RESEARCH

TITLE GOES HERE: DISRUPTIVE INNOVATION: SECONDARY TITLE NEW METRICS NEW MARKETS, ARK INVESTMENT INVEST IN COLLABORATION M ANAGEMENT IN COLL ABORATION AUTHOR WITH DR. OR ARTHUR PARTNER B. LAFFER, AND LAFFER ASSOCIATES

RESEARCH WHITE PAPER BY CATHERINE D. WOOD, CEO ARK INVEST

The attached paper explores some of the broad thematic research areas upon which ARK Investment Management is focused today. These subjects fit squarely in the macro realm that portfolio managers should understand when analyzing investment opportunities. Like changes in economic policy, nonlinear changes in technology can have dramatic effects on industries across the globe. Update: November, 2016

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD1 AND ARTHUR B. LAFFER

SUMMARY

INTRODUCTION

•

Disruptive technological innovations can have profound ramifications on industries, as well as the entire economy. A number of such nonlinear changes are in process today, set to increase wealth and productivity dramatically.

•

The automotive industry is approaching a profound inflection point. Soon the demand for electric vehicles (EVs) will begin to outpace that for gasoline powered cars.

•

Shared autonomous vehicles—via lower costs per mile, enhanced safety, and great convenience—will put downward pressure on annual new car sales.

During the next few years, not only will disruptive innovation continue to change the way the world works, but it could render traditional gauges of economic activity inaccurate. Just a gleam in the eye of the bubble fifteen years ago, the convergence of technological breakthroughs is in full force today. The combination of general purpose technology platforms—the mobile cloud, robotics, batteries, DNA sequencing, and blockchain—is likely to increase productivity and enhance wealth dramatically during the next five years. While the tech and telecom bubble raised what now look like legacy stocks to ridiculous heights, in many ways it actually underestimated how profoundly the world would change and, with few exceptions, missed who would lead the charge.

•

As artificial intelligence solves increasingly complex problems, higher returns on investment will increase adoption of automation. While this will cause short-term dislocations, ultimately it will increase living standards substantially.

•

Rapidly declining costs in DNA sequencing will change the course of health care and decrease costs in the system.

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Low cost and unable to be counterfeit, cryptocurrencies will become an accepted means of payment, creating upheaval in the financial intermediary market and also exerting pressure on central banks.

1

In this paper, we hope to illustrate how the digital world will continue to permeate the physical world, challenging the relevance of many economic statistics. For example, with the help of autonomous electric vehicles, smarter robots, and the cloud, “the sharing economy” will increase the utilization of fixed assets, shrinking demand in some sectors while boosting total factor productivity and returns on invested capital. At the same time, science and technology will take the guesswork out of health care as DNA sequencing cracks the code of life, driving quality up and costs per capita down, and potentially changing the slope of unfunded health care liabilities. Likewise, as competitive cryptocurrencies shake out, evolving as a means of exchange and a store of value, they could pose a serious challenge to the monetary policies and fiat currencies that have lost their way in the aftermath of the 2008 financial crisis.

Catherine Wood is Chief Executive Officer and Chief Investment Officer of ARK Investment Management, a money manager focused on investing in promising areas of disruptive innovation and nonlinear change. Prior to founding ARK, Catherine was Chief Investment Officer of Global Thematic Strategies at AllianceBernstein.

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

AUTOS WILL GO ELECTRIC The automotive industry is approaching a profound inflection point: by 2022 the demand for electric vehicles (EVs) will begin to outpace that for gasoline powered cars.2 As the cost of lithium-ion cells falls faster than most analysts have anticipated and the cost to manufacture traditional Internal Combustion Engine (ICE) powertrains increases, ARK’s analysis suggests that 200-mile range EVs will cost less than the majority of ICE vehicles within five to seven years. If 200-mile range EVs were to accommodate the travel needs of 80% of Americans,3 then the current consensus forecasts of the demand for EVs will miss the mark considerably in 2020. Accounting for roughly 20% of the total cost of an EV, battery economics will be critical to future EV adoption.4 As lithium-ion battery prices decline during the next few years, the cost of ICE powertrains — also accounting for roughly 20% of an auto’s cost — will rise primarily because of more stringent efficiency and emission regulations.5 Currently, EVs sell at a premium to comparable ICE vehicles, but ARK anticipates that a 200-mile range EV with the same amenities as today’s best-selling Toyota Camry will sell at a lower price point by 2022, as shown below.6

FIGURE 1

Projected Price Parity for 200-Mile Range EV and Toyota Camry

200 Mile Range EV

MSRP $60,000 $50,000

$49,900 $41,800

$40,000 $30,000

Toyota Camry MSRP

$31,000 $22,700

$23,100

$23,900

$22,400 $24,700

$20,000 $10,000 $-

2013

2016

2019

2022

Source: NADA Guides, ARK Investment Management LLC

2

ARK Investment Management LLC: https://ark-invest.com/research/electric-vehicles — Some EV forecasts will group hybrid electric vehicles, plug-in hybrid electric vehicles, battery electric vehicles, and extended-range electric vehicles (or some combination of those). ARK uses EV to refer to battery electric vehicles only.

3

Roughly 60% of the U.S. population does not travel long distance in an average year. Among those consumers who do, more than half travel fewer than 200 miles per trip. U.S. Department of Transportation: https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/subject_areas/national_household_travel_survey/index.html

4

ARK Investment Management LLC. http://insideevs.com/tesla-battery-in-the-model-s-costs-less-than-a-quarter-of-the-car-in-most-cases/

5

The Future of the North American Automotive Supplier Industry: Evolution of Component Costs, Penetration, and Value Creation Potential Through 2020 http://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/automotive%20and%20assembly/pdfs/the_future_of_the_north_american_automotive_supplier.ashx

6

ARK Investment Management LLC. ARK’s expectation for EV MSRP parity is largely based on decreasing lithium-ion battery costs and increasing ICE powertrain costs. Other factors could influence MSRP. The MSRP prices shown do not include any government subsidies.

DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

Incorporating the savings associated with lower maintenance and fuel costs, ARK anticipates that the crossover price point will occur even sooner, perhaps before 2020, as is illustrated below. Given a spike in gasoline prices, the total ownership cost of an EV could drop below that of a Toyota Camry within two years.

FIGURE 2

Projected Price Parity Point for 200-Mile Range EV - Inclusive of Five Year Total Cost of Ownership 200 Mile Range EV MSRP + 5 Year Total Cost of Ownership

2014 MSRP + 5 Year Total Cost of Ownership

4

$50,000

Toyota Camry MSRP + 5 Year Total Cost of Ownership 2016

2017 2018

$40,000

2019 2020

$30,000

2021

2022

$20,000 $10,000 $180

175

170

165

160

155

150

145

140

135

130

125

120

115

110

105

100

$/kWh Source: NADA Guides, ARK Investment Management LLC

Based on ARK’s research, a 200-mile range EV will be comparable in price and feature-set to a Toyota Camry by 2021, after which time EVs will extend their competitive pricing advantage. In 2022, ARK expects the cost of a 200-mile EV to drop below $23,000 placing it at a lower price point than 50% of passenger cars sold in the U.S., and just under 50% of those sold globally. Once EVs and ICE based cars approach price parity, the adoption of EVs should accelerate rapidly. Based on their forecasts, however, many well-known institutions are not anticipating price parity or broad based EV adoption anytime soon. Not surprisingly, OPEC’s official forecast is that EV sales will drop to 100,000 units in ten years while the more objective Energy Information Administration (EIA) projects that they will top 2,000,000 units. In stark contrast, ARK projects that annual EV sales will approach 17 million DEFAULT for2020s, axis asand labels: units in the early shown in Figure 3.

Tw Cen MT, Regular, 7-8pt Axis Color = RGB 90,90,90 6

The EIA estimate is extrapolated from its U.S. estimate.

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

FIGURE 3

Annual EV Sales Estimates

18,000,000

17,000,000

16,000,000 14,000,000 12,000,000 10,000,000 8,000,000 6,000,000 2014

4,000,000 2,000,000

2,000,000 330,000

100,000

2015 Global EV Sales

2022 OPEC Annual EV Sales

-

2022 EIA Annual EV Sales

2022 ARK EV Sales Estimate

Source: Source: International Energy Agency, OPEC, Energy Information Administration, ARK Investment Management LLC

Given the significant demand that ARK anticipates, EV adoption is likely to be supply constrained. Based on known battery factory expansion plans through 2020, ARK believes production will satisfy demand for fewer than 1.3 million 200-mile EVs. As the magnitude of the opportunity becomes clear, ARK expects companies like Tesla, Panasonic, Samsung, LG Chem, and GS Yuasa to invest aggressively and fill the void. In a supply-constrained market, the winners are likely to be auto manufacturers with EV manufacturing and design expertise, battery manufacturers able to scale and capitalize on the opportunity, and consumers who will benefit from better performing cars at lower price points. Needless to say, in all likelihood oil and oil service companies will be vulnerable to a substantial and prolonged decline in global oil demand.

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

AUTO SALES WILL FALL IN A VIBRANT “SHARING ECONOMY” While auto sales have been one of the most important gauges of economic well-being historically, the sharing economy and autonomous vehicles could strip them of that role during the next five to ten years. Thanks to web-enabled services like Uber, Lyft, and Zipcar, household vehicles are beginning to feel like the stranded assets they are: high in cost, but utilized roughly 5% of the time on average in a 24-hour day.7 Based on various studies, 8 ARK estimates that sharing services could increase vehicle utilization by eight- to twelvefold,9 activating stranded assets and boosting the efficiency of the U.S. capital base. “Mobility-as-a-service”10 looms as a significant challenge to the auto sector. Individuals who typically would buy a car after landing a first job, or two cars after moving to the suburbs, are rethinking the economics of those decisions given the burst in alternative means of transportation.11 ARK believes that shared car services like Uber and Lyft already may have made a dent in auto sales volumes. According to ARK’s research, during the past three years, ridesharing services have caused a cumulative loss of 100,000 in car sales in the US and are on track to take another 190,000 from auto manufacturers this year.12 Autonomous taxis could push this trend into overdrive, especially if —regulation permitting— Google, Tesla or other competitors deliver a fully autonomous vehicle by 2019.13 ARK estimates that US auto sales will be cut nearly in half by 2025 as autonomous taxi services take off (Figure 4). Sales should level off in the late 2020s at roughly 11 million units at an annual rate compared to 17-18 million today. At that time, autonomous cars sold to fleet operators could dominate urban auto sales. Further, the used car market will be flooded as owners shed truly stranded assets. FIGURE 4

Annual US New Car Sales Millions

Introduction of autonomoaus cars

20 16

...Then as autonomous taxis gain share, urban auto sales will drop to record low levels.

Shared car services slowly eat away at auto sales.

12

Autonomous car sales first drive auto sales higher as the blind, the elderly, and young teens now have more transportation options.

8 4

Auto sales will level off as urban auto sales are comprised primarily of autonomous taxis.

35 20

33

32

31

30

34 20

20

20

20

20

29 20

27

26

28 20

20

24

25

20

20

20

23 20

22 20

20

19

18

17

21 20

20

20

20

20

16 20

15

0 20

6

Sources: ARK Investment Management LLC, Kleiner Perkins Caufield Byers

7

Source: http://www.reinventingparking.org/2013/02/cars-are-parked-95-of-time-lets-check.html

8

Sources: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_108.pdf ; http://sustainablemobility.ei.columbia.edu/files/2012/12/Transforming-Personal-Mobility-Jan-27-20132.pdf

9

We get this factor of 8 from comparing that 4% calculated above to the rented time per vehicle in Zipcar’s last quarterly report. This method will somewhat overstate the utilization of shared cars, but since other studies have given ratios more like 15:1, we are still confident that this is a conservative estimate.

10 Mobility as a service can be defined as transportation modes that are consumed as a service as opposed to personally owned vehicles. For example, taxis fit this category. 11 Examples: http://www.businessinsider.com/how-using-uber-and-lyft-saves-me-money-2015-2; http://www.geekwire.com/2016/ditched-car-went-full-uber/; http://www.nytimes.com/2014/06/12/technology/personaltech/with-ubers-cars-maybe-we-dont-need-our-own.html

Notes: The number of cars per US household peaked in 2007 at 2.07, and is now less than 2. Source: http://greatergreaterwashington.org/ post/21444/the-american-cities-with-the-most-growth-in-car-free-households/

12 Assumes half of the miles driven in mobility as a service today account for incremental forgone auto sales.

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

The catalyst for this trend will be the unbeatable cost and convenience of autonomous taxis, or shared autonomous vehicles (SAVs). As shown in Figure 5, the current cost to own and operate a personal car is $0.70 per mile driven, including depreciation, gas, parking, financing, insurance, maintenance, registration, taxes and tire replacement. For many people, parking and speeding tickets add regularly to these costs. While SAVs still have a few years of technological and regulatory hurdles to jump, if on the road today we believe SAVs would be far more economical than taxis, not to mention cost competitive with personal vehicles, thanks to much higher utilization rates, as shown in the Figure 6. When they do hit the road, given their high technology content and the declining cost curves which typify technology, SAVs will become more compelling over time. By the end of the decade, costs could be cut in half to $0.35 per mile.14 FIGURE 5

Cost Per Mile of a Personally Owned Car ($ per mile)

$0.70

Tires Registration & Taxes

$0.60

FIGURE 6

Costs Per Mile of Taxis, Personal Cars, and Shared Autonomous Vehicles ($ per mile) 3.47

Maintenance & Repair Insurance

$0.50

Financing $0.40

Parking

$0.30

Fuel (gas)

$0.20 Depreciation

$0.10

0.70 0.35

$0.00 Personal Car

Average US Taxi

Personal Car

Shared Autonomous Car 2020

SOURCE: ARK Investment Management LLC, Bankrate, Edmunds, AAA, Turbotax, IHS, the Earth Institute at Columbia University, Love to Know Cars, USA Today, Small Business Taxes and Management, CNET, About.com, Wisegeek, Transforming Personal Mobility Report, A/N Group, Inc.

Yet, cost is just one of the benefits of shared autonomous vehicles. Others, such as safety, convenience, and discretionary time may cement the case for SAVs after they pass regulatory scrutiny. Safety is the most serious of these considerations. Human error contributes to 90% of all auto accidents in the United States today.15 Consequently, U.S. regulators may be swayed sooner than most analysts believe by arguments that autonomous vehicles could prevent more than 27,000 deaths per year.16 ARK believes the value proposition here is clear, and it will become clearer as regulators pave the way and as SAV costs decline. 13 Given the published improvement rate of the Google car, ARK’s analysis shows that autonomous technology will be ready in 2-3 years. ARK believes regulation will not be a impediment. Note that NHTSA has said that it agrees with Google that cars in the future will not have human drivers. Sources: vcom/cars/2016/02/googles-self-driving-car-ai-can-be-the-vehicles-legal-driver-us-government-says/14 Since the original publication, ARK has updated its price per mile estimate for an autonomous vehicle from $0.25 to $0.35 after factoring in the cost of remote human operators that could guide vehicles in emergencies. 14 Since the original publication, ARK has updated its price per mile estimate for an autonomous vehicle from $0.25 to $0.35 after factoring in the cost of remote human operators that could guide vehicles in emergencies 15 Bryant Walker Smith, “Human Error as a Cause of Vehicle Crashes”, Stanford Law School, The Center for Internet and Society, December 18, 2013. http://cyberlaw.stanford.edu/blog/2013/12/human-error-cause-vehicle-crashes

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16 Source: ARK Investment Management LLC https://ark-invest.com/research/autonomous-vehicle-safety#fn-7907-5

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

SHARED AUTONOMOUS VEHICLES WILL FREE RESIDENTIAL, COMMERCIAL AND MUNICIPAL REAL ESTATE FOR HIGHER RETURN Parking lots occupy a lot of otherwise productive space around the world, a problem that SAVs will solve in large part. Spending eight- to twelve-fold more time on the road than traditional cars, SAVs would require only one parking space in reserve per car, compared to the five in place today. If SAVs were to replace 60% of the personal vehicles in the U.S., they would free up roughly 740 million parking spaces worth $13 trillion at today’s values, more than 85% accruing to commercial real estate owners and municipalities. Repurposing the land and buildings would deliver significant incremental returns on invested capital. Homeowners could turn garages into rooms or larger yards, while commercial real estate owners might build out more offices, retail storefronts, or apartments. Municipalities will lose parking fees but could sell off their parking lots to compensate, ultimately turning parking fees into real estate taxes. By our estimates, as shown below, converting parking lots would add roughly $1 trillion, or 7.7%, per year to homeowner, commercial, and municipal real estate returns.

FIGURE 7

Annual Returns from Freed Parking Spaces in the U.S.

Commercial $514 billion

Municipal $383 billion Residential $117 billion Annual Returns Source: ARK Investment Management LLC, The Earth Institute at Columbia University, Transforming Personal Mobility Report

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

ROBOTS WILL MORE THAN DOUBLE GDP PER WORKER IN THE U.S. DURING THE NEXT TWENTY YEARS According to an Oxford University study published in 2013 and updated this year, roughly 47% of all jobs in the U.S. labor force today will be automated during the next 10 to 20 years.17 While that trend sounds ominous for the U.S. workforce, a deeper dive into the study suggests automation will spur productivity and add enormously to GDP per worker as higher value-add jobs displace lower skilled positions. Education and retraining will be important bridges for students and workers if they are to adapt successfully to the changes in automation during the next twenty years. If the Oxford study is correct in assessing the probability of automation in each of the 702 job classifications it analyzed, the impact on real domestic output of goods and services (GDP) will be transformative. As shown below, thanks to the incremental productivity from automation, real GDP per U.S. worker will more than double from $113,000 this past year to $236,000, compounding at an annualized growth rate of 3.4% through 2035. In the absence of automation, productivity would increase at roughly half that rate, or 1.8%, and real GDP per worker would reach only $167,000. In other words, in twenty years, real GDP per worker will be 42% higher and real GDP $12 trillion higher with automation than without it. As always, automation is a game changer.

FIGURE 8

GDP per U.S. Employee, With and Without Automation ($ thousands) GDP per Worker with Automation

GDP per Worker without Automation

$250

$200

$150

$100 2014

2016

2018

2020

2022

2024

2026

2028

2030

2032

2034

Source: Bureau of Labor Statistics, Energy Information Administration, Oxford Study

17 Carl Benedikt Frey and Michael A. Osborne, “The Future of Employment: How Susceptible Are Jobs to Computerization”, University of Oxford, September 17, 2013. http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf; and January 2016. http://www.oxfordmartin.ox.ac.uk/downloads/reports/Citi_GPS_Technology_Work_2.pdf

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

FIGURE 9

Percentage Increase in Real GDP with Automation $11.6 trillion added to GDP, yielding a GDP of $39.4 trillion in 2035 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 2014

2016

2018

2020

2022

2024

2026

2028

2030

2032

2034

Source: ARK Investment Management LLC

FIGURE 10

Net Margins, With and Without Automation Grocery and Food

General Merchandise

4.0% 3.5% 3.0% 2.5%

DEFAULT for axis and labels: Tw Cen MT, Regular, 7-8pt 1.5% Axis Color = RGB 90,90,90 2.0%

1.0% 0.5% 0.0%

Net Margin

Source: ARK Investment Management LLC, NYU Stern, LP Magazine

Net Margin with Automation

2035

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

While automation sounds like an ominous prospect for labor, the “bigger pie” seems to fly in the face of that argument. Where will the $12 trillion in incremental real GDP associated with automation surface by 2035? A good question... with several answers. Some of it could drop to the bottom line of corporate America in the form of higher profits. The food services industry could be one of the biggest beneficiaries given its labor intensity and low margin structure. As shown in Figure 10, grocery store margins could more than double from less than 1% to 2.1%, while general merchandise margins could increase more than 20% from nearly 3% to 3.7%. In both industries, shrinkage provides a large part of the explanation. Robots don’t steal, at least not yet! For competitive reasons, though, companies may choose to reinvest some of the windfall from automation, accelerating growth in capital spending. As artificial intelligence begins to solve increasingly complex problems, the return on investment from “smarter” robots, drones, autonomous vehicles, and other devices will drive their adoption. Therefore, between 2015 and 2025, as is illustrated in Figure 11, annual investment in all forms of automation could escalate from $11 billion to $185 billion, or at a compound annual growth rate of 33%, and from 2015 to 2035 at a compound annual rate of 17%. Unit growth rates could be higher, given the declining cost curves in technology. This rate of growth would be exceptional, providing a glimpse into the upside to the economy associated with automation. Competitive dynamics could turn the gains from automation into benefits for the consumer, in the form of higher wages and/or lower prices. Already today, as illustrated in Figure 12, about 5.4 million jobs in the U.S. go unfilled because of skill-set mismatches. Clearly, companies will have to invest in training to attain more technologically sophisticated and skilled labor. Corporate-sponsored training and retraining programs should deliver high returns on investment, as should vocational school programs. As technology continues to permeate the cost structures of most industries, well run companies should enjoy flat to declining cost curves, giving them more ammunition to compete on price – another boost to consumer purchasing power. As has been the case historically, automation may cause shortterm dislocations but ultimately it will increase the value of labor per dollar of output, create a virtuous cycle, and increase living standards meaningfully in the U.S.

DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

FIGURE 11

Annual Investment in Automation, Select Years ($ in billions) 300

$242 250

$185

200

CA GR

150

33

%

100

50

$11

0

2015

2025

2035

Source: ARK Investment Management LLC

FIGURE 12

Total U.S. Nonfarm Job Openings Total U.S. nonfarm job openings (monthly, seasaonally adjusted, thousands) 6000 5000 4000

DEFAULT for axis and labels: 3000 Tw Cen MT, Regular, 7-8pt Axis 2000 Color = RGB 90,90,90

Source: Bureau of Labor Statistics

16 20

15 20

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11 20

10 20

09 20

08 20

07 20

06 20

05 20

04 20

03 20

02 20

01

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20

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

AS SCIENCE AND TECHNOLOGY PARTNER WITH HEALTH CARE, PROJECTIONS OF UNFUNDED LIABILITIES WILL DECLINE The old adage in advertising was, “I know that half of my advertising works. I just don’t know which half!” Technology solved that problem thanks to algorithms developed by companies like Google, Facebook, and Twitter, each of which calculates and analyzes returns on investment per advertising dollar spent. Health care has been facing the same question: what is the efficacy and efficiency of each dollar spent on health care? In the absence of scientific evidence, doctors and others have relied on trial and error, guesswork, intuition, instinct, and experience. Thanks to breakthroughs in DNA sequencing, however, guesswork will diminish significantly, and the cost curve associated with treatment should flatten and, in some cases, decline over time. Consequently, projections of unfunded retirement medical liabilities could be too high and might surprise on the low side of expectations. DNA sequencing is unlocking some of the secrets of life and death, changing the course of health care. Increasingly, doctors are learning what disease risks and drug-related side effect profiles their patients face, and which drugs are likely to work, thanks to molecular diagnostic tests derived from genomic research.

FIGURE 13

Cost to Sequence a Whole Human Genome (monthly, USD, log scale) Historic Cost Per Genome

Moore's Law

Moore's Law Forecast

Historic Rate Forecast

Step-Change Forecast

$100,000,000 $10,000,000 $1,000,000 $100,000 Cost (US$)

13

$10,000 $1,000 $100 $10 $1

Source: National Human Genome Research Institute (NHGRI), ARK Investment Management LLC

2001

2003

2006

2009

2011

2014

2017

2020

2023

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DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

FIGURE 14

The Number of Human Genomes Sequenced (log scale) Genomes Sequenced

Moore's Law Forecast

Historic Rate Forecast

Tens of billions

100,000,000,000 10,000,000,000

4 BILLION

1,000,000,000 100,000,000

0%

20

GR CA

500 MILLION 50 MILLION

10,000,000 600,000

1,000,000 200,000

100,000 10,000

40,000

Human Genomes Sequenced 2001-2013 (Estimate)

Human Genomes Sequenced in 2014

Human Genomes Sequenced in 2015

Human Genomes Sequenced in 2020

Human Genomes Sequenced in 2025

Source: National Human Genome Research Institute (NHGRI), ARK Investment Management LLC

Both the cost and time to sequence a human genome are collapsing. In fact, the rate of decline is three to four times as fast as Moore’s Law in the microprocessor world. Fewer than 10 years ago, sequencing one human genome cost $10 million and took several months of computing power to complete. Today, the cost is approximately $1,000, including less than a day of computing power. Within a few years, it will drop to $100 and take minutes. The number of human genomes being sequenced is soaring, thanks to the price elasticity of demand. Given how prohibitive the costs have been to date, only 268,000 human genomes had been sequenced globally between the time that the first whole human genome was sequenced in 2000 and year end 2014. Thanks to breakthroughs associated with Illumina’s Hi-Seq X-10, capacity is now in place to sequence 684,000 human genomes in a single year. From that base, even if the rate of growth were to slow down to Moore’s Law, with costs halving every eighteen months to two years, the number of human genomes likely to be sequenced in 2020 would hit 165 million, compounding at a 200% annualized rate of growth. As shown in Figure 17, in 10 years that number could top four billion, suggesting either that the majority of human genomes around DEFAULT for axis and labels: the world will be sequenced, that something like bi-annual sequencing in the developed world to measure the Tw Cen Regular,(epigenetics) 7-8pt will become routine, or that liquid biopsies will become routine in impact of theMT, environment physical examinations to test for cancer in Stage 1 or 2. Axis Color = RGB 90,90,90 Historically in health care, the slope of cost curves has been steeply positive, so much so that it now accounts for 18% of gross domestic product (GDP). Now that technology and science are partnering, the trajectory of health care costs is likely to surprise on the low side of expectations during the next decade, potentially lowering the size of what are perceived as intractable unfunded medical liabilities. The outlook for fiscal policy may not be as bleak as is projected now that the technology is penetrating the health care space, introducing explosive volume growth possibilities at lower costs.

DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

CRYPTOCURRENCIES WILL CHALLENGE TRADITIONAL TRANSACTION PL ATFORMS AND MONETARY POLICIES Until cryptocurrencies surfaced as a digital payments option, merchants and consumers were resigned to a 1.5-3% transaction toll with each credit or debit card purchase, while lower income individuals accepted the 8-9% remittance fee charged by companies like Western Union. Now, those payment platforms are facing the threat that cryptocurrencies could usurp their roles as intermediaries. Historically, cryptocurrencies such as bitcoin have charged 0.01% on a dollar basis,18 as shown below. While they are in early and unstable days, they are developing some credibility as companies like Dell, DirectTV, Overstock, Microsoft, and Expedia begin to include them as an accepted means of payment. The intermediary payments role that cryptocurrencies are attempting to displace is meaningful—roughly $400 billion19 in market value.

FIGURE 15

Fee Comparison Between Transactions Types

10%

Percent of Transaction

15

8% 6% 4% 2%

0% Bitcoin (Sender)

Credit Card (Merchant)

PayPal (Merchant)

Remittances (Consumer)

Source: ARK Investment Management LLC, Quandl, PayPal, IMF, Goldman Sachs

A cryptocurrency is a digital cash system that uses a distributed computing network and consensus algorithms to verify payments and control the supply of monetary units. Unlike other digital objects, units of a cryptocurrency cannot be duplicated or counterfeited, because every coin is tracked in a distributed public ledger accessible to every computer (“miner”) participating in the cryptocurrency’s network. In the case of bitcoin, new coins are created on a pre-determined schedule as an incentive for users to devote processing power to maintain and secure the public ledger in the “mining” process. Other cryptocurrencies are mined or minted in different ways, depending on their software.

18 While we have translated the Bitcoin network fee to a percent of dollar volume, the network itself charges on a per kilobyte size of transaction for incorporation into blocks. 19 https://www.worldpaymentsreport.com/sites/all/themes/wpr_theme/frontend/dist/images/other/infograph.jpg

DEFAULT for axis and labels:

DISRUPTIVE INNOVATION: NEW MARKETS, NEW METRICS CATHERINE D. WOOD AND ARTHUR B. LAFFER

FIGURE 16

U.S. Monetary Base vs. Bitcoin Supply (annual, semi-log scale, U.S. Monetary Base in $ Billions, Bitcoin Supply in Millions of Units)

$6,000

Bitcoin Supply

30

?

$4,000

20

$2,000

10

$0

0 2000

2004

2008

2012

2016

2020

Bitcoin Outstanding (Millions of units)

U.S. Monetary Base

$8,000 U.S. Monetary Base (Billions)

16

2024

Source: ARK Investment Management LLC, Blockchain, FRED

Perhaps as provocative as their intermediary potential is the role that cryptocurrencies could play in monetary policy. As illustrated in Figure 16, bitcoin was created at the same time as the Federal Reserve Board was turbocharging the monetary base during the financial crisis in 2008-2009. The supply of both had similar trajectories, until recently. As shown above, while the monetary base is governed by the Fed and has soared from less than $1 trillion in 2007 to about $4 trillion today, 20 bitcoin’s supply will be capped at 21 million units unless a majority of miners agrees to an increase or decrease. Consequently, its growth will level out, decelerating to a 4% inflationary rate in mid-2016 and just under 2% in mid-2020, 21 according to the open-source software underpinning it. The U.S. monetary base has no such discipline governing it. Could it be that technology and science have combined to present the first serious challenge to monetary policy since the demise of the gold-exchange standard in 1971, or perhaps since the Federal Reserve Board was created in 1913? Cryptocurrencies are still in their early days... but stay tuned! 0

CONCLUSION

2008

2012

2016

2020

2024

2028

DEFAULT for axis and labels: The telecom bubble 7-8pt got one big idea right: general purpose technology platforms were going to Twtech CenandMT, Regular, “converge” and have a major impact on every economic sector, changing the way the world works. The idea was Axis Color = RGB 90,90,90 right, but capital raced into it 10 to 15 years too early, destroying returns on investment in the interim. The broadband build-out was egregious, but the concomitant collapse in broadband pricing laid the foundation for cloud computing and an explosion in innovation. Not only will these disruptions change the relevance and meaning of economic statistics that policymakers use as guides, but they might change the course of government policy. What the bubble mindset did not contemplate was the potentially profound impact that declining cost curves and algorithms might have on fiscal and monetary policies around the world. 20 https://research.stlouisfed.org/fred2/series/BASE 21 https://en.bitcoin.it/wiki/Controlled_supply

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