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Analysts’ Fundamental Error in the Computation of Fundamental Value

Hersh Shefrin

Mario L. Belotti Professor

Santa Clara University

January 2018

Abstract

Sell side analysts who employ discounted free cash flow analysis to establish target prices are

vulnerable to making biased valuation judgments. The bias in question is called "growth

opportunities bias," (GOB) which occurs when a firm is expected to earn a rate of return that

exceeds its cost of capital during the terminal horizon. This paper illustrates the magnitude and

importance of GOB using events from the year 2017. The evidence suggests that GOB is

substantial and economically significant. The paper describes possible explanations for GOB and

concludes with a discussion about GOB-nudges, as well as limits to GOB-nudges.

Keywords: sell side analysts; growth opportunities bias; nudge; mispricing

1

1. Introduction

Growth opportunities bias (GOB) involves the faulty assumption that in competitive markets, a

firm can be expected to earn a perpetual return different from its cost of capital (Shefrin 2006,

2014). Discounted free cash flow (DFCF) analysis is the primary methodology for computing the

fundamental value of a stock. This paper describes the incidence of GOB among analysts who

arrive at target prices by using discounted expected free cash flows, proposes nudges to mitigate

GOIB, suggests a range of explanations for why GOB occurs, and discusses reasons for limits to

GOB-nudges.1 The paper is written primarily for analysts, the firms that hire them, the investors

who rely on their judgments, and the agencies that certify them.2

Besides discounted free cash flow analysis, sell side analysts use a variety of valuation

techniques to establish target prices. Most techniques are ratio-based, involving ratios such as

price-to-earnings, price-to-EBIT, price-to-free cash flow, and price-to-sales.3 However,

DFCF-based techniques, rather than ratio-based techniques, comprise the basis for computing

fundamental values. Notably, some analysts use both approaches, thereby connecting ratio-based

valuations to estimates of fundamental value.

This paper is organized around the following set of questions and answers.

1 The nudge framework is developed in Thaler, Richard and Cass Sunstein, 2008. Nudge: Improving Decisions

About Health, Wealth, and Happiness, New Haven: Yale University Press. 2 When sentiment is positive, target prices will tend to be too high. When sentiment is negative, target prices will

tend to be too low. This paper focuses on the case of positive sentiment. Notably, Modigliani and Cohn (1979)

focused on the case of negative sentiment, which applied during the second half of the 1970s during a period of very

high inflation. Whereas Modigliani and Cohn argued that analyst undervaluation stemmed from discounting real

cash flows at nominal discount rates, the argument in this paper focuses on assumptions about the expected rate at

which free cash flows grow in perpetuity. 3 The analyst literature reports that the majority of analysts use ratio-based valuation models based on P/E and PEG

instead of” more sophisticated valuation models, such as residual income models.” See Bradshaw (2004) and Brown

et al. (2015).

2

Is there a simple way to check for GOB in free cash flow based valuation? There is, and

it involves a single equation, which reframes a standard textbook equation for the sustainable

growth rate.

Do sell side analysts exhibit GOB? They do, and it is easy to check using the single

equation just mentioned. Applying the equation reveals that in some instances, analysts’ long-

term assumptions are highly unrealistic, especially given the degree to which firms historically

have not earned more than their cost of capital.

Is the magnitude of GOB small or large? An analysis of U.S. equity market conditions

from 2017 suggests that the answer is large and economically significant. During 2017, the U.S.

equity market was dominated by technology stocks.4 Media reports discussed below, especially

those in The New York Times and The Wall Street Journal, emphasized this dominance, and

raised questions about whether the market as a whole was overvalued. Given the context, this

paper considers a sample of sell side analysts’ target prices for large technology stocks.

Correcting for GOB implies that analysts overvalued stocks in the sample by 50 percent, relative

to valuations associated with zero GOB.

How can analysts eliminate GOB from their valuations? The paper suggests two

techniques (nudges).

Why do analysts exhibit GOB? The paper discusses possible explanations for GOB,

centered on the following three concepts: analyst ignorance, limits to arbitrage, and agency

conflicts. Analyst ignorance is self-explanatory. The discussion about limits to arbitrage makes

the point that when markets are inefficient, analysts might not wish to set target prices equal to

fundamental value. Nevertheless, if analysts do compute fundamental value using discounted

4 GOB applies beyond the specific time period and stocks discussed in this paper. See Shefrin (2014) and the first

(2006) edition of Shefrin (2017).

3

free cash flow analysis, then it is appropriate to eliminate GOB, and to communicate to investors

the difference between what target price measures and what an estimate of fundamental value

measures. The discussion about agency conflicts suggests why it might actually be in analysts’

interest to obscure the difference between what target price measures and what an estimate of

fundamental value measures.

Will the investment community take steps to mitigate GOB, or are there limits to nudges?

The answer for mitigating GOB is only if it is in the investment community’s interest to do so;

and this will determine the magnitude of limits to nudges. The paper concludes by offering

recommendations for instituting GOB nudges, both for analysts and for a certifying body such as

the CFA Institute. How analysts and the CFA Institute choose to react to the recommendations

remains to be seen.

2. Growth Opportunities Bias

This section derives a condition establishing when a firm can be expected to earns its cost of

capital exactly.

The equation defining free cash flow (FCF) during a given year is:

(1) FCF = UCF - CapEx

where:5

UCF = unlevered cash flow during the year, and

CapEx = capital expenditure during the year.

5 For textbook references to most equations discussed in this section, see Bodie, Zvi, Alex Kane, and Alan Marcus,

2017, Essentials of Investment, Tenth Edition. New York: McGraw-Hill Education. Equations (1) and (3) in this

section correspond to equation (13.9) in Bodie et al. Equation (4) corresponds to equations (13.6) and (13.8).

Equation (5) corresponds to equation (13.12). Note that the equations in Bodie et al. should be interpreted as being

for an all equity financed firm. Equation (6) corresponds to the equation g = ROE×plowback ratio, described on p.

410 of Bodie et al.

4

In some financial textbooks, UCF is defined as:

(2) EBITDA – tax – change in operating net working capital

Let DA denote depreciation and amortization. Then (1) and (2) imply:

(3) FCF = CF-DA - CapEx + DA = NUCF – NetCapEx

where NUCF = net unlevered cash flow, and NetCapEx = CapEx - DA.

In a given year, a firm divides its unlevered cash flows (UCF) into the following three

categories:

1. DA: Replacement of depreciated fixed assets;

2. NetCapEx: capital expenditure for growth, meaning capital investment in excess of

replacement (DA); and

3. FCF: what remains from unlevered net cash flow after expenditures for replacement of

fixed assets and growth.

Notice that net unlevered cash flow is divided into two categories: NetCapEx

(reinvestment for growth) and free cash flow (FCF), which is cash generated that is available to

be paid to the firm’s investors (debtholders and stockholders). The ratio NetCapEx/NUCF is the

rate at which the firm reinvests for growth from its net unlevered cash flow. For short, call this

ratio the “growth reinvestment rate.”

5

Let time be indexed in years by t = 0, 1, 2, …, T, T+1, … Call year 0 the present, year T

the terminal year, and year T+1 the first year of the terminal horizon. Typically, the terminal

horizon is defined so that the firm is expected to earn its cost of capital exactly from year T+1

on. The present value, in year T dollars, of the expected free cash flow stream that begins in year

T+1 and continues into perpetuity is called the Terminal Value (TV). As discussed in standard

textbooks (see previous footnote), when the firm is expected to earn its cost of capital (WACC),

denoted by the symbol k, during the terminal horizon, then

(4) TV = NUCF / k

It is common practice to assume that during the terminal horizon, a firm’s expected cash

flows grow at a constant rate g. In that case, TV is given by the standard present value perpetuity

formula:

(5) TV = FCF(T) × (1+g) / (k-g)

Equating the two equations for TV, (4) and (5), leads to the following equation:

(6) g = k × NetCapEx / NUCF

Equation (6) constitutes the condition for the terminal value (TV) of a constant growth (g)

expected free cash flow stream (FCF when the firm is expected to earn its cost of capital (k)

exactly. The equation states that when the firm is expected to earn its cost of capital exactly

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during the terminal period, then its expected growth rate g is the product of the cost of capital (k)

and its growth reinvestment rate.

Equation (6) links the rate at which the firm is expected to grow during its terminal

horizon with the rate at which it reinvests for growth. Notably, when a firm earns its cost of

capital exactly, its growth rate is not a free variable. Rather, the growth rate is determined by the

firm’s investment policy and its cost of capital, as in standard textbook analysis.6

An analyst who assumes that a firm’s free cash flows will grow at a rate greater than the

rate given by equation (6) is effectively assuming that firm will earn more, in expected value,

than its cost of capital. In a competitive market, that would give rise to growth opportunities bias.

Likewise, an analyst who assumes that a firm’s free cash flows will grow at a rate lower than the

rate given by equation (6) is effectively assuming that firm will earn less, in expected value, than

its cost of capital. This too constitutes growth opportunities bias in a competitive market, as in

the long term investors will shift capital away from inferior opportunities.

3. Examples of Growth Opportunities Bias

To provide an example of GOB, consider the Morgan Stanley report on Amazon, dated April 5,

2017.7 The Morgan Stanley team’s discounted free cash flow analysis is displayed in Exhibit 1,

and its pro forma forecasted balance sheet is presented in Exhibit 2. The Morgan Stanley team’s

target price for Amazon at the time was $975, and its fair (fundamental) value was $973.

6 The textbook equation for sustainable growth rate g is that g is equal to the product of ROE and the plowback ratio.

For an all-equity financed firm that exactly earns its cost of capital, ROIC = ROE = WACC = k. Therefore, equation

(6), which pertains to the ratio g/k, reframes the textbook relationship that the plowback ratio be equal to g/k when

the firm is expected to earns its cost of capital exactly. 7 The report is referenced by its lead author Brian Nowak.

7

From Exhibit 1, notice that the Morgan Stanley team forecasts that Amazon’s perpetual

growth rate will be 3 percent, with the terminal year being 2025. The team estimates the cost of

capital (WACC) to be 7.5 percent. Applying equation (6) implies the following: Given the

Morgan Stanley team’s estimates, if Amazon’s growth reinvestment rate during the terminal

horizon is equal to 40 percent (g/k = 0.03/0.075), then Amazon can be expected to earn its cost

of capital exactly during the terminal horizon.

Because of the constant growth rate steady state assumption for the terminal horizon,

computing Amazon’s growth reinvestment rate during the terminal period involves computing

the rate for the terminal year. Doing so requires knowing unlevered cash flows (UCF), capital

expenditure (CapEx), and depreciation and amortization (DA). The values of UCF and CapEx

for the terminal year 2025 are given in Exhibit 1. However, forecasts of DA only appear in the

pro forma cash flow statement (Exhibit 2), which ends in 2020. Exhibit 3 displays DA, EBITDA,

and the ratio DA/EBITDA. This ratio can be used to estimate DA for the terminal year.

Given the value of CapEx, the value of DA is important for determining how much of

CapEx is earmarked for growth rather than replacement of fixed assets. The larger is DA, the less

will be reinvestment for growth.

Consider two possible methods for estimating the terminal year DA/EBITDA ratio. The

first is to use the 2020 value, and the second is to extrapolate the ratio trend line. Consider each

in turn.

Under the first method (based on the 2020 value), the DA/EBITDA ratio is 38 percent.

Below is the relevant calculation for unlevered cash flow, where the first four items are taken

directly from the Morgan Stanley report.

8

Adjusted EBITDA $72,944

(-) Cash taxes ($14,149)

(+/-) Changes in working capital $1,061

(-) Stock-based compensation ($7,175)

Unlevered cash flow (UCF) is simply the sum of these four items above. Free cash flow to the

firm, also called unlevered free cash flow (UFCF) is the difference between UCF and CapEx.

That is, the third line below is the sum of the first two lines.

Unlevered cash flow (UCF) $52,681

(-) CapEx ($27,412)

Unlevered free cash flow (FCF) $25,269

To compute the growth reinvestment rate, subtract depreciation and amortization (DA) from both

UCF and CapEx, as follows:

DA/EBITDA 2020E (from 2020E balance sheet) 38%

Depreciation and Amortization 2025E = 38% x EBITDA 2025E $27,715

Net unlevered cash flow 2025E = NUCF = UCF – DA $24,966

NetCapEx 2025E = CapEx - DA ($303)

Growth reinvestment rate = NetCapEx / NUCF -1.2%

9

The growth reinvestment rate associated with the first method is -1.2 percent, and is

negative because forecasted CapEx for 2025 will be less than forecasted DA. Recall from the

above discussion that GOB is nonzero unless the growth reinvestment rate is 40 percent.

The second method for computing DA/EBITDA adjusts the 2020 value down by the

estimated trend line from 2015 through 2020, which leads to a 2025 ratio of 22.5 percent. The

growth reinvestment rate associated with the second method is 32.5 percent, which is less than

40 percent.

The two methods for estimating DA in the terminal year give rise to very different growth

reinvestment rates. The balance sheet values for the line item “Fixed Assets, Net” in Exhibit 2

suggest that the first method is more appropriate. In this respect, notice that the Morgan Stanley

team forecasts that Net Fixed Assets will decline every year after 2016, which is consistent with

a negative terminal growth rate associated with the first method.

It seems reasonable to ask whether it makes sense to assume that Amazon will be able to

grow at 3 percent a year into perpetuity while its fixed assets continually decline during the

terminal horizon. This assumption appears to be sufficiently unrealistic as to qualify as extreme.

In view of the fact that the Morgan Stanley team’s forecast of DA needed to be estimated

for the terminal year, consider the Credit Suisse analyst team’s target price for Amazon, taken

from Credit Suisse’s report from July 28, 2017.8 See Exhibit 4. As can be seen in Exhibit 4, the

Credit Suisse report does provide an estimate for terminal year DA, where the terminal year is

2023.

Notably, the Credit Suisse team forecasts that terminal year DA will be $41,897 whereas

CapEx will be $27,205. In other words, the Credit Suisse team assumes that in the terminal year

NetCapEx will be negative, and therefore the growth reinvestment rate will also be negative (as

8 The report is referenced by its lead author, Stephen Ju.

10

net unlevered cash flow is forecast to be positive).9 At the same time, the Credit Suisse team

forecasts a terminal growth rate of 3 percent, and estimates a cost of capital of 10.5 percent.10

4. Two GOB Nudges for Target Price Computations

The Amazon target prices for both the Morgan Stanley team and the Credit Suisse team exhibit

GOB. There are two possible nudges for mitigating GOB when computing target prices. The first

is to maintain all the assumptions, except for the terminal growth rate. The second is to maintain

the forecast of terminal year UCF, but modify the value of FCF during the terminal year, in

order to produce a growth reinvestment rate that would support the assumed terminal growth

rate.

4.1. Nudge Method 1

Consider an example of the first method, adjusting the terminal growth rate, for the Morgan

Stanley target price, beginning with the case in which the DA/EBITDA ratio is 38 percent. By

equation (6), the terminal horizon growth rate, when the firm is expected to earn its costs of

capital exactly, is the product of the growth reinvestment rate and the WACC. That produce is

given by -0.001 = -0.012 × 0.075. By equation (5), terminal value, with growth rate -0.1 percent

is given by

$25,268 × (1-0.001) / (0.075+0.001) = $332,574

9 The Credit Suisse pro forma balance sheet for Amazon leaves blank the values of Property and Equipment, Net,

whose values decline from 2020 on. See Exhibit 5. The missing entries are denoted by “x”, with inferred values and

associated growth rates appearing at the bottom of the Exhibit. Notice the negative growth rates from 2020 on. 10

For a full discussion of the Credit Suisse analyst team’s valuation of Amazon, and the impact of GOB, see

Shefrin, Hersh, October 1, 2017, “Credit Suisse's Mistaken Amazon Valuation Is But The Tip Of The Iceberg,”

Forbes, https://www.forbes.com/sites/hershshefrin/2017/10/01/credit-suisses-mistaken-amazon-valuation-is-but-

the-tip-of-the-iceberg/#736c47223995.

11

In contrast, terminal value when the terminal horizon growth rate is 3 percent, as is assumed in

the Morgan Stanley report, is given by

TV = $25,268 × (1 + 0.03) / (0.075 – 0.03) = $578,379

Terminal value in this analysis is time stamped in 2025. Discounting back to 2017, leads the

present value of the terminal to be $328,511 in the report, but when corrected for GOB, leads

instead to $186,475.

Correcting the Morgan Stanley target price for GOB, using the first nudge, effectively

involves replacing the amount $328,511 associated with NPV of terminal value in Exhibit 1 with

$186,475, and then recalculating equity value per share. Had the Morgan Stanley team used -1.2

percent for its terminal growth rate in computing equation (5), instead of 3 percent, then it would

have established a target price for Amazon of approximately $680. Notably, Morgan Stanley’s

$973 estimated fair value suggests an overvaluation of 43 percent, relative to a value associated

with expecting Amazon to earn its cost of capital exactly during the terminal horizon.

For completeness, here is how the computations change using the second method

(estimated trend line) for computing DA/EBITDA. Recall that the second method entails a growth

reinvestment rate of 32.5 percent in 2025, and terminal growth rate of 2.4 percent. The target

price associated with this growth rate is approximately $884, which represents an overvaluation

of 10 percent.

Consider next how the growth rate adjustment nudge applies to the Credit Suisse target

price analysis. For the terminal year (2023), Credit Suisse forecasts the following values: UCF of

$93,603, CapEx of $27,205, DA of $41,897, and FCF of $66,398. This implies a forecasted

value for NUCF of $51,706 and for NetCapEx of -$14,692. The associated growth reinvestment

rate is NetCapEx/NUCF, which equals -28.4 percent. Multiplying the growth reinvestment rate

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by the WACC yields the terminal growth rate (-3 percent), when Amazon is expected to earn its

cost of capital exactly during the terminal horizon. In the first nudge, substitute -3 percent for +3

percent in equation (5), the computation of terminal value TV.

4.1. Nudge Method 2

Consider next how the second type of nudge, involving the adjustment of free cash flow in the

terminal year, applies to the Credit Suisse target price analysis. In this nudge, choose FCF so that

the growth reinvestment rate (NUCF-FCF)/NUCF equals the value of g/k assumed in the report.

In this regard, the Credit Suisse team assumed that g/k would be 28.6 percent (= 0.03/0.105).

Therefore set terminal year FCF equal to 71.4 percent (= 1 – 0.286) of NUCF, yielding a value

of FCF equal to $36,933. Now substitute $36,933 for the $66,398 which Credit Suisse originally

forecast for terminal year free cash flow, in the computation for terminal value (TV).

The two nudge techniques produce target prices which, while not identical, are close to

each other: $948 for the first and $984 for the second. In contrast, Credit Suisse’s July 27

Amazon target price for 2018 was $1,474.

5. Technology Stocks and Market Values in 2017

Between December 30, 2013 and June 7, 2017 the value of the S&P 500 index increased by over

32 percent. Technology stocks contributed heavily to the increase, a fact emphasized in media

coverage of the market. See Thomas (2017). At the time, stocks of technology companies

comprised featured the highest market capitalizations in the index. The stocks in question, in

order of market capitalization from largest to smallest, were: Apple, Alphabet, Microsoft,

Amazon, and Facebook.

13

Of these five stocks, all but Microsoft were included in the acronym FAANG, with the

“N” in FAANG referring to Netflix. Between December 30, 2013 and June 7, 2017 the FAANG

stocks increased by much more than the S&P 500 index, and had gained attention for their

relative performance. See Exhibit 6. In November 2017, The Wall Street Journal noted that the

FAANG stocks comprised 11 percent of the S&P 500. See Gold (2017).11

Notably, between

December 30, 2013 and June 7, 2017 the increase in Microsoft’s stock price was higher than that

of either Apple or Alphabet, but not as high as Netflix: this fact raises the question of why

Microsoft was excluded from this particular subset of stocks.

Coverage in The New York Times drew a comparison between the recent period and the

dot-com bubble period, as both periods featured the dominance of technology stocks in market

valuations. Unlike the dot-com period, during the recent period technology firms were profitable

and cash flows were positive. However, like the dot-com period, there was a great variety of

views about valuations, with many investors expressing concerns that the stocks of technology

firms were overvalued, and other investors suggesting that the future prospects of these firms

merited their valuations.

Amazon’s valuation (during 2017) is a case in point. One view (described in media

coverage) held that in the long term, Amazon’s future earnings growth would be unable to catch

up with its sales expansion as well as the large investment spending needed to force other firms

out of its markets. A contrasting view, expressed by an active money manager with Amazon as

his top position, held that Amazon’s large cash position and profitability of its web services

division gave it a competitive advantage never before seen.

11

Certainly, market prices for individual stocks can reflect psychological benefits from holding those stocks, as well

as financial benefits associated with free cash flows. That said, the analyst target prices investigated in this paper are

based solely on financial considerations, with no mention of auxiliary psychological benefits.

14

The Times article concludes with one money manager characterizing the market

environment at the time as a “mania,” but one where money managers in general could not risk

being left out, should these stocks continue to climb.

6. GOB in Analysts’ Valuations of FAANG Stocks

Consider sell side analysts’ assessments of the fundamental values of the FAANG stocks during

the first three quarters of 2017, the time period of the media coverage discussed in the previous

section. Although not all analysts arrived at target prices by using discounted free cash analysis,

some did, and their judgments provide some insight into the fundamental values of these stocks.

Data on sell side analysts’ assessments of FAANG stocks were collected from Thomson

One, and from Yahoo Finance. Yahoo Finance, double checked with Bloomberg, was used to

obtain the consensus analyst target price for each stock, as of July 28, 2017. The Thomson One

database was used to obtain analyst reports whose release dates were as close as possible to July

28, 2017, and which contained a discounted free cash flow analysis.

The majority of analysts following the FAANG stocks, or most stocks in general, do not

provide discounted free cash flow computations. As Exhibit 7 shows, six analyst firms provide

these computations, but typically not for all five FAANG stocks. Notice that there are no analyst

reports mentioned for Apple, Inc. This is because no reports for this period included discounted

free cash flow computations with sufficient detail that they could be tested for GOB. The

FAANG stocks without Apple are usually described by the acronym FANG.

Exhibit 7 displays the DCF-based target prices for each such analyst firm and FANG

stock, the mean target prices, and the consensus target prices for July 28. Notice that the

15

DCF-based target prices are typically higher than the consensus values, of which they are part;

however, the correlation between the two is 99 percent.

Exhibit 8 documents the percent contribution of terminal value to target price for each

report. The mean percent contribution is 70 percent, although there is considerable variation

across stocks. The high contribution of terminal value indicates that the potential importance of

GOB is high.

Panels A and B of Exhibit 9 document the analysts’ assumptions about cost of capital

(WACC) and terminal growth rate. For each stock, there is a bit of disagreement among some

analysts about these assumptions, but by and large they held uniform views.

To test for the presence of GOB in each report, compute the terminal growth rate when

the firm is expected to earn its cost of capital exactly during the terminal horizon. Exhibit 10

displays the associated growth rate.12

A comparison of the values in Exhibit 10 with those in

Panel B of Exhibit 9 indicates that every report features GOB. Negative growth rates in Exhibit

10 feature the implicit assumption that firms’ capital expenditures will be insufficient to replace

depreciated assets completely, despite those firms being assumed to grow at rates near or above

the growth rates of the overall economy. This feature was a subject of discussion in section 3.

Consider adjusting target prices by applying the first of the two nudge techniques

discussed in section 4. Exhibit 11 illustrates the degree of overvaluation in each report, measured

as the ratio of target price in report to target price adjusted to remove GOB. The mean

overvaluation across all reports underlying Exhibit 11 is 50 percent.13

Keep in mind that

overvaluation as it is used here, refers to impact of GOB, not whether market prices are actually

12

For the Morgan Stanley target price for Amazon, the higher growth rate from section 3 is used. 13

On November 29, 2017 technology stocks fell sharply, with no clear fundamental cause. See Dieterich et al.

(2017).

16

50 percent higher than fundamental value. The latter sense of overvaluation is discussed later in

the paper.

7. Possible Explanations for GOB

What are we to make of GOB-induced target price bias of FANG stocks by 50 percent? This

section discusses three possible explanations for analyst susceptibility to GOB, of which two are

explained using metaphors for the market. The first explanation involves “analyst ignorance.”

The second explanation is based on limits to arbitrage, and employs Keynes’s metaphor of a

“beauty contest” (Keynes, 1936). The third explanation is based on agency costs, and uses a

“drug dealer” metaphor.

7.1. Analyst Ignorance

“Analyst ignorance” pertains to failure to appreciate the economic principle that in the long run

firms are expected to earn their cost of capital exactly. The principle is an entrenched idea in

traditional finance, is regularly taught in academic programs, and is incorporated into free cash

flow analysis. See Cornell and Damodaran (2014).

Certainly “analyst ignorance” is not total, and is understood by at least some analysts. In

this regard, a UBS Research note on discounted free cash flow valuation explains that during the

terminal horizon, a firm’s expected return on invested capital (ROIC) will coincide with its

WACC.14

This last issue, about ROIC, and the associated valuation mathematics do not qualify as

14

UBS Research, March 16, 2017. “Fundamental Equity Analytics: How To… Analyse and Talk the Language of

Multiples.” The UBS report states: “The 2nd stage terminal value period assumes that the sustainable ROIC is equal

to the WACC. This therefore assumes that any perpetuity growth generates no further added value. As a result there

is no requirement for ROIC or perpetuity growth rate assumptions.” (Page 40). Because of equation (4), the last

sentence is true. However, ignoring the perpetuity growth rate obscures the degree to which the firm might

underinvest during the terminal horizon.

17

rocket science. However, none of the analyst reports examined for this paper discuss the ROIC-

WACC comparison, let alone implement it in their target price derivations.15

Therefore, despite

the existence of the UBS Research note, there are grounds for suggesting some measure of

“analyst ignorance.”

Exhibit 12 contrasts the mean prior five-year ROIC for each of the FAANG stocks and

their associated mean WACC values from the analysts’ reports discussed in the paper. For Apple,

the WACC value is taken from the UBS Research report mentioned above, which uses Apple

stock as an illustrative example. Notice that in Figure 12, three of the five firms featured ROIC

values below their corresponding WACC values, while two firms featured the opposite. Five

years is a relatively short period, compared to the terminal horizon. Nevertheless, the recent

history does not support the perspective that all five stocks can be expected to earn more than

their cost of capital during their respective terminal horizons.

There are behaviorally-based explanations for why some analysts might be ignorant

about GOB. The first involves framing, and the fact that GOB is an opaque concept. Even

though the growth reinvestment rate is straightforward to compute and apply, it is not a salient

number in analyst reports. Expressed differently, the growth reinvestment rate is not among the

standard valuation variables that analysts use when computing discounted free cash flows. The

associated opaqueness might lead analysts to believe that they are free to choose the terminal

growth rate, such as setting it equal to the forecasted growth rate of the economy. However, in

doing so, they neglect the connection between the terminal growth rate and investment policy.

A second framing issue pertains to the fact that the growth reinvestment rate is based on

values that are net of depreciation. The ratio of CapEx to unlevered cash flow is easy to compute.

15

Ironically, during 2017, no regular UBS research reports appear to present discounted free cash flow analysis for

establishing target prices for FAANG stocks.

18

However the growth reinvestment rate is the ratio of “net CapEx” to “net unlevered cash flow,”

as both numerator and denominator are net of depreciation. Growth reinvestment is less

transparent than the ratio of CapEx to unlevered cash flow. The low forecasted terminal growth

rates are directly tied to low analyst forecasts for NetCapEx, which for some of the FAANG

firms is negative. In contrast, see Exhibit 13 which provides historical growth rates for the

FAANG firms.16

7.2. Limits to Arbitrage: Keynes’s Beauty Contest Metaphor

Next, consider “limits to arbitrage.” In the behavioral perspective, limits to arbitrage involve

constraints that prevent markets from being fully efficient when the market is populated by both

error-prone investors subject to biases and error-free investors. Keynes (1936) used the metaphor

of a “beauty contest” to explain why stock prices would not coincide with fundamental values.17

In the beauty contest metaphor, participants submit entries to a newspaper contest for

what they judge to be the “six prettiest faces” from a hundred newspaper photos, with the

winning entry being the one closest to the average entry. Therefore, beauty contest participants

are induced to base their selections on the choices they predict other participants will make, as

well as than their own subjective sense of contestants’ beauty. Implicit in the metaphor is that

participants hold heterogeneous views.

As in the beauty contest metaphor, Keynes suggested that investors do not necessarily

trade by taking long positions in stocks they judge to be undervalued relative to fundamental

16

The period associated with mean historical growth rates varies from firm, as the different FAANG firms have

different ages. Periods for computing arithmetic means begin once the growth rates stabilize from initial extreme

values, which are mostly positive. Some might argue that advances in machine learning and artificial intelligence

will allow for high terminal growth rates in the face of declining net assets. Such an argument does not appear in

analyst reports. 17

The discussion about the beauty contest metaphor for equity markets is found in section V of Chapter 12 of

Keynes (1936).

19

value, and short positions in stocks they judge to be overvalued relative to fundamental value.

Instead, he suggested that most investors attempt to identify stocks which they believe other

investors will find increasingly attractive going forward, and to purchase those stocks before they

increase in price. An analogous statement applies to short selling, and stocks that other investors

might view less favorably going forward.

Differences of opinion are implicit to the beauty contest metaphor and to real world

markets. Indeed the discussion about Amazon’s stock price in section 5 above provides a vivid

example of the latter. Keynes’s argued that in the presence of such differences, error-free

investors cannot be counted on to bring market prices and fundamental values into equality.

Specifically, he stated that professional investors “are, in fact, largely concerned, not with

making superior long-term forecasts of the probable yield of an investment over its whole life,

but with foreseeing changes in the conventional basis of valuation a short time ahead of the

general public…, with what the market will value it at, under the influence of mass psychology,

three months or a year hence.” (Keynes, 1936, Pages 154, 155).

Security analysts fall into the category of Keynes’s professional investors. Some analysts

might compute fundamental value, but many do not, instead relying on ratio-based valuation

techniques. In the behavioral perspective, while market prices are assumed to converge to

fundamental values in the long run, limits to arbitrage might prevent them from converging in

the short run. In addition, sentiment can cause the gap between market prices and fundamental

values to widen for long periods before reverting to zero. Therefore, setting target prices equal to

fundamental values in the short run, which in practice is 12 to 18 months, might not be optimal.

Therefore analysts who do not suffer from analyst ignorance, but generally rely on discounted

free cash flow techniques, might intentionally inject bias into their target prices, because setting

20

target price equal to fundamental value might be non-optimal in the presence of inefficient

prices.18

In this regard, while the S&P 500 rose 20 percent during all of 2017, on average, FANG

stocks rose by almost 50 percent.19

7.3. Agency Conflicts: A “Drug Dealer Metaphor”

Consider next an agency conflict-based explanation for why sell side analysts who set target

prices using discounted free cash flows might intentionally establish target prices that are too

high.

Survey results from Brown et al. (2015) indicate that analysts report that what is

extremely important to their career advancement opportunities are broker votes in the annual

survey conducted by the Institutional Investor All American Research Analyst. Broker votes are

the second most important contributor to compensation, behind industry knowledge. Analysts

report that their compensation does not strongly depend on having generated accurate earnings

forecasts and profitable stock recommendations. In particular, they state that unfavorable

forecasts and stock recommendations do not result in lower compensation.

Broker votes link analyst incentives to broker incentives, and broker incentives are

positively linked to trading volume. In theory, with investors being the ultimate consumers of the

valuation services provided by analysts, competition among analysts might eliminate systematic

biases. However, such an argument assumes that investors are themselves free of bias. In this

18

Because of market inefficiencies that persist as a result of limits to arbitrage, GOB-impacted target prices might

provide better predictors of short-to-intermediate term prices than target prices that are free of GOB. The lead

analysts for the reports discussed in section 3, Brian Nowak of Morgan Stanley, and Stephen Ju of Credit Suisse, are

highly rated by websites such as TipRanks. In December 2017, Ju had a five star rating and was ranked 67 out of

10,977 analysts, while Nowak had a four and a half star rating and was ranked 579 out of 10,977 analysts. See

https://www.tipranks.com/analysts/stephen-ju and https://www.tipranks.com/analysts/brian-nowak. 19

See Chapter 3 of Shefrin (2017) for an example featuring GOB along with very positive returns in the short and

intermediate term, with eventual reversal after analysts reduced the degree of bias in their long-term free cash flow

forecasts.

21

respect, the combination of psychological factors and limits to arbitrage can support the

persistence of GOB by analysts.

Chief among psychological factors is “motivated reasoning,” a form of “confirmation

bias,” whereby people downplay the importance of information that does not confirm views they

wish to hold. In this regard, many investors might wish to believe that fundamentals justify high

market valuations. Information that is contrary to desired views does not activate their

neurological reward systems, and therefore does not capture their attention. A secondary

psychological consideration involves psychological benefits from holding, or trading stocks,

beyond the direct financial benefits. However, there is no mention made of such benefits in the

analyst reports studied for this paper.

Just as the limits of arbitrage can be described using a beauty contest metaphor, the

agency conflict aspect can be described using a “drug dealer” metaphor. In the “drug dealer”

metaphor, self-interested drug dealers encourage their customers’ self-destructive habits, and

customers resist efforts at rehabilitation; and of course, dealers too can be addicts.20

Just as drug

cartels supply drug dealers with substances that feed their customers’ addictive habits, analysts

supply brokers with upwardly biased target prices to feed investors’ addiction to trading

overvalued stocks. See Barber and Odean (2000) who analyze trading patterns of individual

investors.21

Brokers’ interests are served by high trading volume, not overvaluation per se. For this

reason, brokers would not penalize specific analysts because they produce target prices that lie

below consensus. The key here is that trading volume is related to the degree of disagreement.

Industry knowledge, the top compensation factor for analysts, provides credibility to their

20

Adam Smith (1759) focused attention on a human weakness he called “self-deceit.” 21

Just to be clear, the “drug dealer metaphor” is a metaphor.

22

reports, even if inaccurate. In the drug dealer metaphor, credibility matters more to investors than

accuracy.

Just as user addiction lies at the heart of the drug market, bias and sensation seeking lies

at the heart of the drug dealer metaphor. Investors are the ultimate consumers of analyst reports,

and if they may have no interest in hearing about fundamental value. As the late artist Amy

Winehouse (2006) sang: “No rehab!” For investors, “No rehab!” means ignoring GOB, even

when they possess the technical skills to compute fair values using discounted free cash flows;

and of course, analysts do possess those skills.

7.4. Causality

There is reason to wonder about causality, and whether analysts’ target price biases causally

induce market overvaluation. At the very least, there is reason to wonder whether analysts are

providing investors with informed judgments about the degree to which market prices reflect

fundamental values.

Causality is especially germane for the “drug dealer” metaphor, but also applies to the

other two explanations. Of course, causality might run in either direction. Just as analysts’ target

prices might influence investors’ judgments, market prices might sway analysts’ judgments of

fundamental value. In any event, there is a discernable relationship between this bias and the

relative values displayed in Exhibit 6. Specifically, the correlation between the values in Exhibit

6 (return relative to the market) and the values in Exhibit 11 (overvaluation) is 68 percent.

23

7.5. Limits to Nudges?

The three explanations are neither mutually exclusive nor exhaustive. Moreover, the nudge

techniques described above are appropriate for addressing analyst ignorance. In this regard, the

CFA Institute provides educational products and certification services to the financial analyst

community. Approximately a quarter of the analysts authoring reports list their CFA

designations.

There is a long history of security analysts being criticized. In his 1972 Journal of

Finance paper, Slovic (1972) echoes a warning by Gray (1966) to analysts “that unless they

develop procedures for measuring the validity of their efforts they are likely to have such

assessments imposed upon them by the profession.” What should we make of this warning,

which has hardly been borne out, in light of the three explanations proposed in this section? Are

there limits to nudges?

If limits to arbitrage provide the primary explanation for GOB, then GOB might be

tactical. In this case, the case for applying GOB nudges still holds, with the focus being on

analysts making clear to investors the distinctions between target prices and unbiased judgments

of fundamental value. In this case, the role of the CFA Institute would be similar to that

described for addressing analyst ignorance.

If agency conflicts provide the primary explanation for GOB, then only a change in

incentives will lead to the application of GOB nudges. In the absence of investor demand that

GOB be mitigated, attempts to raise the issue of GOB will be strongly resisted (Shefrin, 2014),22

22

Shefrin (2014) documents previous unsuccessful attempts to make analysts aware of valuation bias stemming

from a failure to require that firms be expected to earn their cost of capital exactly during the terminal horizon.

Moreover, all indications suggest that analysts have ignored the arguments in Shefrin (2014), and for that matter

blog posts such as Shefrin (2017). The author’s attempts to communicate directly with analysts authoring recent

reports on FANG stocks have been unsuccessful, as the latter have chosen not to respond.

24

both by analysts and by the CFA Institute.23

In other words, there may well be limits to nudges in

the presence of agency conflicts.

8. Conclusion

A minority of sell side analysts arrive at target prices by computing fundamental value using

discounted free cash flow analysis. For those that do, target prices feature growth opportunities

bias. For FANG stocks dominating U.S. equities in 2017, GOB has led to overvaluations of

approximately 50 percent.24

In this respect, overvaluation is conditional on analysts’ forecasts of

free cash flow and cost of capital estimates. Those who trust these forecasts and estimates as

being free from bias might well conclude that the market overvalues FANG stocks by 50 percent.

Some might even argue that upwardly biased target prices for FANG stocks is a major

contributor to overvaluation of equity markets in general, not just overvaluation of FANG stocks.

An important part of mitigating GOB is assessing the rates at which firms need to

reinvest their cash flows for growth, if they are to earn their cost of capital in the long run. The

examples discussed in this paper make clear that analysts underestimate how much reinvestment

will be required. Moreover, some analysts assume that firms will be able to grow at the long run

potential of the economy, while simultaneously allowing their capital to decline to zero over

time. This assumption is sufficiently unrealistic as to qualify as extreme. In all cases analyzed in

this paper, the terminal growth rate is much lower than historical growth rates of net Plant,

23

See the discussion about products and revenue streams in the CFA Institute’s Annual Report, Fiscal Year 2016. In

the drug dealer metaphor, brokers’ interests in feeding investor biases are supported by analysts’ target prices, and

analysts’ methods are in turn supported by the CFA Institute, whose revenue streams derive from (already chartered)

analysts and the firms for which they work. 24

In most respects, the case of Microsoft is similar to the FANG stocks. For details, see

https://www.forbes.com/sites/hershshefrin/2017/12/01/testosterone-driven-rise-in-tech-stocks-reaches-

climax/#31f3f99528f5 which discusses a report on Microsoft from Oppenheimer. One difference is that Microsoft’s

ROIC, since 1995 as well as the previous five years, approximately 24 percent and 15 percent respectively, has been

substantially above the 8.7 percent value of WACC value used in the Oppenheimer report. This raises the question of

whether 2024 is too early as a terminal year for Microsoft, as assumed in the Oppenheimer report.

25

Property, and Equipment; and this forecast assumption requires some serious justification that is

entirely absent in the analyst reports studied here.

Despite evidence that analysts are aware of GOB, there is little indication that financial

firms whose sell side analysts engage in discounted free cash flow analysis have an interest in

mitigating GOB.

Although GOB nudges are straightforward to implement, a combination of agency issues

and behavioral issues plausibly stand as obstacles to financial firms mitigating GOB. Moreover,

as noted earlier, 25 percent of the sell side analysts authoring reports on FAANG stocks carry the

CFA designation. This state of affairs leads to two recommendations.

The first recommendation is for all security analyst reports to contain a section providing

discounted free cash flow-based estimates of fundamental value, including assessments of past

ROIC, forecasts of future ROIC, historical base rate ROIC statistics relative to WACC, growth

reinvestment rates, and valuations technically free of GOB. Moreover, these portions of reports

need to be salient for investors.

The UBS Research report (2017) is written to explain that ratio based valuation analysis

can be consistent with, and therefore correspond to, discounted free cash flow valuation analysis.

Actually, it is difficult to find explicit discussions within analyst reports about making this

correspondence. Nevertheless, analysts relying on ratio based valuation techniques might infer

that such a correspondence is valid, by comparing their target prices with those of analysts who

rely on discounted free cash flow-based valuation. Of course, if the latter succumb to GOB, then

so implicitly will the former.25

25

The above discussion should not be interpreted to imply that that target prices established by analysts who

mitigate GOB will indeed coincide with fundamental value. Analysts are still vulnerable to a wide variety of other

biases. For example, long-term growth rate forecasts of 3 percent, to coincide with the long-term growth potential of

the economy, are likely to be upward biased. In this regard, is it equally likely that a specific firm’s long run growth

26

The behavioral position is that differences between market price and fundamental value

can be large, even if such differences fall to zero in the long run. Remember, that in a behavioral

equilibrium with mispricing, equating target prices and fundamental values might be non-

optimal. However, making fundamental values salient in reports might help investors counteract

motivated reasoning and other psychological phenomena that fuel mispricing, especially stock

market bubbles. It is odd that transparent discounted free cash flow valuation of Apple, Inc., a

firm with the highest market valuation in the world, and with 35 analysts following its stock,

cannot be found on Thomson One during the period under study.

The second recommendation pertains to the CFA Institute, which charters financial

analysts. A case can be made that the Institute has a moral responsibility to highlight GOB in its

programs, publications, and editorial policy. This means making the issue of GOB, and its

possible impact on market mispricing, highly visible. It means publishing articles explaining

GOB. It means articulating strong editorial positions for identifying GOB and implementing

GOB-based nudges. It means documenting the extent of GOB over time. It means revising

Institute sponsored publications to explain vulnerability to GOB in equity valuation and how to

implement GOB nudges. It means taking active positions to mitigate GOB and then holding its

members accountable.

Of course if the drug dealer metaphor applies to the market, then analysts will resist

supplying target prices that implement GOB nudges, the CFA Institute will support the

persistence of GOB, and investors will reject efforts at “rehabilitation” associated with

mitigating GOB. In this case, the market will reflect mutual reinforcing delusions about fair

value, and GOB will persist as a characteristic of equilibrium.

rate will be 50 basis points higher than the growth rate of the overall economy, than 50 basis points lower. Long-

term, only the latter is feasible.

27

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29

Exhibit 1

Amazon DCF Analysis

Morgan Stanley | Amazon DCF Valuation Run-Rate

(USD millions) 2014 2015 2016 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E Projections

Discounted Cash Flow (DCF) Valuation Analysis

Net revenue $88,988 $107,007 $135,987 $165,670 $200,865 $238,331 $278,363 $321,000 $365,737 $412,101 $459,669 $508,060 $523,302

% change Y/Y 20% 20% 27% 22% 21% 19% 17% 15% 14% 13% 12% 11% 3.0%

Adjusted EBITDA $6,553 $10,805 $15,444 $20,802 $27,998 $35,445 $44,070 $51,147 $58,663 $65,055 $69,976 $72,944 $75,133

(-) Cash taxes ($177) ($273) ($413) ($2,125) ($3,579) ($5,392) ($7,678) ($9,736) ($11,558) ($12,963) ($13,900) ($14,149)

(+/-) Changes in working capital $977 $2,556 $3,916 $2,390 $2,312 $2,067 $2,123 $1,894 $1,677 $1,500 $1,231 $1,061

(-) Capex ($4,892) ($4,588) ($6,736) ($8,621) ($10,454) ($12,405) ($14,490) ($16,870) ($19,404) ($21,988) ($24,664) ($27,412)

(-) Stock-based compensation ($1,497) ($2,120) ($2,975) ($3,775) ($4,375) ($4,775) ($5,175) ($5,575) ($5,975) ($6,375) ($6,775) ($7,175)

Unlevered free cash flow (UFCF) $964 $6,380 $9,236 $8,670 $11,903 $14,940 $18,849 $20,860 $23,403 $25,229 $25,868 $25,268 $26,026

% of Revenue 1% 6% 7% 5% 6% 6% 7% 6% 6% 6% 6% 5% 5%

Adj. EBITDA Margin 7% 10% 11% 13% 14% 15% 16% 16% 16% 16% 15% 14% 14%

UFCF / EBITDA 15% 59% 60% 42% 43% 42% 43% 41% 40% 39% 37% 35% 35%

Fair value (one year forward)

PV of FCF 126,093 Equity Value: WACC vs. Perpetual Growth Rate

NPV of terminal value 328,511 6.50% 7.00% 7.50% 8.00% 8.50%

Enterprise value 454,604 2.50% 546,473 486,316 438,318 399,138 366,554

(-) Debt 7,694 3.00% 606,091 531,064 $472,891 426,472 388,575

(+) Cash 25,981 3.50% 685,873 588,758 516,202 459,939 415,039

Equity value 472,891

Fully Diluted Shares 486 Equity Value per Share: WACC vs. Perpetual Growth Rate

Equity value per share $973.00 6.50% 7.00% 7.50% 8.00% 8.50%

Implied terminal EBITDA multiple 8.0x 2.50% $1,124 $1,001 $902 $821 $754

3.00% $1,247 $1,093 $973 $878 $800

DCF valuation assumptions 3.50% $1,411 $1,211 $1,062 $946 $854

Valuation Date One year forward

WACC 7.5%

Perpetual Growth Rate 3.0%

Source: Company data, Morgan Stanley Research estimates; Exhibit 30.

30

Exhibit 2

Amazon Balance Sheet

Balance Sheet | Amazon.com model; Morgan Stanley Report, April 5, 2017

(USD millions) 2015 2016 2017E 2018E 2019E 2020E

BALANCE SHEET

ASSETS

Cash & Cash Equivalents 15,890.00 19,334.00 30,254.60 46,121.50 64,503.10 88,315.60

Marketable Securities 3,918.00 6,647.00 6,647.00 6,647.00 6,647.00 6,647.00

Inventories 10,243.00 11,461.00 15,586.50 20,797.80 26,200.50 31,290.20

Net Accounts Receivable & Other 6,423.00 8,339.00 10,262.60 11,930.80 13,651.30 15,932.80

Deferred Tax Assets 0 0 0 0 0 0

Total Current Assets 36,474.00 45,781.00 62,750.80 85,497.10 111,001.90 142,185.60

Fixed Assets. Gross 30,053.00 36,906.00 45,527.00 55,980.60 68,385.60 82,875.90

Accumulated D&A 8,215.00 7,792.00 18,172.40 31,158.80 46,090.80 62,835.30

Fixed Assets, Net 21,838.00 29,114.00 27,354.60 24,821.90 22,294.80 20,040.60

Deferred Tax Assets 0 0 0 0 0 0

Goodwill 3,759.00 3,784.00 3,784.00 3,784.00 3,784.00 3,784.00

Other Assets 3,373.00 4,723.00 5,812.50 7,038.90 8,346.00 9,740.90

Total Assets 65,444.00 83,402.00 99,701.90 121,141.90 145,426.70 175,751.10

LIABILITIES AND STOCKHOLDERS' EQUITY

Accounts Payable 20,397.00 25,309.00 29,125.30 33,831.50 38,616.30 43,793.70

Accrued Expenses & Other 10,384.00 13,739.00 16,595.00 19,451.00 22,307.00 25,163.00

Unearned Revenue 3,118.00 4,768.00 4,768.00 4,768.00 4,768.00 4,768.00

Interest Payable 0 0 0 0 0 0

Other Liabilities & Accrued Expenses 0 0 0 0 0 0

Current Portion of Long-Term Debt 0 0 0 0 0 0

Total Current Liabilities 33,899.00 43,816.00 50,488.30 58,050.50 65,691.30 73,724.70

Current Liabilities Less CP LTD 33,899.00 43,816.00 50,488.30 58,050.50 65,691.30 73,724.70

Long-term Debt 8,235.00 7,694.00 6,694.00 6,694.00 5,694.00 5,694.00

Other Long-Term Liabilities 9,926.00 12,607.00 12,607.00 12,607.00 12,607.00 12,607.00

Total Liabilities 52,060.00 64,117.00 69,789.30 77,351.50 83,992.30 92,025.70

STOCKHOLDERS' EQUITY

Preferred Stock 0 0 0 0 0 0

Common stock 5 5 5 5 5 5

Treasury Stock -1,837.00 -1,837.00 -1,837.00 -1,837.00 -1,837.00 -1,837.00

Additional paid-in capital 13,394.00 17,186.00 17,186.00 17,186.00 17,186.00 17,186.00

Accum Other Comprehensive Inc -985 -985 -985 -985 -985

Retained Earnings 2,545.00 4,916.00 15,543.60 29,421.40 47,065.30 69,356.30

Total Shareholders' Equity 13,384.00 19,285.00 29,912.60 43,790.40 61,434.30 83,725.30

Total Liabilities + Stockholders' equity 65,444.00 83,402.00 99,701.90 121,141.90 145,426.70 175,751.10

Source: Company data, Morgan Stanley Research estimates; Exhibit 28.

31

Exhibit 3

(USD millions) 2015 2016 2017E 2018E 2019E 2020E

Depreciation and Amortization (D&A) $6,281 $8,117 $10,380 $12,986 $14,932 $16,745

Adjusted EBITDA $10,805 $15,444 $20,802 $27,998 $35,445 $44,070

D&A/EBITDA 58.1% 52.6% 49.9% 46.4% 42.1% 38.0%

Exhibit 4

Amazon.com, Inc. – Discounted Cash Flow Analysis

US$ in millions, unless otherwise stated

2017E 2018E 2019E 2020E 2021E 2022E 2023E '17-'22 '18-'23

EBITDA $14,527.5 $22,687.4 $35,357.1 $51,675.0 $71,883.8 $95,657.6 $122,268.1 45.8% 40.1%

Net Income $1,292.1 $1,810.1 $4,163.9 $7,541.1 $12,041.6 $17,552.7 $23,880.6 68.5% 67.5%

Depreciation & Amortization $11,331.7 $15,963.3 $20,690.7 $25,710.1 $30,881.6 $36,320.6 $41,897.3 26.2% 21.3%

Other Non-Cash Charges (Benefits) $4,246.2 $4,759.9 $5,692.7 $6,679.7 $7,763.7 $8,930.8 $10,161.2 16.0% 16.4%

Interest Expense (Income) $474.2 $611.1 $673.2 $666.1 $638.5 $525.9 $378.6

Changes in Operating Assets & Liabilities $1,976.4 $8,127.5 $8,937.2 $10,646.7 $12,602.2 $14,849.4 $17,285.3 49.7% 16.3%

Unlevered Cash Flows $19,320.6 $31,271.9 $40,157.8 $51,243.6 $63,927.5 $78,179.5 $93,603.0 32.3% 24.5%

Capital Expenditures $21,722.7 $22,811.6 $23,947.5 $24,961.8 $25,848.2 $26,602.7 $27,205.4 4.1% 3.6%

Unlevered Free Cash Flows ($2,402.1) $8,460.3 $16,210.3 $26,281.9 $38,079.3 $51,576.7 $66,397.6 -284.7% 51.0%

Y/Y % Change -175.6% 452.2% 91.6% 62.1% 44.9% 35.4% 28.7%

Weighted Average Cost of Capital 10.5% 10.5%

Perpetual UFCF Growth Rate ("G") 3.0% 3.0%

2017E 2018E

NPV of Unlevered Free Cash Flows $94,858 $147,775

Present Value of Terminal Value $429,950 $553,499

Enterprise Value $524,808 $701,275

Off-Balance Sheet Assets $0 $0

Adjusted Enterprise Value $524,808 $701,275

Year End Net Debt (Cash) ($23,297) ($37,601)

Equity Value $548,104 $738,875

Diluted Shares Outstanding 493.0 501.4

Equity Value Per Share $1,112 $1,474

Source: Company data, Credit Suisse estimates; Figure 14.

32

Figure 5

Figure 18: Amazon.com, Inc. – Balance Sheet, Credit Suisse, July 27, 2017

in millions, unless otherwise stated

2015A 2016A 2017E 2018E 2019E 2020E 2021E 2022E

Assets:

Cash and Cash Equivalents 15,890.0 19,334.0 22,731.6 37,035.7 58,081.8 88,547.8 130,354.3 185,397.4

Marketable Securities 3,918.0 6,647.0 8,248.0 8,248.0 8,248.0 8,248.0 8,248.0 8,248.0

Inventories 10,243.0 11,461.0 12,801.9 14,245.1 15,725.6 17,218.9 18,697.1 20,129.5

Accounts Receivable, Net and Other 6,423.0 8,339.0 10,283.1 11,634.7 13,680.3 15,889.9 18,209.2 20,595.3

Deferred Tax Assets 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total Current Assets 36,474.0 45,781.0 54,064.5 71,163.5 95,735.7 129,904.6 175,508.6 234,370.2

Property and Equipment, Net x x x x x x x x

Goodwill 3,759.0 3,784.0 4,254.0 4,254.0 4,254.0 4,254.0 4,254.0 4,254.0

Other Intangibles 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Deferred Tax Assets 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Other Assets 3,373.0 4,723.0 6,284.4 6,301.9 6,356.8 6,405.5 6,509.5 6,582.0

Total Assets 65,444.0 83,402.0 104,413.1 128,667.3 156,710.2 190,279.9 230,954.6 280,170.8

Liabilities:

Accounts Payable 20,397.0 25,309.0 30,869.7 37,174.4 44,406.2 52,689.7 62,105.7 72,788.7

Accrued Expenses and Other 10,384.0 13,739.0 15,490.0 18,422.3 21,589.6 25,030.1 28,740.7 32,746.0

Unearned Revenue 3,118.0 4,768.0 5,964.5 7,650.0 9,714.2 12,339.7 15,612.8 19,592.4

Interest Payable 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Current Portion of Long-Term Debt 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total Current Liabilities 33,899.0 43,816.0 52,324.3 63,246.7 75,709.9 90,059.5 106,459.2 125,127.1

Long-Term Debt 8,235.0 7,694.0 7,683.0 7,683.0 7,683.0 7,683.0 7,683.0 7,683.0

Other Long-Term Liabilities 9,926.0 12,607.0 14,553.3 19,339.3 23,508.9 27,237.1 30,631.0 33,759.7

Commitments and Contingencies 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Stockholder's Equity:

Preferred Stock 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Common Stock 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

Treasury Stock, At Cast -1,837.0 -1,837.0 -1,837.0 -1,837.0 -1,837.0 -1,837.0 -1,837.0 -1,837.0

Additional Paid-in Capital 13,394.0 17,186.0 25,396.5 32,132.1 39,378.3 47,329.1 56,168.5 66,035.5

APIC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Plug 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Deferred Stock-Based Compensation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Accumulated Other Comprehensive Loss -723.0 -985.0 -607.0 -607.0 -607.0 -607.0 -607.0 -607.0

Retained Earnings 2,545.0 4,916.0 6,895.1 8,705.2 12,869.1 20,410.3 32,451.9 50,004.6

Total Stockholder's Equity 13,384.0 19,285.0 29,852.6 38,398.3 49,808.4 65,300.4 86,181.4 113,601.0

Total Liabilities and Stockholder's Equity 65,444.0 83,402.0 104,413.1 128,667.3 156,710.2 190,279.9 230,954.6 280,170.8

Source: Company data, Credit Suisse estimates

Property and Equipment, Net -- Inferred 21,838 29,114 39,810 46,948 50,364 49,716 44,683 34,965

Property and Equipment, Net -- Inferred, Growth Rate Y/Y 33.3% 36.7% 17.9% 7.3% -1.3% -10.1% -21.7%

Exhibit 6

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FB AMZN AAPL NFLX GOOGL

33

Exhibit 7

Target Price FB AMZN NFLX GOOGL

Morgan Stanley $190 $973 $1,069

Credit Suisse $236 $1,474 $252 $1,349

Jefferies $215 $1,250 $1,200

Cantor Fitzgerald $1,150 $205 $1,100

SunTrust Robinson $210 $1,190 $1,100

Cowen $195 $1,100 $1,050

Mean FV Target Price $209 $1,190 $229 $1,145

Consensus $193 $1,147 $186 $1,053

Mean FV Target Price $209 $1,190 $229 $1,145

Number analysts following 39 39 35 7

Exhibit 8

%-Contribution of TV FB AMZN NFLX GOOGL

Morgan Stanley 67.8% 69.5% 57.5%

Credit Suisse 70.5% 74.9% 86.5% 62.9%

Jefferies 66.7% 62.8% 52.2%

Cantor Fitzgerald 83.2% 89.9% 64.0%

SunTrust Robinson 68.3% 83.7% 60.6%

Cowen 73.3% 61.8% 69.1%

Mean 69.3% 72.6% 88.2% 61.0%

Stdev 2.6% 9.6% 2.4% 5.8%

34

Exhibit 9

Panel A

WACC FB AMZN NFLX GOOGL


Credit Suisse 10.5% 10.5% 11.5% 10.5%

Jefferies 10.0% 12.0% 9.8%



Cowen 10.8% 11.0% 11.0%

Panel B

Assumed Terminal Gr Rate FB AMZN NFLX GOOGL


Credit Suisse 3.0% 3.0% 3.0% 3.0%

Jefferies 3.5% 3.0% 2.5%



Cowen 3.5% 3.0% 3.0%

Exhibit 10

Growth Rate, adjusting for GOB FB AMZN NFLX GOOGL


Credit Suisse 0.4% -3.0% -15.3% 0.6%

Jefferies -1.0% -26.2% 0.9%


SunTrust Robinson 0.1% -0.1% -0.03%

Cowen 1.1% -2.2% 0.1%

35

Exhibit 11

Overvaluation FB AMZN NFLX GOOGL


Credit Suisse 24.3% 55.5% 110.4% 19.7%

Jefferies 57.6% 110.3% 16.8%



Cowen 22.2% 29.6% 25.2%

Mean Overvaluation 30.5% 55.3% 83.1% 30.2%

Cum Ret Rel to Mkt 72.0% 53.6% 92.3% 15.3%

Exhibit 12

5-year ROIC

Mean WACC Arithmetic Mean

FB 9.9% 8.4%

AMZN 10.2% 2.5%

AAPL 7.0% 24.4%

NFLX 10.8% 4.1%

GOOGL 9.8% 12.9%

Exhibit 13

Mean Growth Rates PP&E, Net

FB 61.9%

AMZN 34.3%

AAPL 23.2%

NFLX 54.9%

GOOGL 28.1%

analysts’ fundamental error in the computation of fundamental … annual meetings... · 2018. 3....

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