dCJOJQJkH'mH 2@2 Heading 1 @&544 Heading 2 @&5622 Heading 3 @&622 Heading 4 @&6D@D Heading 5$&d@& CJ22 Heading 6 @&6<A@<Default Paragraph Font6*@6Endnote ReferenceH*22TOC 6 X !22TOC 3 X !22TOC 2 X !..TOC 1 X !, @B,Footer  !,@R,Header  !<&@a<Footnote ReferenceCJEH2@r2 Footnote TextCJ&)@& Page Number..Times1C$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI& C$EƀeI& R S W  (((<)?)@)f1g178w88;;;f<r>> ?"?S?^?_?g?o?z????? CE=HJxNPPQQQQQ&STVlXXX[[[[[[[P@Q@Q @QvP@Q|g 4 @&6D@D Heading 5$&d@& CJ22 Heading 6 @&6<A@<Default Paragraph Font6*@6Endnote ReferenceH*22TOC 6 X !22TOC 3 X !22TOC 2 X !..TOC 1 X !, @B,Footer  !,@R,Header  !<&@a<Footnote ReferenceCJEH2@r2 Footnote TextCJ&)@& Page Number..Times12 OJQJkH'8C@8Body Text Indent(U@( Hyperlink>*B*n+[G:y     GGyyy MM[t/tZt                 G/!$R)05: CKMMT[   B  r )E  o rt[GIe1/ !!!!E"#$$&&*,]/h11@35558;f<? CE=HMMMMxNPQ&STVVXXXY;ZZ.[m[[[[Qb>@Pp>@QzQY@QY@QzQZ@PZ@Q|P&k@Q|Q}Q}Pw@P}@Q`~P}@Q~@Qb~Q~QQQ$Q:Q<QLQ\QrQQ2P@P@P@P@ P@ P@P@ Q @Q@QVQVQP<@P>@P@P@P,@P~@P@P@Pj@Pl@QP@P@P@GTimes New Roman5Symbol3 Arial9New York3Times"AsIgI&pG YI%!+>0dZ7Ch16 PBV Multiples Russ HallAswath Damodaran [>@>Normal $dCJOJQJkH'mH 2@2 Heading 1 @&544 Heading 2 FMicrosoft Word DocumentNB6WWord.Document.8 ՜.+,D՜.+,< hp  ' Stern Schooler%Z: Ch16 Title(RZ _PID_GUID _PID_HLINKS'AN{3BD9BF87-B757-1168-B579-B0CD5A817F55}A`bmailto:Inter@ctivex Oh+'0  4 @ L Xdlt|'Ch16ofPBV Multipleso Russ HallleussNormallAswath Damodaranrd9waMicrosoft Word 8.0d@`4<@h Q@3!@h! YISummaryInformation( DocumentSummaryInformation8XCompObjX0TableXY In addition, there is the very real possibility that Rediff could make the shift into other businesses in the near future, such as online retailing, especially if it succeeds in its initial push to raise capital and expand its presence in the market.18 0JmHHhI&Hc |\jbjbSS 11Y]XYz](] ___4.adiiihnii<e$pp"qqqqqqe{g{g{g{g{g{g{,~{Q _qqqqq{t__qqitttq_q_qe{_v`^^__qe{ttyVz__e{iεetir~Y{ CHAPTER 1 THE DARK SIDE OF VALUATION In 1990, the ten largest firms, in terms of market capitalization, in the world were industrial and natural resource giants that had been in existence for much of the century. By January 2000, the two firms at the top of the list were Cisco and Microsoft, two technology firms that had barely registered a blip on the scale ten years prior. In fact, six of the ten largest firms, in terms of market capitalization, at the beginning of 2000 were technology firms, and amazingly, four of the six had been in existence for 25 years or less. In an illustration of the speeding up of the life cycle, Microsoft, in existence only since 1977, was considered an old technology firm in 2000. The new technology firms dominating financial markets were the companies that use the internet to deliver products and services. The fact that these firms had little in revenues and large operating losses had not deterred investors from bidding up their stock prices and making them worth billions of dollars. In the eyes of some, the high market valuations commanded by technology stocks, relative to other stocks, were the result of collective irrationality on the part of these investors, and were not indicative of the underlying value of these firms. In the eyes of others, these valuations were reasonable indicators that the future belongs to these internet interlopers. In either case, traditional valuation models seemed ill suited for these firms that best represented the new economy. Defining a Technology Firm What is a technology firm? The line is increasingly blurred as more and more firms use technology to deliver their products and services. Thus, Wal-Mart has an online presence and General Motors is exploring creating a web site where customers can order cars, but Wal-Mart is considered a retail firm and General Motors an automobile manufacturing firm. Why, then, are Cisco and Oracle considered technology firms? There are two groups of firms that are [using this word too much in the paragrap2 OJQJkH'8C@8Body Text Indent(U@( Hyperlink>*B*+XG:y    GGyyy KKXt/tZt                 yE`!$)06B:BKKQX   a  )E  y{"h], at least in popular terminology, technology firms. The first group includes firms like Cisco and Oracle that deliver technology-based or technology-oriented products hardware (computers, networking equipment) and software. You could also include high growth telecommunications firms such as Qualcomm in this group. The second group includes firms that use technology to deliver products or services that were delivered by more conventional means until a few years ago. Amazon.com is a retail firm that sell 0EAb` """"v"#$$&'M*-/11n36!6"67:f;s=@UCEKKK-KKMNOQSSUUUVWWXAXXX!<!!!!!!!!!!*9!!!!*9!!!!*9!!!!!*9!!!!!!*9!!!!!!*9!! !!!!!!!!*9!! !!! ! !!!!!!!!!!!!!!!!!!!!!!! f;s=@UCE HKKKKKKMNOQSSUUUXXXX 1 1 1 1 11`1@111 K s only online, leading to its categorization as a technology firm, while Barnes and Noble is considered a conventional retailer. This group is further broken up into firms that service the ultimate customers (like Amazon) and firms that service other businesses, often called B2B (Business to Business) firms. As the number of technology firms continues to expand at an exponential rate, we will undoubtedly see further sub-categorization of these firms. There are more conventional measures of categorizing te )E   wy .C$$ )E   wy .C?"`"^$&&&&t&'((*+K.1355l7:þ}zw(lMO9:;=OLN3 &(,.?"`"^$&&&&t&'((*+K.1355l7:: :;>d? !$::d?l?qAzADDSG`GIIOOOOPQQRRSSYYZZ[[[[\\@\A\\\\\\\\\\\\\\ttv v vxx zzz|`~‚HhI&HHhfI&HHh uIH0JmH0J j0JU j0JUCJOJQJmHjoeCJOJQJUmH6j[^CJOJQJUmHA:: :;>d?qADSGILOOOOO+OOQRSUWWYYYZ[[\@\\\\\\\\\\\ſ|zzzzwwuuuuruu|  L    v           A    #   0 tuw)d?qADSGq*F & FEƀsIF & FEƀsIF & FEƀsISGILOOOOO+OOqkkiiigi !F & FEƀsIF & FEƀsI OQRSq*F & FEƀsIF & FEƀsIF & FEƀsISUWWYYYZ[[\@\qoiggeeeee !F & FEƀsI F & FEƀsI  @\\\\\\\\\\\t vxz‚1$1$ $&1$#$)@-000hP/ =!"#$%)00h0= /!"#$%&00h/ =!"#$%17 you 2 11 youyou10  [>@>Normal $dCJOJQJkH'mH 2@2 Heading 1 @&544 Heading 2 @&5622 Heading 3 @&622 Heading 4 @&6D@D Heading 5$&d@& CJ22 Heading 6 @&6<A@<Default Paragraph Font6*@6Endnote ReferenceH*22TOC 6 X !22TOC 3 X !22TOC 2 X !..TOC 1 X !, @B,Footer  !,@R,Header  !<&@a<Footnote ReferenceCJEH2@r2 Footnote TextCJ&)@& Page Number..Times12 OJQJkH'8C@8Body Text Indent(U@( Hyperlink>*B*n+[G:y     GGyyy MM[t/tZt                G/!$R)053: CKMMT[     r )E  o rt[GIe1/ !!!!E"#$$&&*,]/h11@35558;f<? CE=HMMMMxNPQ&STVVXXXY;ZZ.[m[[[[!<!!!!!!!!!!*9!!!!*9!!!!*9!!!!!*9!!!!!!*9!!!!!!*9!! !!!!!!!!*9! ! !! ! ! !!!!!!!!!!!K K K KSSS :x/3d?SGOS@\x0256789:\14:UnknownAswath Damodaran Crocker Liu Marissa RyanStern School of BusinessValued Gateway 2000 CustomerSharon Gadayev Champa ChozomMS OFFICE WIN95WILLIAM H. GREENE Avijit Ghosh PC OperationsStern Mike UretskyDiane Belleville David BackusEric and Amy Kolchinsky Stern NYUQueen Elizabeth Ramirez Xavier Martin Ranjay Gulati kim lampaPreferred Customer Alan ShapirogdalyElliot M. BergerProf. E GilmanElaine LengyelSuzette LemsonFelicia ShutterVictor Clark MullinsShaaron M. GomesEditors Gary Simon Norman WhiteL & N JankovicNT Workstation James Cheng Paola DubiniRete SDA Bocconi Davide ContiCustomerURSProf. Giacomo De LaurentisDaniela FaccioAndrea LorenzoniInformation TechnologyPatrizia Trivellato Adam SosinskyPaul, Mel, Marilyn, and Dave Bill Starbuck Paul B. BrownMike Kao Russ HallHedi M. Bergsohn Hedi BergsohnRizzo, PatrickDLJ$DPXX !!8@0(  B S  ?) 1 # . EPf+p+++ ,,,,OOPPUVVXX,4goT Y 6  u } ~y %-$$}%~%,,h3m377H;O;CCHHpNuNNNOOZP[PUWWQX\XXX Russ Hall-C:\dos\temp\AutoRecovery save of CHAP01ed.asd Russ Hall-C:\dos\temp\AutoRecovery save of CHAP01ed.asdAswath DamodaranMacintosh HD:CHAP01ed.docAswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.doc * hhOJQJo(@hh.lLll`n!!!!!!!!!!!!! o &*,]/h158;f<? CE=HJMMMMMxNPQ&STVVXXX[[[[[&&&&h1h1h1 h1 h1 h1 h1 h1h1`h1@h1h1h1 M M M M MVVV :/3d?SGOS@\0256789:\14<UnknownAswath Damodaran Crocker Liu Marissa RyanStern School of BusinessValued Gateway 2000 CustomerSharon Gadayev Champa ChozomMS OFFICE WIN95WILLIAM H. GREENE Avijit Ghosh PC OperationsStern Mike UretskyDiane Belleville David BackusEric and Amy Kolchinsky Stern NYUQueen Elizabeth Ramirez Xavier Martin Ranjay Gulati kim lampaPreferred Customer Alan ShapirogdalyElliot M. BergerProf. E GilmanElaine LengyelSuzette LemsonFelicia ShutterVictor Clark MullinsShaaron M. GomesEditors Gary Simon Norman WhiteL & N JankovicNT Workstation James Cheng Paola DubiniRete SDA Bocconi Davide ContiCustomerURSProf. Giacomo De LaurentisDaniela FaccioAndrea LorenzoniInformation TechnologyPatrizia Trivellato Adam SosinskyPaul, Mel, Marilyn, and Dave Bill Starbuck Paul B. BrownMike Kao Russ HallHedi M. Bergsohn Hedi BergsohnRizzo, PatrickDLJ Administratorisadayan[X !!<!!!!!!!!!!*9!!!!*9!!!!*9!!!!!*9!!!!!!*9!!!!!!*9!! !!!!!!!!*9! !! ! ! !!!!!!!!!!!!!!!!!!!!!!!! o &*,]/h158;f<? CE=HJMMMMMxNPQ&STVVXXX[[[[[&&&&h1 h1 h1 h1 h1 h1h1`h1@h1h1h1 dL dL dL dL dLUUU :‚/3d?SGOS@\‚0256789:\14<UnknownAswath Damodaran Crocker Liu Marissa RyanStern School of BusinessValued Gateway 2000 CustomerSharon Gadayev Champa ChozomMS OFFICE WIN95WILLIAM H. GREENE Avijit Ghosh PC OperationsStern Mike UretskyDiane Belleville David BackusEric and Amy Kolchinsky Stern NYU!8@0(  B S  ? j u 7+A+++++++&S+SSSXYY[[,4go" ' P V C K LU]eGOzS[$$L%M%X,\,:3?36688H<O<AFPFKKQRRSSSXZ[}[[[[Aswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.doc * hhOJQJo(@hh.`n@h hOJQJo(` @hh.@J6J6\+J6J6p"HhHcHdhgHC$EƀgI&C$EƀgI&C$EƀgI&C$EƀgI&C$EƀgI&C$EƀgI&C$EƀgI&C$EƀgI&C$EƀgI& C$EƀgI& R S W  (((<)?)@)f1g178w88;;;f<r>> ?"?S?^?_?g?o?z????? CE=HJxNPPQQQQQ&STVlXXX[[[[[[[P@Q@Q @QvP@Q|Qb>@Pp>@QzQY@QY@QzQZ@PZ@Q|P&k@Q|Q}Q}Pw@P}@Q`~P}@Q~@Qb~Q~QQQ$Q:Q<QLQ\QrQQ2P@P@P@P@ P@ P@P@ Q @Q@QVQVQP<@P>@P@P@P,@P~@P@P@Pj@Pl@QP@P@P@GTimes New Roman5Symbol3 Arial9New York3Times"AsIhI&pG YI%!+>0dZVCh16 PBV Multiples Russ HallAswath DamodaranF & FEƀsIF & FEƀsI FMicrosoft Word DocumentNB6WWord.Document.8 ՜.+,D՜.+,< hp  ' Stern Schooler%Z: Ch16 Title(RZ _PID_GUID Queen Elizabeth Ramirez Xavier Martin Ranjay Gulati kim lampaPreferred Customer Alan ShapirogdalyElliot M. BergerProf. E GilmanElaine LengyelSuzette LemsonFelicia ShutterVictor Clark MullinsShaaron M. GomesEditors Gary Simon Norman WhiteL & N JankovicNT Workstation James Cheng Paola DubiniRete SDA Bocconi Davide ContiCustomerURSProf. Giacomo De LaurentisDaniela FaccioAndrea LorenzoniInformation TechnologyPatrizia Trivellato Adam SosinskyPaul, Mel, Marilyn, and Dave Bill Starbuck Paul B. BrownMike Kao Russ HallHedi M. Bergsohn Hedi BergsohnRizzo, PatrickDLJ Administratorisadayan[X !!8@0(  B S  ? j u 7+A+++++++88&S+SSSXYY[[,4go" ' P V C K LU]eGOzS[$$L%M%X,\,:3?36688H<O<AFPFKKQRRSSSXZ[}[[[[Aswath DamodaranMacintosh HD:CHAP01ed.docAswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran:Macintosh HD:DarkSideofValuation:Russ's Files:CHAP01ed.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.docAswath Damodaran4Macintosh HD:DarkSideofValuation:ModChapters:ch1.doc * hhOJQJo(@hh.`n@h hOJQJo(` @hh.@88\+87p"HhHcHdhgHC$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI&C$EƀeI& C$EƀeI& R S W  (((<)?)@)f1g178w88;;;f<r>> ?"?S?^?_?g?o?z????? CE=HJxNPPQQQQQ&STVlXXX[[[[[[[P@Q@Q @QvP@Q|Qb>@Pp>@QzQY@QY@QzQZ@PZ@Q|P&k@Q|Q}Q}Pw@P}@Q`~P}@Q~@Qb~Q~QQQ$Q:Q<QLQ\QrQQ2P@P@P@P@ P@ P@P@ Q @Q@QVQVQP<@P>@P@P@P,@P~@P@P@Pj@Pl@QP@P@P@GTimes New Roman5Symbol3 Arial9New York3Times"AsIgI&pG YI%!+>0dZ7Ch16 PBV Multiples Russ HallAswath DamodaranF & FEƀsI tr Implicit in these comparisons is the assumptions that more visitors to your site translate into higher revenues, which, in turn, it is assumed will lead to greater profits in the future. All too often, though, these assumptions are neither made explici@h hOJQJo(Xl` @hh.@ l d"HhHcHdhgHC$Eƀ uIC$Eƀ uIC$Eƀ uIC$Eƀ uIC$Eƀ uIC$Eƀ uIC$Eƀ uIC$Eƀ uIC$Eƀ uI C$Eƀ uI 0 f;s=@UCE HKMNOQS@UUUXXXXXXX0@1 @1v0@0~@0@0@0@ 0@ 0@0@ 0 @0>@0@0@0,@0~@0@0@0j@0l@1x0@0@0@GTimes New Roman5Symbol3 _PID_HLINKS'AN{3BD9BF87-B757-1168-B579-B0CD5A817F55}A`bmailto:Inter@ctivex Oh+'0  4 @ L Xdlt|'Ch16ofPBV Multipleso Russ HallleussNormallAswath Damodaranrd8waMicrosoft Word 8.0d@ԭ@h Q@3!@iT! YI3 c l\jbjbSS 11X]zz( 2224hv< *$"Y"["["["["["[",,.~"p2"2222Y"fz22Y" Vx!22Y"~ t~M" CHAPTER 1 THE DARK SIDE OF VALUATION In 1990, the ten largest firms, in terms of market capitalization, in the world were industrial and natural resource giants that had been in existence for much of the century. By January 2000, the two firms at the top of the list were Cisco and Microsoft, two technology firms that had barely registered a blip on the scale ten years prior. In fact, six of the ten largest firms, in terms of market capitalization, at the beginning of 2000 were technology firms, and amaArial9New York3Times"AsI uIpG oH%!+>0dXSCh16 PBV Multiples Russ HallAswath Damodaran [>@>Normal $dCJOJQJkH'mH 2@2 Heading 1 @&544 Heading 2 @&5622 Heading 3 @&622 Headint nor tested, leading to unrealistic valuations. The estimates of future growth are often based upon assessments of the competence of existing managers and their capacity to convert a promising idea into commercial success. This is often the reason why firms in this phase try to hire managers with a successful track record in converting ideas into dollars, because it gives them credibility in the eyes of financial backers. It is also a company that has had unique success in building itself up through acquisitions of smaller firms with promising technology, and converting it into commercial success.12 3