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1、Investors should consider this report as only a single factor in making their investment decision.For Reg AC certification and other important disclosures,see the Disclosure Appendix,or go to Oppenheimer +44(20)7552-5782 Goldman Sachs International Sharon Bell +44(20)7552-1341 Goldman Sachs Internat

2、ional PORTFOLIO STRATEGY SEPTEMBER 5,2024|5:00AM BSTGLOBAL STRATEGY PAPER NO.70AI:To buy,or not to buy,that is the questionGuillaume Jaisson +44(20)7552-3000 Goldman Sachs International The technology sector has generated 32%of the Global equity return and40%of the US equity market return since 2010

3、.This has reflectedstronger fundamentals rather than irrational exuberance.The tech sectorglobally has seen EPS rise c.400%while all other sectors together haveachieved c.25%from the peak pre-GFC.The introduction of transformative technologies typically attractsgrowing investor interest as well as s

4、ignificant capital and newcompetition.As enthusiasm builds and stock prices increase,the sum ofindividual company valuations can overstate the total potential aggregatereturns;often a bubble develops and bursts.Historically,investors over-focus on the originators,understate theimpact of competition

5、and overstate the returns on capital invested bythe early innovators.At the same time,investors tend to underestimatethe growth of new entrants to the industry that can piggyback off thecapex of others,enabling them to generate new products and services.Valuations often also understate the opportuni

6、ties that can accrue in thenon-technology industries that can leverage the technology to generatehigher returns in existing,as well as in new,product categories.In our view,the technology sector is not in a bubble and is likely tocontinue to dominate returns.However,concentration risks are high andi

7、nvestors should look to diversify exposure to improve risk-adjustedreturns while also gaining access to potential winners in smallertechnology companies and other parts of the market,including in the oldeconomy,which will enjoy the growth of more infrastructure spend.Lilia Peytavin +33(1)4212-1716 G

8、oldman Sachs Bank Europe SE-Paris Branch NoteNote:The following is a redacted version of the original report published September 5,2024 34 pgs.Techs Rational Exuberance Technology has been the most important driver of returns for the equity markets globally since the end of the Global Financial Cris

9、is.Its performance has far outstripped other major sectors,and with good justification.Earnings per share have surged while all industries together,outside of tech,have largely stagnated(Exhibit 1).Increasingly,these powerful returns have been accounted for by a small group of dominant companies,mai

10、nly in the US.These,too,have not reflected irrational exuberance:their earnings growth has dwarfed that of the broader market,justifying their performance(Exhibit 2).The drivers of this success have reflected their ability to leverage software and cloud computing and to fuel high profitability gener

11、ated by extraordinary demand growth in the period since 2010.But their more recent surge in performance since 2022 owes much to the hopes and aspirations around AI.Despite continued powerful earnings growth,valuations have been rising,led by an increasingly narrow group of hyper-scalers.The question

12、 for investors is whether this is becoming a bubble and,even if it is not,whether the risks of such high concentration are creating a dangerous trap for investors,or possibly an opportunity to diversify into potential beneficiaries of these technologies through cheaper companies outside of the domin

13、ant few.Story Time Financial markets reflect and anticipate fundamentals,but sentiment can also play an important role as it does with other fashions and trends in broader life.In equity markets,narratives have the power to attract and direct much-needed capital.However,they can also amplify interes

14、t to the point of monopolising investor attention at the expense of other opportunities,and leading to unrealistic expectations about future profits and leaving companies vulnerable to a sharp de-rating.In recent years,periods of intense speculation have centered on a variety of narratives,ranging f

15、rom the dot-com and the internet boom at the end of the last Exhibit 1:Tech earnings have outstripped those of the global market 12m Trailing EPS(USD).Indexed to 100 on Jan-2009.Exhibit 2:The Magnificent Seven earnings have outstripped the broader US market Magnificent Seven and S&P 500,12m trailing

16、 EPS.Indexed to 100 on Jan-2005 050100150200250300350400450858789919395979901030507091113151719212325World TechnologyWorld Technology,Media,Telecom(TMT)World ex.TMT0500100015002000250030003500050607080910111213141516171819202122232425Magnificent 7S&P 500Sour ce:Dat ast r eam,Wor l dscope,Gol dman Sa

17、chs Gl obal Invest ment Resear chSour ce:Fact Set,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 2Goldman SachsGlobal Strategy Papercentury,to China growth,Cryptocurrency,the Green transition and,most recently,AI.But history reveals a much longer list,much of which revolves around the

18、emergence of new technologies.The interest that new innovations receive has been an important part of directing the necessary capital to grow and commercialise innovations.Very often the technologies behind these periods of speculation have proved to be transformational leading to significant second

19、ary innovations,new products and services,and far-reaching societal changes to the way that we live,work and consume.Along the way,however,the excitement often turns into an obsessive fervor with investors clambering to get exposure to the theme at any price.Thats when bubbles emerge and,eventually,

20、burst.A recent study found that in a sample of 51 major tech innovations introduced between 1825 and 2000,bubbles in equity prices were evident in 73%of cases1.From an investor perspective,the success and eventual impact of an innovation cannot be known at the outset,and it is even more challenging

21、predicting which competitor is likely to succeed over the long run.Consequently,as more new entrants emerge,investors tend to buy multiple companies as options on their future success,leading to the sum of all valuations to overstate the potential returns that can be generated by a technology or ind

22、ustry.The challenge for investors is less about whether they recognise an important innovation or market driver when it emerges,but more about whether they value the potential gains correctly and identify the correct winners and losers.This question is relevant in relation to the current focus on AI

23、 and its potential.While AI is not a new technology,it has captured the imagination of investors and,by association,companies since the launch of Chat-GPT and other large language models.The extraordinary beat on Nvidia investor day in July 2023 sharpened the focus on the potential for the industry.

24、Since then,investors have clamoured for access to the theme and companies have duly responded with record numbers mentioning AI,even in sectors outside of the industry.1Chancellor,E.,and Kramer,C.(2000).“Devil Take the Hindmost:A History of Financial Speculation”.New York:Plume Books.5 September 202

25、4 3Goldman SachsGlobal Strategy Paper Lessons from History;the Market Risks and Opportunities in AI What can history tell us about the life cycle of new innovations and how they impact the stock market?Although it is difficult to generalise,some common characteristics are:A breakthrough technology e

26、merges and reaches commercial scale.nNew companies and capital flood into the space.nSpeculation builds and valuations of companies rise,often resulting in a bubble.nThe bubble bursts,but the technology tends to re-emerge as a principal driver in the neconomy and stock market.The technology/industry

27、 becomes dominated by a few large players.nSecondary innovations emerge,creating new companies and products that leverage nthe initial technology and its increased adoption.Other industries are disrupted by the innovations,forcing incumbents either to adapt nor disappear.The secondary innovations cr

28、eate new employment opportunities and,with them,nnew sources of demand as many of the benefits are passed on to the consumer.Productivity tends to rise,but usually only after the full adoption of this new technology and network effects are realised.Exhibit 3:Companies citing AI spiked following the

29、release of Chat GPT Proportion of S&P 500 firms mentioning“AI”during quarterly earnings calls 0%5%10%15%20%25%30%35%40%45%50%201520162017201820192020202120222023202420252Q2441%Sour ce:GS Dat awor ks,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 4Goldman SachsGlobal Strategy PaperThrou

30、ghout this life cycle there are typically both risks and opportunities for investors.The risks include:Underestimating the impact of competition in driving down returns.1.Overstating the returns on capital invested by the innovators that are 2.developing the technology.The upside opportunities that

31、are often overlooked include:New companies that can utilise the technology to create new goods and 1.services to drive new sources of demand and growth.New markets that open up as a result of the technology.2.Companies outside of the technology space that can benefit from the 3.technology as demand

32、patterns change.The impact of competition When new products or technologies emerge,particularly when they appear transformational,investors tend to underestimate the scale of new competition and its impact on the future returns of the incumbents or originators.There are many useful examples in histo

33、ry that demonstrate the pattern of investor excitement and the promise of high returns leading to a surge of competition and,ultimately,overcapacity that drives down returns.The result is often a large de-rating of companies in the industry and,in some cases,spectacular failures of companies.Neverth

34、eless,this process doesnt usually mark the end of the technology.Mostly,the infrastructure left behind in the wake of the initial investor surge and capex leads to the emergence of new products and services.These are often underestimated or poorly anticipated.Here are some of them:Books,16th Century

35、 The printing press was one of the greatest enabling technologies of all time.Following its invention in 1454,its impact was spectacular.According to research by Buring and Van Zanden2,the number of books published increased from zero to about 3 million per year by 1550 in Europe-more than the total

36、 number of manuscripts produced in the entire 14th century.By 1800,600 million books had been published.As with all technology innovations,the price of books collapsed.Canals,18th Century The innovation of canals for transportation was an important component of the First Industrial Revolution.The fi

37、rst canals built generated strong returns for investors,attracting new inflows of capital that pushed up stock prices and led to a bubble in canal stocks in the 1790s on the London Stock Exchange which peaked in 1793.By the 1800s,2Buring,E.,and Van Zanden,J.L.(2009).“Charting the Rise of the West:Ma

38、nuscripts and printed books in Europe;A Long-Term Perspective from the Sixth through Eighteenth Centuries.The Journal of Economi c Hi story,69(2),409-445.5 September 2024 5Goldman SachsGlobal Strategy Paperthe return on capital in canals had fallen from a pre-bubble peak of 50%to just 5%,and a quart

39、er of a century later only 25%of canals were still able to pay a dividend3.Nevertheless,the canal infrastructure became instrumental in reorganising industries and factories,which,in turn,spawned the growth of many new industries,businesses and products.While many of the original companies failed,th

40、e infrastructure generated strong growth for others.Railways,19th Century A similar exuberance surrounded the growth of railways in the 19th century in the UK,which were to become equally transformative in terms of economic growth,business organisation and societal change.As capital flooded in,there

41、 were nearly 1,240 projects seeking capital by 1845 and the number of miles of network increased from 100 miles in 1830 to 6,123 miles by 18504.A bubble in valuations of railway stocks formed in the 1840s,and by 1850 most stocks had plummeted by an average of 85%from their peak,and the total value o

42、f these shares had dropped to less than half the capital spent on them5.As with the canals,the legacy of the infrastructure became pivotal to growth cities,changing demands for consumer products and other industries that followed.The Telegraph,19th Century The innovation of the telegraph in the mid-

43、1840s had a similar effect.By 1851,there were more than 50 different telegraph companies competing in the US,across the same lines.As the returns fell,most of the firms failed or were consolidated into larger units.Ultimately,Western Union Telegraph took over its two major competitors and became the

44、 first US nationwide monopoly in 1866.The Telephone,20th Century A similar wave of excitement followed the invention and commercialisation of the telephone.The expiration of Bells original patents in 1894 generated a surge of investment and competition.By 1904,60%of American cities with more than 5,

45、000 people had two phone networks.The competition drove a wave of consolidation led by AT&T,which was eventually restricted by an antitrust settlement in 1913 that prevented it from taking over independent phone companies and forced it to give up its controlling share in Western Union Telegraph Comp

46、any.Nonetheless,the constraints on its core business encouraged AT&T to invest in new technologies through its Bell Laboratories subsidiary which became a major innovator in new areas of telecom innovation6.The Radio,20th Century The periods after World Wars I and II(WWI and WWII)saw massive demand

47、for consumer products that attracted waves of investment as new market entrants 3Chancellor,E.,and Kramer,C.(2000).“Devil Take the Hindmost:A History of Financial Speculation”.New York:Plume Books.4Campbell,Gareth(2014).“Government Policy during the British Railway Mania and the 1847 Commercial Cris

48、is”.5Odlyzko,A.(2000).“Collective hallucinations and inefficient markets:The British railway mania of the 1840s”.6Starr,Paul.(2002).“The Great Telecom Implosion”.5 September 2024 6Goldman SachsGlobal Strategy Paperemerged.As broadcast radio took off,for example,demand for radios surged and between 1

49、923 and 1930,60%of US families purchased a radio.In 1920,US broadcast radio was dominated by KDKA,but,by 1922,600 radio stations had opened across the US,supported by the growing advertising industry.A bubble developed and the value of shares in the Radio Corporation of America(RCA),for example,rose

50、 from$5 to$500 in the 1920s but collapsed by 98%between 1929 and 1932,and most radio manufacturers failed,but the industry continued to grow,supported by advertising and the plethora of new consumer products that emerged.The personal computer(PC),20th Century The PC revolution fueled a similar boom

51、in both the number of companies and the valuations of new entrants in the market.While IBM facilitated the widespread commercialisation of the PC,hundreds of companies entered the market in the 1980s.In 1983,however,several companies in the sector announced losses,including Atari,Texas Instruments a

52、nd Coleco.A collapse in PC share prices followed and many PC manufacturers went out of business,including Commodore,Columbia Data Systems and Eagle Computer.While several of the surviving businesses took many years to recover,the industry matured and became dominated by just a few companies.Internet

53、,21st Century This pattern was repeated during the internet bubble of the late 1990s.Speculation grew rapidly as investors began to see the potential of the internet.When search engine company Yahoo!had its initial public offering,its stock rose from$13 to$33 in a single day.Qualcomm shares rose in

54、value by over 2,600%,13 major large-cap stocks increased in value by over 1,000%and another seven large-cap stocks each rose by over 900%in 1999.The Nasdaq index increased fivefold over the period between 1995 and 2000.In just a month after its peak in 2000,the Nasdaq had fallen 34%as hundreds of co

55、mpanies lost 80%or more of their value.The Nasdaq itself fell by nearly 80%by the time it troughed in October 2002.So,there is a fairly consistent historical pattern:radical new technologies tend to attract significant capital and competition.Not all examples in history end with a spectacular bubble

56、,but most do end with a downward adjustment in prices across the industry as returns moderate.Even in cases where a bubble bursts and many companies eventually collapse,this does not mean that the technology itself fails.However,rising competition is central to reducing returns relative to market ex

57、pectations at the peak of the cycle.Eventually the market for the original technology tends to consolidate into a few large winners,and the growth opportunity shifts to secondary innovations or products and services that follow the original technology.With the current dominant companies,the conditio

58、ns are unusual in that most of these were already dominant in the previous wave of technology in particular software and cloud.The scale of profitability that they achieved resulted in them being in a unique position to be able to absorb the very high costs of innovation in the AI space.While the pr

59、otective moats around the current AI winners are significant,and valuations are not bubble-like,the number of new patents in this area is growing rapidly,suggesting that 5 September 2024 7Goldman SachsGlobal Strategy Papernew competitors will emerge and costs will come down.The number of patent fami

60、lies(group of patents that are all related to the same invention or technology)in GenAI has grown from just 733 in 2014 to more than 14,000 in 20237.While the hyper-scalers have huge scale and ability to invest in proprietary AI models,cheaper open source alternatives are emerging at a very rapid ra

61、te.The website Hugging Face,which is a network for enthusiasts,already has around 650,000 models8,suggesting that the typical pattern of large-scale capital growth and competition is happening in the AI space,just as occurred in previous waves of technology.Overstating returns on investment-Telecoms

62、 in the 1990s Just as competition is often underestimated,the returns on capital invested by the innovators are typically overstated.Companies at the epicenter of an innovation often fail to achieve the returns that their high valuations imply as the marginal cost of the technology falls and capacit

63、y increases over time,while a typical overlooked opportunity is that investors understate the returns available to new entrants in an industry that emerge after the initial investments are made that can piggyback off the capex of others.In the case of most major technological innovations throughout

64、history,while the potential may be obvious,it is rarely clear in the early stages what business models will ultimately dominate to scale and commercialise the technology.This was evident in the early days of the internet.While there was widespread and broad speculation in any new company that offere

65、d potential exposure to the industry,the incumbent 7Venditti,B.(2024).“Ranked:Top Companies by Generative AI Patents”.Vi sual Capi tal i st.8“Big techs capex splurge may be irrationally exuberant“.The Economi st(2024).Exhibit 4:By 2022,the number of AI patents granted worldwide exceeded 60,000 Thous

66、ands of AI patents granted globally 2.02.22.62.73.13.53.85.18.115.823.438.362.30102030405060702010201120122013201420152016201720182019202020212022Number of AI patents granted(in thousands)Sour ce:St anfor d HAI Resear ch,Dat a compil ed by Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024

67、 8Goldman SachsGlobal Strategy Paperwinners were generally seen to be the telecom companies.They were viewed as a relatively safe route to the potential fortunes that the internet may generate compared to the more speculative unprofitable dot-com companies.Telecoms had the benefit of being well-esta

68、blished companies,in many cases ex monopolies or state-run enterprises,with low volatility earnings and an existing and large-scale client base.They also had tangible assets and owned and developed fibre optic networks,routers,wireless systems and telecoms equipment that were the underlying infrastr

69、ucture of the internet9.It seemed like they were in a perfect place to receive a high share of the future revenues driven by the internet in e-shopping.But investors significantly overstated the returns on the capital investment that these companies made.This was partly a consequence of new entrants

70、 and partly because of the huge scale of capital invested.Competition was stimulated by de-regulation of the industry,led by the US,which introduced the telecoms act of 1996.The act deregulated the broadcast and telecoms industry in order to provide an environment that could take advantage of the te

71、chnological convergence of these trends and a surge in capital investment followed.According to the Federal Communications Commission,the amount of fibre optic cable laid in the US went from one million miles in 1996 to 10 million by 2000,much financed by debt.When Global Crossing and WorldCom colla

72、psed,they had$25bn and$100bn of debt.A similar pattern occurred across Europe.In the UK,a spending spree occurred after the government allowed 3G spectrum auctions in April 2000 which generated 22.5bn in revenues for the government and similar auctions in Germany raised roughly$30bn.Ultimately,howev

73、er,the capex boom resulted in severe overcapacity in bandwidth for internet usage.While the fixed costs of these new networks were very high,the marginal costs of sending signals over them was very low1011.Increasingly,competition forced prices down and by 2004 the cost of bandwidth had fallen by mo

74、re than 90%,despite internet usage doubling every few years.As late as 2005,as much as 85%of broadband capacity in the US was still going unused.Many companies could not repay their significant debts in the US and some of the auctions for 3G licenses in 1999 had to be re-run because the original com

75、panies that made the bids defaulted on their bids.When the auction was re-run,the bids were only 10%of the original$4bn raised12.Ultimately,the valuation of these companies collapsed,alongside the broader technology bubble.Between 2000 and 2002,the Dow Jones technology index lost 86%and the wireless

76、 communications index dropped 89%with 23 companies going bankrupt in the US alone and the failure of WorldCom became the biggest stock market failure in history with a loss of$102 billion in July 200213.9Starr,Paul(2002).“The Great Telecom Implosion”.10“UK mobile phone auction nets billions”.BBC New

77、s,April 27,2000.11Osborn,Andrew(November 17,2000).“Consumers pay the price in 3G auction”.The Guardi an.12See Ted:https:/ Great Telecom Implosion”.The Ameri can Prospect.5 September 2024 9Goldman SachsGlobal Strategy PaperAs in other examples in history,the problem was not a miscalculation of the gr

78、owth potential of the technology,but rather that investors had attributed too much future value to the companies that had built technology and infrastructure to provide it.In this case,like many others before,the ultimate winners were the companies that could free ride off this spending and utilise

79、the capacity to build business models that could leverage the technology and provide new products and services.Many of these winners did not emerge until the onset of the smart phone in 2006 and the onset of apps which then spawned a growing industry of platform companies,ride sharing,social media a

80、nd so on.History lessons;the opportunity While the market for a technology innovation can become dominated by a few very large companies for a long time,the initial transformative technology becomes a conduit that kickstarts a whole range of other innovations and,with this,new companies and market o

81、pportunities.At the same time,one of the other characteristics of technology is that once new innovations become widely used by companies,the main beneficiary is the consumer who enjoys new products and services at lower prices.For example,while coal and steam were the foundations of the First Indus

82、trial Revolution,a range of other developments quickly followed.Mass migration to cities and the movement away from agriculture resulted in demand for new consumer products.Mechanised looms transformed the textile industry and domestic products such as soaps,which were typically made at home,began t

83、o be manufactured in factories.This generated new markets and became the catalyst for the building of consumer brands,advertising and marketing.During the railway boom,the steam engine spawned the development of the railways,and the network effect and connectivity then allowed other technologies to

84、develop.Similarly,during the Second Industrial Revolution,the harnessing of gas and oil to create electricity was one of the key driving inventions.But this,in turn,enabled the mass production of steel,the development of the internal combustion engine and the automobile.The start of the modern assem

85、bly line in factories became a further innovation,transforming the production and distribution of a range of new products.Similarly,the network impact of the railway boom and the telegraph fostered a host of new market opportunities and companies.With the computer age of the Third Industrial Revolut

86、ion came the rapid acceleration of service industries.The first transistorised consumer products started to appear in 1952,opening new markets as consumers were willing and able to pay a premium for low power consumption and portability.By the mid-1950s,prototype silicon devices were developed in No

87、rthern California.Plastics and lighter materials also generated significant new growth markets,while the growth of multinational companies opened new market opportunities.A similar pattern emerged with the internet as its rapid roll-out and adoption enabled the development and penetration of the sma

88、rtphone.This,in turn,spawned an industry of 5 September 2024 10Goldman SachsGlobal Strategy Papercompanies based on the apps used on these phones(think of the revolution in taxi and food delivery services,for example)and the internet of things(a world of connected appliances and devices).So,while th

89、e leading tech today will most likely remain dominant in their respective markets,rapid innovation,particularly around machine learning and AI,will likely create a new wave of tech superstars.It is probable that AI and robotics will not only create new faster-growing innovative companies but also ra

90、ise the prospect of major restructuring gains in non-technology sectors.AI Is Still Not in a Bubble.but Diversification Is Important Despite the significant interest that AI has generated,it still does not appear to have driven a bubble in valuations which sets it apart,so far at least,from previous

91、 narrative investment cycles like the internet in the late 1990s.The dominant companies are less likely to be in a bubble if we compare their valuations to other periods.Current valuations are much lower than have been typical in other recent bubble periods,stretching back to the Nifty 50 era of the

92、 early 1970s,the Japanese bubble in the late 1980s and indeed the technology bubble in 2000(Exhibit 5).For example,the median PE and EC/Sales of the 7 biggest technology companies today is roughly half that of the dominant 7 at the peak of the technology bubble in 2000.5 September 2024 11Goldman Sac

93、hsGlobal Strategy Paper Perhaps more importantly,however,the current dominant companies are much more profitable and have stronger balance sheets than those that dominated during the tech bubble(Exhibit 6).Exhibit 5:Dominant companies today are not as expensive as those in previous bubble periods in

94、 history Market weightMarket Cap($Bn)*24m fwd P/E*24m fwd EV/SalesMagnificent 7(2024)Apple7.3%338726.57.7Microsoft6.6%304325.79.4NVIDIA5.7%264924.113.2Amazon4.0%185025.42.5Alphabet3.9%180816.62.0Meta Platforms2.4%111819.25.5Tesla1.4%67255.44.9Magnificent 7(2024)Aggregate31.3%1452723.95.0Tech Bubble

95、Leaders(2000)Microsoft4.5%58153.219.2Cisco Systems4.2%543101.717.5Intel3.6%46542.111.5Oracle1.9%24584.619.0IBM1.7%21823.52.3Lucent1.6%20637.94.1Nortel Networks1.5%19986.46.4Tech Bubble Leaders(2000)Aggregate19.0%245752.08.2Japan Financial Bubble(1989)Nippon Telegraph and Telephone6.9%157100.1Industr

96、ial Bank Of Japan4.6%105154.2Sumitomo Mitsui Banking3.4%7749.2Bank of Tokyo-Mitsubishi3.3%7549.8Fuji Bank3.1%7152.8Dai-Ichi Kangyo Bank2.9%6544.0Sakura Bank2.8%6262.1Japan Financial Bubble(1989)Aggregate27.0%61367.0Nifty 50(1973)IBM7.1%4835.5Eastman Kodak3.6%2443.5Sears Roebuck2.7%1829.2General Elec

97、tric2.0%1323.4Xerox1.8%1245.83M1.4%1039.0Procter&Gamble1.4%929.8Nifty 50(1973)Aggregate19.9%13534.3SizeValuation*Act ual (LTM)P/E and EV/Sal es dat a fr om 02/01/1973 for Nift y 50.*LTM P/E dat a and EV/Sal es fr om 27/12/1989 for Japan Financial Bubbl e.*24m fwd P/E and EV/Sal es dat a fr om 24/03/

98、2000 for Tech Bubbl e.Sour ce:Dat ast r eam,Fact set,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 12Goldman SachsGlobal Strategy Paper Over-investment risks While the dominant companies may have justifiable valuations based on their current and expected cash flows,there remains a ris

99、k that they will not achieve the returns on their investment that the market currently assumes.From the late 1990s,software and,later,cloud computing were able to be highly effective in leveraging the technologies with very high margins and low capex.The era of ultra-low interest rates following the

100、 financial crisis rewarded these business models relative to traditional industry that had very high capital invested but achieved low returns(see Exhibit 7).Most of the AI hyper-scalers emerged out of these successes and have the scale and cash flows to invest.Nevertheless,the AI winners of today a

101、re no longer capital-light businesses.Just as we saw with the networking companies of the internet,AI is driving a major capex boom and threatens to stifle the high rates of returns that have characterised the sector over the past 15 years and which current valuations imply will continue.Exhibit 6:T

102、he current dominant companies are much more profitable and have stronger balance sheets than those that dominated during the tech bubble Next 12 month estimate for Big Tech&last 12 months for Tech Bubble Fundamentals Cash as%of Market CapNet Debt to EquityReturn on Equity(%)Net Income Margin(%)Magni

103、ficent 7(2024)Microsoft6.6%3.0%-20%27%35%Apple7.3%1.8%-32%146%27%Nvidia5.7%3.7%-61%65%53%Amazon4.0%8.6%-21%17%9%Alphabet3.9%4.0%-29%27%28%Meta Platforms2.4%4.2%-23%27%34%Tesla1.4%4.3%-25%12%9%Magnificent 7(2024)Aggregate31.3%4.2%-30%46%28%Tech Bubble Leaders(2000)Microsoft4.5%3.0%-63%35%39%Cisco Sys

104、tems4.2%0.4%-17%22%17%Intel3.6%2.5%-33%26%25%Oracle1.9%1.0%-61%39%15%IBM1.7%2.7%111%39%9%Lucent1.6%0.9%38%36%9%Nortel Networks1.5%1.1%-3%-1%-1%Tech Bubble Leaders(2000)Aggregate19.0%1.7%-4%28%16%Market Weight(%)Sour ce:Dat ast r eam,Fact set,Gol dman Sachs Gl obal Invest ment Resear ch5 September 20

105、24 13Goldman SachsGlobal Strategy Paper Many leading tech companies are now ramping up their spending at an extraordinary rate.According to Alphabet,spending on capex was$12bn in Q1 2024,driven overwhelmingly by investment in our technical infrastructure,with the largest component for servers,follow

106、ed by data centers.For the year it expects a similar run rate,so close to$50bn.A new forecast from the International Data Corporation(IDC)Worldwide Artificial Intelligence Spending Guide shows that global spending on AI,including software,hardware and services for AI-centric systems,is expected to g

107、row at a compound annual growth rate(CAGR)of 27%over the 2022-2026 forecast with spending on AI-centric systems expected to surpass$300 billion in 2026.Nvidia has predicted that$1 trillion will be invested by 2027 in data center upgrading alone.The hyper-scalers alone now represent 23%of total S&P 5

108、00 capex and R&D.Exhibit 7:Capital-light businesses have significantly outperformed those that employ heavy capital World Capital vs.Non-Capital intensive.Price return(USD)-Capital intensity based on:Assets/Employee,Assets/Net Income,and CAPEX/Net Income.050010001500200025009092949698000204060810121

109、41618202224Capital IntensiveNon Capital Intensive Capit al-int ensive:El ect r icit y,Indust r ial Mat er ial s,Aut omobil es and Par t s,Gas,Wat er and Mul t i-ut il it ies,Indust r ial Met al s and Mining,Tel ecommunicat ions Ser vice Pr ovider s,Leisur e Goods,Const r uct ion and Mat er ial s,Oil

110、 Equipment and Ser vices.Non-capit al-int ensive:Technol ogy Har dwar e and Equipment,Medical Equipment and Ser vices,Phar maceut ical s and Biot echnol ogy,Househol d Goods and Home Const r uct ion,Bever ages,Food Pr oducer s,Ret ail er s,Tobacco,Soft war e and Comput er Ser vices,Per sonal Goods.S

111、our ce:Dat ast r eam,Wor l dscope,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 14Goldman SachsGlobal Strategy Paper Investors have become increasingly confident about the future revenues in both semiconductors and hardware enablers.Perhaps surprisingly,despite all the capital investe

112、d in technology,there is little evidence that the age of the intellectual property assets are rising.Indeed,since the start of this century,estimates suggest the age is declining(Exhibit 10).Usage of ChatGPT has continued to grow,whether looking at numbers of visits or time spent(Exhibit 11).The ris

113、k is that as competition increases,the returns and margins begin to fade,and the growth rates of many of the current dominant companies will likely adjust lower.Nevertheless,there are some reasons to be more hopeful that in previous technology cycles.Importantly,while capex is rising sharply,our US

114、strategy team notes that capex relative to cash flows is less alarming.At the height of the Tech Bubble,TMT stocks were spending more than 100%of cash flows from operations(CFO)on capex and R&D.Today,the capex and R&D as a share of CFO equals 72%currently in Exhibit 8:AI investment has surged over t

115、he past several years Global actual and forecast revenues by AI-exposed sector,4Q2019=100 Exhibit 9:The market has significantly upgraded its AI investment expectations across the AI hardware stack Change in consensus global revenue forecasts since March 2023,$bn,annualised 8010012014016018020022024

116、02602019202020212022202320242025SemiconductorsHardware Enablers(ex.Semis)Software Enablers0501001502002503003504004505001Q242Q243Q244Q241Q252Q253Q254Q25SemiconductorsHardware Enablers(ex.Semis)Sour ce:Fact Set,Gol dman Sachs Gl obal Invest ment Resear ch Sour ce:Fact Set,Gol dman Sachs Gl obal Inves

117、t ment Resear ch Exhibit 10:US average age of fixed asset Intellectual Property Exhibit 11:ChatGPT,total minutes spent by users (old chaptgpt website)and (new website),Worldwide data on comScore(total minutes spent,in billions)3.94.14.34.54.74.95.15.35.5192519371949196119731985199720092021US average

118、 age of fixed assets intellectual property0123456Jan 2023Apr 2023Jul 2023Oct 2023Jan 2024Apr 2024Jul 2024CHATGPT.COMOPENAI.COM Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch This char t r epl aces t he one incl uded or iginal l y in t his r epor t,which was based on number of vis

119、it s r at her t han minut es spent,and did not incl ude t he new websit e dat a.As such,it inaccur at el y showed a fal l-off in Chat GPT visit s.Sour ce:comScor e5 September 2024 15Goldman SachsGlobal Strategy Paperthe US,compared with a 40-year median of 67%.Furthermore,as our technology analysts

120、have argued,the significant step-up in capex may actually generate strong returns and,by comparison,may not be very different from what we saw with the cloud innovations.They reflect on the 2013-2016 time frame when Microsoft was spending aggressively on capex to build out Azure when,at one point,gr

121、oss margins for Azure were negative but then became hugely profitable.They argue that Microsoft Gen-AI revenues($5-6 billion annualised)have scaled more rapidly compared to Azure,which took roughly 7 years to get to comparable levels.Though capex intensity is up sharply overall for the leading AI te

122、ch companies,today it is still roughly where we were in the Azure cycle at comparable revenues.Additionally,while capex has increased,and expectations of future revenues have accelerated,the period of payback on cash flows embedded in current valuations remains much lower than it was at the peak of

123、the technology bubble in 2000(Exhibit 12).AI and the Risk of Concentration While these companies may be less highly valued than in other narrative-led bubble periods,the scale of market dominance is greater this time.The 10 biggest stocks have their highest share of the market for many decades at ov

124、er one third of the index,while the five biggest companies are worth 26%of the total value of the S&P 500(Exhibit 13).Exhibit 12:The period of payback on cash flows embedded in current valuations remains much lower than it was at the peak of the technology bubble in 2000 The number of years of free

125、cash flow of the equity market required to acquire its own market capitalisation in each year 010203040506070809010096979899000102030405060708091011121314151617181920212223S&P 500 TechS&P 500STOXX 600142 years221 years We use t odays FCF,assuming no gr owt h in fut ur e FCF and not discount ing fut

126、ur e cash flows Sour ce:Fact set,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 16Goldman SachsGlobal Strategy Paper This,again,may not be irrational.The power of the dominant companies to generate shareholder returns and compound over time is a feature that has been recognised in much

127、 of the literature on the subject.Bessembinder14,for example,conducted a study of all 26,168 companies in the US that had publicly listed equity since 1929 and found that,over time,while aggregate wealth creation had been$47.4 trillion,the majority reduced shareholder wealth.He also found that the e

128、xtent to which stock market wealth creation is concentrated in a few companies has increased over time.One of the reasons for this may be the growing issue of scale required in dominant technology platforms,particularly when it comes to compute power and R&D spending.Furthermore,the scale of the inv

129、estments required to ramp up in this industry preclude some smaller competitors,particularly now that interest rates have increased and the cost of capital is higher.Nevertheless,with markets being increasingly dependent on the fortunes of so few,the collateral damage of stock-specific mistakes is l

130、ikely to be particularly high.Furthermore,other leading companies in other sectors,or parts of the World,enjoy lower volatility than these companies.This is true,for example,for the GRANOLAS(a list of 11 dominant companies in Europe).Prior to the market correction in July,the Magnificent 7 stocks ha

131、d explained around 50%of the S&P 500s returns(Exhibit 15).14Bessembinder,Hendrik(2020).“Wealth Creation in the U.S.Public Stock Markets 1926 to 2019”.SSRN El ectroni c Journal.Exhibit 13:The current scale of market dominance is greater than in other narrative-led bubble periods Market value of the b

132、iggest companies of the S&P 500 as percentage of the index market value 5101520253035408588919497000306091215182124Market share of top 5 companiesMarket share of top 10 companies26%35%Sour ce:Dat ast r eam,Compust at,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 17Goldman SachsGlobal

133、Strategy Paper Is high stock concentration a big risk?Historically,with new entrants emerging,few companies remain unscathed as competition either forces companies to disappear,merge or be acquired.From this perspective,a market that becomes dominated by a few stocks becomes increasingly vulnerable

134、to either disruption or anti-trust regulation.Even companies that have enjoyed near monopoly power in the past have ultimately succumbed to these pressures.Standard Oil,for example,controlled over 90%of oil production in the US by 1900 nand 85%of sales.Bell Telecom had reached 90%of US households by

135、 1969.Just before it nrelinquished control of the Bell Operating Companies and was split into different companies in 1982,it reached 5.5%of the market.General Motors earnings were more than 10%of the S&P 500 between 1955 and n1973.At its peak,General Motors had a 50%market share in the US and was th

136、e worlds largest automaker from 1931 through to 2007.IBM became dominant in mainframe computers in the 1970s and had over a 60%nmarket share in mainframe computers in 1981.Microsoft became dominant in PCs,and by 2000 had a 97%share in operating nsystems in the PC and laptop markets.There are,for exa

137、mple,only 51 companies that have appeared every year in the Fortune 500 since 1955.In other words,just over 10%of the Fortune 500 companies in 1955 have remained on the list during the 69 years through this year15.Based on this history,it would appear reasonable to assume that when the Fortune 500 l

138、ist is released 70 years from now in the 2090s,almost all of todays top companies will no longer exist 15Oppeheimer,P.,Jaisson,G.,Bell,S.,von Scheele,M.,and Peytavin,L.(2024).“The Concentration Conundrum;What to do about market dominance”.Gol dman Sachs Gl obal Investment Research,Gl obal Strategy P

139、aper.Exhibit 14:The realised volatility of the GRANOLAS is on average 2x lower than for the Magnificent 7 1-year realised volatility of daily returns Exhibit 15:The contribution of the Magnificent 7 and of GRANOLAS to aggregate index returns is very high 0%5%10%15%20%25%30%35%40%45%18192021222324Mag

140、nificent 7GRANOLAS50%34%48%35%51%48%0%10%20%30%40%50%60%70%Magnificent 7GRANOLASContribution to Index ReturnsYTD3 years ago5 years ago Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch Magnificent 7 incl ude:Micr osoft,Al phabet,Amazon,Appl e,Met a,NVIDIA,Tesl a;GRANOLAS incl ude:GS

141、K,Roche,ASML,Nest l e,Novar t is,Novo Nor disk,LOr eal,LVMH,Ast r aZeneca,SAP,Sanofi Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 18Goldman SachsGlobal Strategy Paperas currently configured and will be replaced by new companies in new,emerging industries that we

142、 cant even imagine today.This process sometimes accelerates or slows down but since 1980,for example,more than 35%of S&P 500 constituents have turned over during the average 10-year period,largely reflecting innovation.Of the current top 50 companies in the US,only half were in the top 50 a decade a

143、go,and many did not even exist before the 1990s(NVIDIA(1993),Amazon(1994),Netflix(1997),PayPal(1998),Alphabet(1998),Salesforce(1999),Tesla(2003)and Facebook(2004).More recently Nvidia has grown at an extraordinary pace,becoming the worlds biggest company from a relatively small base just a few years

144、 ago.As a result of changes in leadership and,by implication,growth,history would suggest that buying dominant companies generates lower returns over time.For example,Exhibit 17 shows the total return on average since 1980 that would have been achieved by buying and holding the top 10 stocks over di

145、fferent time horizons(from 1 year out to 10 years),while Exhibit 18 shows the same in relative returns(compared with the S&P 500).These data suggest that,while absolute returns remain good for the dominant companies,these strong returns fade over time,and they often remain solid compounders.Importan

146、tly,however,the returns are generally negative for dominant companies if an investor buys and holds them as other faster-growing companies come along and outperform.Exhibit 16:Only 51 companies have remained in the Fortune 500 list since 1955 Only these 51 companies have been in the Fortune 500 sinc

147、e 19553MCrown HoldingsHoneywell InternationalO-I Glass(Owens-Illinois)Abbott LaboratoriesCumminsHormel FoodsPaccarAltria GroupDanaIBMPepsiCoArcher Daniels MidlandDeereInternational PaperPfizerAlcoaDowJohnson&JohnsonPPG IndustriesBoeingEli LillyKelloggProcter&GambleBristol-Myers SquibbExxon MobilKimb

148、erly-ClarkRaytheon TechnologiesCampbell SoupGeneral DynamicsKraft-Heinz Rockwell AutomationCaterpillarGeneral ElectricLockheed MartinS&P GlobalChevronGeneral MillsMerckTextronCoca-ColaGeneral MotorsMotorola SolutionsWeyerhaeuserColgate-PalmoliveGoodyear Tire&RubberNorthrop GrummanWhirlpoolConocoPhil

149、lipsHersheyOwens Corning Sour ce:Amer ican Ent er pr ise Inst it ut e,Dat a compil ed by Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 19Goldman SachsGlobal Strategy Paper None of this means that these companies would necessarily be poor investments.They may well remain good compounde

150、rs,be more defensive and enjoy lower volatility and higher risk-adjusted returns.However,it does suggest that:1)The dominant companies are unlikely to be the fastest-growing companies over the next decade.2)The stock-specific risk in the index is currently very high,suggesting an increasing pay-off

151、through diversification.Exhibit 17:Absolute returns remain good for dominant companies.Average forward realised absolute return(US Top 10 companies).Since 1980 Exhibit 18:.but they generally underperform(over the long run)Average forward realised relative return(US Top 10 companies).Since 1980 12.9%

152、10.7%10.1%9.4%8.6%0%2%4%6%8%10%12%14%1y.fwd2y.fwd3y.fwd5y.fwd10y.fwd-0.13%-1.5%-2.0%-2.3%-2.3%-3%-2%-1%0%1y.fwd2y.fwd3y.fwd5y.fwd10y.fwd Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear chLeadership changes-Music and m

153、arkets Narrative-led trends in markets,while often backed by quality fundamentals,can also be seen in other areas of life.Whether it is in fashion,art,music or stock markets,leaders rarely stay dominant forever and what is most sought after does not stay constant.In music for example,Taylor Swift,is

154、 now the largest-selling artist.She also made history by being the first artist since the charts began in 1958 to take all top 10 songs on Billboard Hot 100 with her album Midnights in 2022,overtaking the previous winner,Drake,who had 9 of the 100s top 10 in 2021.So new leadership is not confined to

155、 the stock market.Indeed,just as with stocks,there are the long-term staples those that stay dominant in their category,or large over long periods of time.The Beatles have the most Hot 100 singles of anyone over time(20),while Mariah Carey has the most as a solo artist(19 as well as the only artist

156、to have a No.1 in four distinct decades).But these artists are now not growing their downloads in the same way as Taylor Swift is today.It is similar in the stock market.Some of the greatest leaders have disappeared,some stay as household names,but new leaders emerge and can become dominant very qui

157、ckly.There are 5 companies in the top 10 today that were in the top 10 in 2015,3 that were in the top 10 in 2010 and just 1 that featured in the top 10 in 2005.In the music charts,there are 3 artists in the current top 10 that were also in the top 10 in 2015,3 in 2010 and none that were in the top 1

158、0 in 2005.5 September 2024 20Goldman SachsGlobal Strategy Paper Exhibit 19:The 10 largest S&P companies through time By market cap on 31 December IBMIBM2.9%General Electric2.6%General Electric4.1%Exxon MobilExxon Mobil2.9%AT&T2.2%Exxon Mobil2.6%General ElectricGeneral Electric2.3%Exxon Mobil2.2%Pfiz

159、er2.5%Philip MorrisPhilip Morris2.2%Coca-Cola2.0%Cisco Systems2.4%General MotorsRoyal Dutch Shell1.9%Merck&Co1.8%Citigroup2.2%AmocoBristo-Myers Squibb1.6%Philip Morris1.7%Walmart2.0%Royal Duch ShellMerck&Co1.6%Royal Dutch Shell1.6%Microsoft2.0%Du PontWalmart1.6%Procter&Gamble1.2%American Internation

160、2.0%AT&TAT&T1.5%Johnson&Johnson1.2%Merck&Co1.8%ChevronCoca-Cola1.4%IBM1.1%Intel1.7%General Electric3.3%Exxon Mobil3.2%Apple3.3%Apple7.0%Exxon Mobil3.1%Apple2.6%Alphabet2.5%Nvidia6.4%Citigroup2.2%Microsoft1.8%Microsoft2.5%Microsoft6.4%Microsoft2.1%General Electric1.7%Exxon Mobil1.8%Alphabet6.2%Procte

161、r&Gamble1.7%Chevron1.6%General Electric1.6%A3.8%Bank of America1.6%IBM1.6%Johnson&Johnson1.6%Meta Platforms A2.4%Johnson&Johnson1.6%Procter&Gamble1.6%A1.5%Eli Lilly1.8%American Internation1.6%AT&T1.5%Wells Fargo1.4%Broadcom1.6%Pfizer1.5%Johnson&Johnson1.5%Berkshire Hathaway1.4%Tesla1.4%Philip Morris

162、1.4%JPMorgan Chase1.5%JPMorgan Chase1.4%JPMorgan Chase1.2%19851990199520002005201020152024 Sour ce:Amer ican Ent er pr ise Inst it ut e,Dat ast r eam,Dat a compil ed by Gol dman Sachs Gl obal Invest ment Resear ch Exhibit 20:Best-Selling music artists globally Thousands of yearly certified record sa

163、les for 1985-2015;billions of Spotify global streams for 2023 Madonna25,803 Michael Jackson16,077 Michael Jackson19,988 Backstreet Boys26,625 Michael Jackson25,187 Madonna14,657 Garth Brooks18,113 Eminem25,177 Bruce Spingsteen18,634 Queen13,760 Whitney Houston16,438 Celine Dion20,933 Prince15,839 El

164、ton John13,599 Bon Jovi14,176 Mariah Carey20,554 Elton John 14,114 Bruce Springsteen11,476 Madonna12,842 Garth Brooks16,011 Phil Collins12,124 Metallica9,979 Mariah Carey11,803 Britney Spears15,993 Dire Straits11,056 Phil Collins9,699 Metallica11,920 Christina Aguilera13,942 Elvis Presley10,701 Elvi

165、s Presley9,072 Guns N Roses11,068 Whitney Houston13,307 Billy Joel10,674 Billy Joel8,867 Celine Dion10,759 Madonna11,788 Queen10,638 The Beatles8,610 Queen9,762 Elton John11,021 Eminem32,651 Rihanna59,112 Drake70,853 Taylor Swift29.1 Lil Wayne18,909 Kesha49,083 Bruno Mars62,436 Bad Bunny16.4 Jay-Z18

166、,186 Taylor Swift31,959 Ed Sheeran57,973 The Weeknd14.1 Mariah Carey15,868 Flo Rida30,972 Taylor Swift53,352 Drake14.0 Garth Brooks14,313 Eminem27,473 Justin Bieber52,044 Peso Pluma10.5 Britney Spears13,378 Lady Gaga16,615 Rihanna41,349 Feid7.9 Maroon 513,101 Chris Brown22,008 Katy Perry37,772 Karol

167、 G7.4 Whitney Houston11,024 Drake22,156 Chris Brown34,771 SZA7.1 Celine Dion10,857 Kanye West21,555 Kanye West28,453 Kayne West6.9 Madonna10,737 Katy Perry21,436 Nicki Minaj28,399 Lana Del Rey6.9 19851990199520002005201020152023 Sour ce:St at ist a,Dat a is Beaut iful,RIAA,IFPI,Dat a compil ed by Go

168、l dman Sachs Gl obal Invest ment Resear ch5 September 2024 21Goldman SachsGlobal Strategy PaperThe risk of anti-trust regulation In addition to the risk of competition and failure to adapt,regulatory pressures pose a risk for very dominant companies with increasingly monopolistic power(see:US Econom

169、i cs Anal yst:Concentrati on,Competi ti on,and the Anti trust Pol i cy Outl ook,18 July 2021)and the recent collapse in many Technology companies performance in China illustrates this.The tech sector and internet platforms have become a major political focus in both the US and China the markets with

170、 the highest concentration of large-cap Technology stocks.The most recent news on the DOJ subpoena of Nvidia in its antitrust probe,and the share price reaction,is an example of the impact that such news can have on highly rated growth companies.Social attitudes towards tech companies may also be ch

171、anging as they are seen increasingly as gaining huge profits while employing relatively few people.The continued rise in the profit share of GDP relative to the labour share of GDP leads(Exhibit 21)into the narrative that many of the most profitable companies need reigning in,or taxing more.Many of

172、these companies that were historically difficult to tax are becoming easier targets as they build up large data centers and physical capital.As Exhibit 22 shows,their profits have increased by much more than their tax rates in recent years.Governments will be keen to find new sources of tax revenue

173、and the increasingly high energy demands of the major technology leaders might be seen as a justification for higher taxes.According to the International Energy Agency,data centers already account for about 1%to 1.5%of global electricity use16.Our US strategists analysis of company stock performance

174、 following previous antitrust lawsuits by the DoJ and FTC shows that revenue growth slowed,valuation compressed and shares underperformed the overall index(Exhibit 23,Exhibit 24).However,the cases took years to resolve and share price response was often muted during the initial stages.The most promi

175、nent examples include AT&T,where a break-up was mandated by a consent decree following eight years of litigation(1974-82);MSFT,where a settlement was reached involving a consent decree and changed business practices 16Leffer,L.(2023).“The AI Boom Could Use a Shocking Amount of Electricity”.Exhibit 2

176、1:US profit and labour share of GDP Exhibit 22:Technologys share of net income has increased relative to the share of taxes paid Ex Diversified Financial Services,Investment Trusts and Real Estate(USD)50515253545556575859-2024681019291942195519681981199420072020Profit Share(%)Labour Share(%,RHS)0%2%

177、4%6%8%10%12%14%16%18%20%80 82 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20 22 24Information Technology as a%of MSCI WorldProfitTax share Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch Sour ce:Fact Set,Dat ast r eam,Wor l dscope,Gol dman Sachs Gl obal Invest ment Resea

178、r ch5 September 2024 22Goldman SachsGlobal Strategy Paperfollowing three years of litigation(1998-2000/01);and IBM,where no formal action was taken after 13 years of litigation(1969-82)see:US Equi ty Vi ews:Equi ti es,anti trust,and the“i nesti mabl e”val ue of due process,13 July 2021.Nevertheless,

179、we see three reasons why dominant tech companies may stay bigger for longer in the current cycle than we might have seen in historical technology cycles:1)The tech sector is deflationary(Exhibit 25).As long as that is the case,there is no real incentive for politicians to attack it.In this way,the t

180、ech sector from a policy perspective may be different from others,such as banks,supermarkets or energy companies,where politicians often argue that the benefits(for example of higher interest rates for savers,or lower food and energy prices)are not being passed on to consumers.This does not make tec

181、hnology companies immune from regulation,but it is more likely to come from issues around privacy and use of data,or the impact on mental health,than on pricing.Exhibit 23:Historical examples of regulatory scrutiny AT&T and IBM relative valuation reflect LTM P/B vs.S&P 500 median.Microsoft relative

182、valuation reflects NTM P/E vs.Info Tech median.Average sales growthRelative valuationCompanyLawsuit filingResolutionYears ResolutionPre-resolutionPost-resolutionChangeLawsuit filingAt resolutionChangeAT&T197419828Breakup10%4%-6%1.3 x0.9 x-31%Microsoft19982000/20012-3Consent decree39%10%-29%1.8 x0.9

183、x-50%IBM1969198213No formal action14%5%-9%4.9 x1.9 x-61%Sour ce:Gol dman Sachs Gl obal Invest ment Resear ch Exhibit 24:Relative valuation following antitrust lawsuit filing Change in relative valuation.Based on trailing P/B.IBM and MSFT relative to Info Tech.AT&T relative to S&P 500.-80%-60%-40%-20

184、%0%20%40%-80%-60%-40%-20%0%20%40%024681012141618202224Months since lawsuit filingMSFTAT&TIBM Sour ce:Compust at,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 23Goldman SachsGlobal Strategy Paper 2)Technology is increasingly seen as an issue of national security.Technology,including cy

185、ber security,chips and increasingly AI,are seen as a critical part of national infrastructure and strategic defense.This has become more important as geopolitical tensions rise across the world,making it less likely that a government would support anti-trust legislation that undermines a competitive

186、 lead.For example,the US in its Foreign Direct Product Rule(FDPR)allows US officials to control the flow of foreign products built with US-originated technology.IBM recently has announced the closure of its China R&D operation with the loss of 1,000 jobs,and there are recent news reports that ASML w

187、ill put more curbs on its China business.3)The technology sector invests hugely in R&D.Given that the current incumbent winners are so cash-generative,they have an ability to maintain this investment,strengthening their market moat and also potential future growth.According to Erik Brynjolfsson,Prof

188、essor and Senior Fellow at the Stanford Institute for Human-Centered AI,the top 10%of firms by market value account for over 60%of this intangible digital investment(see Top of Mi nd:The post-pandemi c f uture of work,29 July 2021).“Theyre pulling further away from firms at the median and bottom,so

189、that inequality is growing over time.Thats leading to a winner-take-most outcome in which superstar firms are harvesting most of the gains from new technologies rather than those insights diffusing evenly throughout the economy.And thats also happening at the level of individuals and workers the lab

190、our share of income has fallen in recent decades,and the top 1%is getting ever wealthier as they capture a growing share of total income”.Our analysts also see significant opportunities for secondary growth opportunities in cloud computing coming from AI.They estimate that the Cloud Software TAM(Iaa

191、S,PaaS,and SaaS)could approach$2 trillion by 2030(CAGR:22%,2024-2030).Their analysis suggests Gen-AI spending could constitute 1015%of the Cloud Software Exhibit 25:The tech sector is deflationary US Communication CPI vs All CPI(1997=100)4060801001201998200220062010201420182022US Communication CPI v

192、s ALL CPI Sour ce:Haver Anal yt ics,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 24Goldman SachsGlobal Strategy Papermarket($200-$300bn)as spending gradually extends beyond the hyper-scalers and foundation model providers to become more pervasive across all three layers of the tech s

193、tack(see:Gen-AI Part VIII:Catal yst or Cul pri t?,25 Aug 2024).Opportunities for Diversification Ex Tech Compounders(ETCs)While technology may not be in a bubble,the characteristics of large cap technology can be found in a more diverse and diversified portfolio.It is true that few companies match t

194、he earnings growth that the largest tech companies have been enjoying;however,there are plenty of companies that do have high margins and returns on investment,reinvest for future growth and have strong balance sheets that exist outside of the tech sector.We call these the Ex Tech Compounders,or ETC

195、s.We have put together a list of global ETCs,which can be found in the Appendix.The list looks for companies that have market caps above$10bn and have high margins(EBITDA 14%,EBIT 12%,Net Income 10%),high profitability(ROE 10%),strong balance sheets(ND/Equity 75%,ND/EBITDA 2x),low volatility(Vol 4%a

196、nd earnings 8%)and have consistently grown their earnings over the past decade.As Exhibit 26 shows,the ETCs have outperformed the global market over the past year and have kept pace with the performance of the Magnificent 7.The valuation of our global ETCs list is in line with its average since 2016

197、 and the list trades at the lowest premium to the world stock market since 2018.Healthcare and Biotech One area likely to benefit from AI and the ability to analyse large data sets is healthcare and bio technology.We have already seen very dramatic reductions in the costs of DNA sequencing(Exhibit 2

198、8)with the cost of sequencing an entire gnome falling from$100 Exhibit 26:The Global Ex Tech Compounders(ETCs)have outperformed the global market over the past year.Total return performance.Indexed to 100 on Jan-21.Exhibit 27:.and since 2015 Ex.Tech Compounders(ETCs).Relative total return performanc

199、e.80100120140160180200220Jan-21Jul-21Jan-22Jul-22Jan-23Jul-23Jan-24Jul-24GRANOLASMagnificent 7Ex.Tech Compounders(cap-weighted)MSCI AC World9010011012013014015016017018019015161718192021222324Ex.Tech Compounders(cap-weighted)vs.MSCI AC World Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment R

200、esear ch Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 25Goldman SachsGlobal Strategy Papermillion in 2001 to$50 in 202217.The pace of this reduction far outpaces Moores law and suggests a significant increase in the productivity and cost of developing new medici

201、nes and therapeutic discoveries().AI has also been instrumental in speeding up data processing in the development of vaccines.For example,linearFold,an algorithm for ribonucleic acid(RAN)secondary structure recognition,increased the speed times for Covid-19 sequencing from 55 minutes to 27 seconds18

202、.The healthcare industry and biotech have significantly underperformed large cap US tech companies in recent years,suggesting that the opportunities are not fully reflected in valuations(Exhibit 29).Our healthcare analysts believe that AI can accelerate synthetic data generation for drug development

203、 and diagnostics,generating designs for novel drugs,personalised medicine,diversity and equity in healthcare,manufacturing and supply chain efficiency,and approval and launch materials.Banks and Financial Services Our analysts see:1)Enhanced coding efficiency,2)Data extraction:Synthesise data and co

204、ntent from large datasets or documents,3)Chatbots,4)Automation,5)Human/AI collaboration.In Europe,for example,our banks team estimate the potential AI adoption uplift to ROE at c.200bp(excluding the upfront investment required).They highlight the AI impact is most clearly driven by numerous modest c

205、ost gains,with the cost opportunity c.3x the revenue opportunity.Consumer Products and Services Academic work points to only a small proportion of the social returns from technological advances over the 1948-2001 period being captured by producers,indicating that most of the benefits of technologica

206、l change are passed on to consumers rather than captured by producers.These results indicate that the bubble of 17National Human Genome Research Institute(2024).“DNA Sequencing Costs:Data”.18Baidu Research(2020).“Opening up worlds fastest RNA structure prediction algorithm to the scientific communit

207、y to support battle against coronavirus”.Exhibit 28:Cost of sequencing DNA of one human genome USD Exhibit 29:The healthcare industry and biotech have significantly underperformed large cap US tech companies in recent years Total return performance.Indexed to 100 on Jan-21.10010001000010000010000001

208、0000000100000000200020042008201220162020 Cost per Genome(USD)Moores Law80100120140160180200220Jan-21Jul-21Jan-22Jul-22Jan-23Jul-23Jan-24Jul-24Magnificent 7MSCI World HealthcareMSCI World Biotech Sour ce:Nat ional Human Genome Resear ch Inst it ut e,US Nat ional Inst it ut e of Heal t h,Dat a compil

209、ed by Gol dman Sachs Gl obal Invest ment Resear ch Sour ce:Dat ast r eam,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 26Goldman SachsGlobal Strategy Papernew-economy stocks in the 1990s resulted from the alchemist fallacy19.This was evident in the case of the internet.Waves of new pr

210、oducts and services emerged in the years after the bubble burst with the emergence of the smart phone and apps.Arguably,many of these products did not answer an urgent problem that needed to be solved but rather developed new products that then created demand ride-sharing,platform business,social me

211、dia and so on.It is likely that a similar pattern will develop with AI.Robotics and Cyber Security According to Cybercrime Magazine,cybercrime would have a value equivalent to the third-largest economy globally,at$10.5 trillion annually by 2025,while Statistica suggests it will rise to$13.8 trillion

212、 by 2028.The demand for cyber security will rise dramatically and AI can help in this process.Current processes cannot keep up with the volume of malware,estimated at around 1 billion programmes with 560,000 new pieces each day according to DataProt20.AI automation can help to detect and differentia

213、te between those that are most harmful21.Our analysts expect Security vendors to emerge as beneficiaries across both the infrastructure and application layers as well as within data posture investments as security continues to trend higher as a percentage of total budgets.In robotics,a whole range o

214、f other applications driven by emerging companies might become large markets autonomous driving,for example,or humonoid robotics,enhanced by AI.Already advances are evolving rapidly and according to industry estimates the global market for humanoid robots could reach 214bn by 203222.Of course,it is

215、not possible to anticipate what these products may be or who is likely to develop them,but that is another reason for ensuring broad diversification in equity exposure as well as balanced portfolios have access to private markets where many of the nascent companies may be.Ethics and nostalgia market

216、s In past technology cycles,the second-round impacts on work and society often drive new areas of consumer growth.It is likely,for example,that more AI will mean more demand for fact-checking services.The ability to work more productively from home may mean the regentrification of shopping and enter

217、tainment in neighbourhoods close to large-density populations.The growth of artificial immersive entertainment may also boost demand for experiences in the real world.This might reflect the growing popularity of goods and services that are seen as authentic or nostalgic.Retro crafts are growing in p

218、opularity,whether it be the growth reality TV programmes where 19Nordhaus,William D.(2005).“Schumpeterian Profits and the Alchemist Fallacy”.Yal e Economi c Appl i cati ons and Pol i cy Di scussi on Paper No.6,SSRN El ectroni c Journal.20Jovanovic,B.(2024).“A Not-So-Common Cold:Malware Statistics in

219、 2024”.DataProt.21Morgan,Steve(2020).“Cybercrime To Cost The World$10.5 Trillion Annually By 2025”.22The Brainy Insights(2023).“Humanoid Robot Market Size Worth$214.4 Billion by 2032:The Brainy Insights”.5 September 2024 27Goldman SachsGlobal Strategy Papercontestants compete in baking,spelling,sowi

220、ng or even ballroom dancing competitions.These fashions are spreading into retail.According to Grand View Research,for example,the market for so-called artisanal bakery products was valued globally at$95.13 billion in 2022 and is likely to grow at a compound rate of 5.7%from 2023 to 203023.The focus

221、 on sustainability and interest in the past together create new consumer markets.According to research conducted by GlobalData for ThredUP,a US second-hand store,the resale clothes market is growing at 15 times the rate of traditional retail24.According to a report by Statistica,as of 2021,42%of mil

222、lennials and Gen Z respondents stated that they were likely to shop for second-hand items25.A similar trend has emerged in transport with the growth in the sharing economy and the growth of cycle,scooter and car sharing.Few would have predicted the steady growth in the bicycle market a decade ago;th

223、e global bicycle market was valued at over$64 billion in 2022 and is expected to grow at a compound rate of 9.7%from 2023 to 203026.Perhaps even more striking is how the bicycle is outselling the car.Analysis of 30 European countries by the Confederation of the European Bicycle Industry(CONEBI)and t

224、he European Cyclists Federation(ECF)suggests that,at the current trajectory,10 million more bikes will be sold per year in Europe by 2030,representing a rise of 47%compared with 2019.On this basis,the 30 million bikes sold annually in Europe would be more than double the annual sales of cars27.Ethic

225、ally produced products and services is also a growing market and AI can help.Research from Bain found that 7%of consumers in rich developed countries are willing to pay a premium for sustainably sourced products and brands28.AI can help develop a supply chain inventory,making it easier for companies

226、 to prove provenance and quality of their components and ingredients.In the 21st century,in a highly digitalised world where almost everyone is connected to the internet and the cutting edge of technology threatens to displace jobs and companies,it is meaningful that one of the biggest company in Eu

227、rope is LVMH.This is a company that sells the value of heritage in historic brands.It was formed in 1987 through the merger of two old companies:Louis Vuitton(founded in 1854)and Moet Hennessey,which itself was a merger in 1971 between Moet&Chandon,the champagne producer(founded in 1743)and Hennesse

228、y,producer of cognac(founded in 1765).According to its website,the company develops the brands that perfectly encapsulate all that they have embodied for our customers for centuries.23Grand View Research(2023b).“Artisanal Bakery Products Market Size,Share and Trends Analysis Report,20232030”.24Thred

229、Up 2024 Resale Report.25Smith,P.(2022).“Female consumer willingness to buy secondhand apparel by age worldwide 2019”.Stati sta.26Grand View Research(2023a).“Bicycle Market Size,Share and Trends Analysis Report,20232030”.27Sutton,M.(2020,December 2).“Annual bike sales to run at more than double new c

230、ar registrations by 2030”.Cycl i ng Industry News.28Faelli,F.,Blasbeg,J.,Johns,L.,and Lightowler,Z.(2023).“Selling Sustainability Means Decoding Consumers”.Bai n&Company.5 September 2024 28Goldman SachsGlobal Strategy PaperAs the ubiquity of technology increases and individuals increase their relian

231、ce on technology as they communicate via networks,the value they place on authenticity and human connectivity which can evoke a nostalgic image of a simpler,pre-digital life is likely to grow.This is true across many product categories,including food.The old economy and infrastructure Increasingly,t

232、he ambitions of large cap tech companies are dependent on greater electricity generation and infrastructure.Many of the companies that stand to benefit from this trend are in the old economy and have much lower valuations,having stagnated and disappointed for many years.AI could continue to boost re

233、turns in the Technology space,but for these companies to fulfill their potential,they will need huge increases in electrical power(and,with it demand for infrastructure spend and copper).Our analysts estimate that data center power demand is poised to grow 160%by the end of the decade,which should d

234、rive a significant acceleration to a level of electricity growth in the US and Europe not seen in a generation(see GS Sustai n:AI/data centers gl obal power surge and the Sustai nabi l i ty i mpact,28 April 2024).After stagnating over the last decade,our US utilities analysts expect US electricity d

235、emand to rise at a 2.4%compound annual growth rate(CAGR)over 2022-2030,with data centers accounting for roughly 90bp of that growth,and data centers will likely more than double their electricity use by 2030.This implies that the share of total US power demand accounted for by data centers will incr

236、ease from around 3%currently to 8%by 2030,translating into a 15%CAGR in data center power demand from 2023-2030.A similar trend is in play in Europe and Asia.Our European utilities analysts also expect a secular capex supercycle ahead with European investments in power grids accelerating by 80-100%,

237、depending on the region.And on the renewables front,they expect Europe to add nearly 800 gigawatts(GW)of wind and solar over the coming 10-15 years,nearly tripling the amount currently installed in the region(see:Gen AI:Too much to spend,too l i ttl e benefit?,25 June 2024).Decarbonisation and an en

238、ergy transition is what is needed to generate this power.But to do this,a capex super cycle is needed that will benefit many of the left-behind value sectors.5 September 2024 29Goldman SachsGlobal Strategy PaperAppendix Criteria for Global Ex.Tech Compounders:Constituents of MSCI AC World nExcludes

239、GS Sell-rated companies nLarge cap(Mkt Cap$10bn)nHigh margins(EBITDA 14%,EBIT 12%,Net Income 10%)nHigh profitability(ROE 10%)nStrong balance sheets(ND/Equity 75%,ND/EBITDA 2x)nVolatility(5y Realised Vol 4%and earnings 8%2y forward CAGR)and nconsistently grown their earnings over the past decade Base

240、d on consensus estimates n5 September 2024 30Goldman SachsGlobal Strategy Paper Exhibit 30:Ex.Tech Compounders Ex.Tech CompoundersNameGICS SectorUS vs.Non-USRegionCountryMarket Cap($bn)12m fwd P/EEli LillyHealth CareUSNorth AmericaUnited States903.245.9Novo Nordisk BHealth CareNon-USEuropeDenmark456

241、.034.2LVMH Moet Hennessy Louis VuittonConsumer DiscretionaryNon-USEuropeFrance356.520.9AstraZenecaHealth CareNon-USEuropeUnited Kingdom266.219.3NovartisHealth CareNon-USEuropeSwitzerland260.815.1Kweichow Moutai AConsumer StaplesNon-USAsia/Pacific Ex JapanChina247.218.6Hermes InternationalConsumer Di

242、scretionaryNon-USEuropeFrance243.745.6LOrealConsumer StaplesNon-USEuropeFrance232.329.5LindeMaterialsUSNorth AmericaUnited States226.028.6Intuitive SurgicalHealth CareUSNorth AmericaUnited States171.765.9InditexConsumer DiscretionaryNon-USEuropeSpain165.524.0StrykerHealth CareUSNorth AmericaUnited S

243、tates137.227.7Honeywell InternationalIndustrialsUSNorth AmericaUnited States133.719.2Vertex PharmaceuticalsHealth CareUSNorth AmericaUnited States123.039.9Boston ScientificHealth CareUSNorth AmericaUnited States120.330.9EatonIndustrialsUSNorth AmericaUnited States115.226.8Automatic Data ProcessingIn

244、dustrialsUSNorth AmericaUnited States112.027.1Air LiquideMaterialsNon-USEuropeFrance108.025.3FAST RETAILINGConsumer DiscretionaryNon-USJapanJapan101.039.5CSLHealth CareNon-USAsia/Pacific Ex JapanAustralia99.129.7NIKE BConsumer DiscretionaryUSNorth AmericaUnited States96.925.2FerrariConsumer Discreti

245、onaryNon-USEuropeItaly94.351.4Zoetis AHealth CareUSNorth AmericaUnited States83.029.4CintasIndustrialsUSNorth AmericaUnited States80.446.7Hindustan UnileverConsumer StaplesNon-USAsia/Pacific Ex JapanIndia79.557.3Cie Financiere RichemontConsumer DiscretionaryNon-USEuropeSwitzerland79.319.5Daiichi San

246、kyoHealth CareNon-USJapanJapan79.247.3Trane TechnologiesIndustrialsUSNorth AmericaUnited States77.729.2ITC LtdConsumer StaplesNon-USAsia/Pacific Ex JapanIndia75.428.0Parker-HannifinIndustrialsUSNorth AmericaUnited States73.822.1ChipotleConsumer DiscretionaryUSNorth AmericaUnited States72.945.7Copart

247、IndustrialsUSNorth AmericaUnited States51.332.6SikaMaterialsNon-USEuropeSwitzerland50.431.1Oriental LandConsumer DiscretionaryNon-USJapanJapan49.746.0Monster BeverageConsumer StaplesUSNorth AmericaUnited States47.625.7HOYAHealth CareNon-USJapanJapan47.532.6WW GraingerIndustrialsUSNorth AmericaUnited

248、 States46.323.6ExperianIndustrialsNon-USEuropeUnited Kingdom43.829.1Old Dominion Freight LineIndustrialsUSNorth AmericaUnited States41.930.6Edwards LifesciencesHealth CareUSNorth AmericaUnited States41.724.7UltraTech CementMaterialsNon-USAsia/Pacific Ex JapanIndia39.835.8Grupo Mexico BMaterialsNon-U

249、SLatin AmericaMexico39.79.2WEGIndustrialsNon-USLatin AmericaBrazil39.735.0AMETEKIndustrialsUSNorth AmericaUnited States38.724.1IDEXX Laboratories IncHealth CareUSNorth AmericaUnited States38.641.4Howmet AerospaceIndustrialsUSNorth AmericaUnited States38.231.5Asian PaintsMaterialsNon-USAsia/Pacific E

250、x JapanIndia36.957.5ResMedHealth CareUSNorth AmericaUnited States36.026.6BeiersdorfConsumer StaplesNon-USEuropeGermany35.628.3Ingersoll RandIndustrialsUSNorth AmericaUnited States35.425.1Veeva Systems AHealth CareUSNorth AmericaUnited States34.833.0ASSA ABLOY BIndustrialsNon-USEuropeSweden33.722.1Ma

251、rtin Marietta MaterialsMaterialsUSNorth AmericaUnited States31.225.3Vulcan MaterialsMaterialsUSNorth AmericaUnited States30.927.9CelltrionHealth CareNon-USAsia/Pacific Ex JapanKorea30.839.9HEICO AIndustrialsUSNorth AmericaUnited States30.146.2Aena SMEIndustrialsNon-USEuropeSpain30.114.0lululemon ath

252、leticaConsumer DiscretionaryUSNorth AmericaUnited States29.817.6Nestle IndiaConsumer StaplesNon-USAsia/Pacific Ex JapanIndia29.167.5WabtecIndustrialsUSNorth AmericaUnited States28.620.7DexComHealth CareUSNorth AmericaUnited States27.936.2TerumoHealth CareNon-USJapanJapan27.728.9ANTA Sports ProductsC

253、onsumer DiscretionaryNon-USAsia/Pacific Ex JapanChina27.214.2Axon EnterpriseIndustrialsUSNorth AmericaUnited States26.865.6FortiveIndustrialsUSNorth AmericaUnited States25.218.5RollinsIndustrialsUSNorth AmericaUnited States24.545.8STERISHealth CareUSNorth AmericaUnited States23.725.5Aristocrat Leisu

254、reConsumer DiscretionaryNon-USAsia/Pacific Ex JapanAustralia23.121.3Straumann HoldingHealth CareNon-USEuropeSwitzerland22.634.6Deckers OutdoorConsumer DiscretionaryUSNorth AmericaUnited States22.628.5EvolutionConsumer DiscretionaryNon-USEuropeSweden21.015.5Sonova HoldingHealth CareNon-USEuropeSwitze

255、rland20.926.3SymriseMaterialsNon-USEuropeGermany18.732.3GenmabHealth CareNon-USEuropeDenmark18.420.1Nongfu Spring HConsumer StaplesNon-USAsia/Pacific Ex JapanChina17.520.3Expedia GroupConsumer DiscretionaryUSNorth AmericaUnited States17.110.1James Hardie CUFSMaterialsNon-USAsia/Pacific Ex JapanAustr

256、alia16.023.4MonclerConsumer DiscretionaryNon-USEuropeItaly15.921.2NordsonIndustrialsUSNorth AmericaUnited States14.225.4CochlearHealth CareNon-USAsia/Pacific Ex JapanAustralia13.045.7Neurocrine BiosciencesHealth CareUSNorth AmericaUnited States12.620.6TeleflexHealth CareUSNorth AmericaUnited States1

257、1.616.3Fortune Brands InnovationsIndustrialsUSNorth AmericaUnited States9.517.3Median39.728.0 Sour ce:Dat ast r eam,Fact Set,Gol dman Sachs Gl obal Invest ment Resear ch5 September 2024 31Goldman SachsGlobal Strategy PaperDisclosure Appendix Reg AC We,Peter Oppenheimer,Guillaume Jaisson,Sharon Bell

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