Michael Cembalest

March 20, 2020

Coronavirus update: COVID-19 and the markets

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1

Where can I find all these charts and what they mean

Private Bank

Asset Management

www.jpmorgan.com/coronavirusupdates

www.jpmorgan.com/coronavirus-research

2

Infection counts

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

T0

T3

T6

T9

T1

2

T1

5

T1

8

T2

1

T2

4

T2

7

T30

T3

3

T3

6

T3

9

T4

2

T4

5

T4

8

T51

T5

4

Source: JHU. March 18, 2020. T0: China = Jan 22, Outside China = Feb 4.

Coronavirus T days after respective region's outbreakCumulative number of cases

World ex-China

China

3

East vs West: cultural differences; SARS impact on behaviors; ability of federal and local governments to monitor and enforce population movement restrictions; testing capabilities, etc

0

20

40

60

80

100

120

140

160

180

200

Jan 22 Feb 01 Feb 11 Feb 21 Mar 02 Mar 12

Hubei (China)

Europe

Dev Asia (Sing, HK, SKor, Jpn, Tai)

Can-US

China ex Hubei

Infections per 1 million people by region

Source: Johns Hopkins University, IMF, JPMAM. March 18, 2020.

4

The example of Taiwan

• QR code scanning and online reporting of each person’s travel history

• Health symptoms were used to classify traveler infectious risks based on flight origin and travel history in

the past 14 days

• People with low risk were sent a health declaration border pass via SMS to their phones for faster

immigration clearance

• Those with higher risk were quarantined at home and tracked through their mobile phone to ensure that

they remained there during the incubation period

• Taiwan also proactively seeks out patients with severe respiratory symptoms (based on information from a

national health database) to see who had tested negative for influenza so that they could be retested for

COVID-19

5

Infection rates

Italy

Switzerland

Spain

Norway

IranAustriaDenmark

South Korea

GermanyFrance

Sweden

Finland

Singapore

U.S.Japan

0

50

100

150

200

250

300

350

400

450

500

550

600

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

HubeiItalySwitzerlandSpainNorwayIranAustriaDenmarkSouth KoreaGermanyFranceBelgiumSwedenNetherlandsFinlandIrelandSingaporeIsraelPortugalGreeceU.K.MalaysiaHong KongU.S.AustraliaCanadaRomaniaChina ex HubeiJapanPolandSaudi ArabiaIraqEgyptPhilippinesBrazilIndia

Reported infections per 1 million people for countries with over 100 reported cases for at least the last 5 days

# of days after total reported cases reaches 100

Source: Johns Hopkins University, IMF, J.P. Morgan Asset Management. March 18, 2020.

6

GreenlandFinland, Sweden, IcelandNorway, AlaskaEstonia, RussiaUK, DenmarkIreland, Quebec, Saskatchewan, BelarusGermany, Belgium, Netherlands, Poland, OntarioBrColumbia, Ukraine, N Dakota, Slovakia, HeilongjiangCroatia, Switzerland, Romania, Washington, Minnesota, FranceItaly, Oregon, Wisconsin, Michigan, JilinNY, Massachusetts, Illinois, Pennsylvania, Ohio, Beijing, XinjiangSpain, Greece, Colorado, Portugal, Virginia, Maryland, Hebei, Shanxi, Tianjin, TurkeyJapan, California, Oklahoma, N. Carolina, S.Korea, Shandong, QinghaiArizona, Arkansas, Mississippi, Iraq, Afghanistan, Henan, JiangsuPakistan, Texas, Louisiana, Iran, Hubei, Anhui, Shanghai, TibetNepal, Algeria, Florida, Hunan, JiangxiEgypt, Qatar, FujianUAE, Mexico, Saudi Arabia, Bangladesh, Guangdong, Guangxi, TaiwanIndia, Hong Kong, Macau, Cuba, OmanDominican Republic, Hainan, JamaicaVietnam, HondurasThailand, Philippines, Sudan, SenegalCambodia, Burkina Faso, TrinidadNigeria, Costa Rica, Panama, EthiopiaSri Lanka, VenezuelaCameroon, Colombia, Maldives, Guyana, BruneiSingapore, Malaysia

0 4,000 8,000 12,000 16,000 20,000 24,000 28,000 32,000 36,000 40,000

72.5°

67.5°

62.5°

57.5°

52.5°

47.5°

42.5°

37.5°

32.5°

27.5°

22.5°

17.5°

12.5°

7.5°

2.5°

Global reported infections by latitude

Source: Johns Hopkins, JPMAM. March 18, 2020

89k

Everything below 2.5 N: Argentina, Australia, Bolivia, Brazil, Chile, Congo, Ecuador, Indonesia, Kenya, New Zealand, Paraguay, S Africa

Reported infections as a function of latitude: for now, the one third of the world’s population below 22.5°N has not experienced meaningfully high levels of infection

95% of all infections in a latitude

band encompassing 55% of the

world’s population

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

72.5° 62.5° 52.5° 42.5° 32.5° 22.5° 12.5° 2.5° -7.5° -17.5° -27.5° -37.5° -47.5°

% of infections

% of world population

Infections and world population as a function of latitude

Source: Johns Hopkins University, NASA, JPMAM. March 17, 2020.

7

Infections as a function of temperature and humidity: 90% still in the blue zone

Infections as a function of prevailing temperature and relative humidity

Relative humidity (percent)

Below 5 to 20 to 35 to 50 to 65 to 80 to

5 20 35 50 65 80 95

Below -10 - - 1 - - 232 -

-10 to -5 - 125 246 1,123 470 234 -

-5 to 0 - 2,601 8,466 1,142 1,280 3,302 899

0 to 5 58 1,749 2,858 444 1,212 4,024 25

5 to 10 - 2,705 53,944 19,232 4,950 448 173

10 to 15 - - 9,550 81,748 2,102 164 -

15 to 20 - 279 452 1,817 106 536 65

20 to 25 269 196 202 991 1,016 1,171 -

25 to 30 76 - 11 30 - - -

30 to 35 61 11 6 - - - -

35 to 40 - - - - - - -

Source: WHO, Johns Hopkins, OpenWeatherMapAPI, JPMAM, March 18, 2020

Tem

pera

ture

(C

els

ius)

8

What we have learned about the virus

• Up to 85% of infections occur in family clusters

• Most of the remainder occurred due to contact with hard surfaces in the immediate

environment of those with infection

• Limited instances of hospital-borne infection

• Although asymptomatic patients were reported for SARS, no known transmission

occurred from these patients

• Basic reproductive number (a measure of transmissibility): similar to SARS

• Incubation time (how long it takes to show symptoms): similar to SARS

• Serial interval (how long it takes to become infectious to others): different, and

that’s the root of the problem

• Average symptoms show up on Day 5, contagiousness can begin on Day 4

9

COVID-19 (SARS-CoV-2) and surfaces: rapid time-decay of viral load

Source: van Doremalen et al, “Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1”, National Institute of Allergy and Infectious Diseases. 2020.

1

10

100

1,000

10,000

0 10 20 30 40 50 60 70 80

Decay of SARS-CoV-2 on CopperViral load measure, TCID50 per ml of medium

Hours

99% dissipation in 8 hrs

1

10

100

1,000

10,000

0 10 20 30 40 50 60 70 80

Decay of SARS-CoV-2 on CardboardViral load measure, TCID50 per ml of medium

Hours

97% dissipation in 8 hrs

1

10

100

1,000

10,000

0 10 20 30 40 50 60 70 80

Decay of SARS-CoV-2 on Stainless SteelViral load measure, TCID50 per ml of medium

Hours

97% dissipation in 24 hrs

99.8% dissipationin 48 hrs

1

10

100

1,000

10,000

0 10 20 30 40 50 60 70 80

Decay of SARS-CoV-2 on PlasticViral load measure, TCID50 per ml of medium

Hours

45% dissipation in 24 hrs

98% dissipationin 48 hrs

10

Some promising news in development of anti-viral medications

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

0 10 20 30 40 50 60 70 80 90 100

Source: Wuhan Institute of Virology. February 4, 2020.

Remdesivir tests against 2019-nCoV in cell cultures% virus inhibition % cytoxicity

Inhibition

Cytoxicity

Dosage (micrometers)

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

0 10 20 30 40 50 60 70 80 90 100

Source: Wuhan Institute of Virology. February 4, 2020.

Chloroquine tests against 2019-nCoV in cell cultures% virus inhibition % cytoxicity

Inhibition

Cytoxicity

Dosage (micrometers)

11

Some promising news in development of anti-viral medications

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 1 2 3 4 5 6

Source: Gautret et al, IHU-Méditerranée Infection. March 2020.

Treatment results of patients with COVID-19% of patients that test positive for infection

Control group

Hydroxychloroquine only

Hydroxychloroquineand azithromycin

combination

Days

12

Drug development underway:vaccines, direct viral inhibitors and immunomodulators

Drug Companies Status Type Drug Companies Status Type Drug Companies Status Type

FavipiravirFujifilm; Medivector; Zhejiang

Hisun PharmaceuticalLaunched Antiviral INO-4800

Beijing Advaccine

Biotech; GeneOne Life

Science; Inovio

Preclinical VaccineDendritic cell

vaccine

Beijing Dingcheng

Taiyuan Biotechn;

Betta Pharma

Discovery Vaccine

Actemra Genentech/Roche LaunchedImmuno-

modulatorCYNK-001

Celularity; Sorrento

TherapeuticsPreclinical Cell Therapy

Recombinant

vaccine

Clover

BiopharmaceuticalsDiscovery Vaccine

RintatolimodAim Immunotech; GP Pharm

SA; Goethe UniversityLaunched

Immuno-

modulator

SARS-CoV-2

vaccine

Chongqing Zhifei

Biological; Institute of

Microbiology

Preclinical VaccineLive-attenuated

vaccine

Codagenix; Serum

Institute of IndiaDiscovery Vaccine

ASC-09 + ritonavir Ascletis Pharma Phase III Anti-retroviralAdjuvant/COVID-

19 vaccineNovavax Preclinical Vaccine

SARS-CoV-2

mRNA vaccineCurevac AG Discovery Vaccine

Remdesivir Gilead Phase III Antiviral S-protein/ACE2Sichuan Kelun

PharmaceuticalPreclinical

Prophylactic

polypeptide

Monoclonal

antibodies/vaccine

Dyadic International;

Israel Institute for

Biological Res

DiscoveryAntibody/

Vaccine

Kevzara Regeneron/Sanofi Phase III/IIImmuno-

modulator

ChAdOx1 nCoV-

19Jenner Institute Preclinical Vaccine

SARS-CoV-2

vaccine

Fudan University; ID

PharmaDiscovery Vaccine

BDB-1 Beijing Defengrei Biotechnology Phase II AntibodyMesenchymal

stem cells

Wuhan Hamilton

BiotechnologyPreclinical Cell Therapy Z-VacciRNA

Guanhao Biotech; Zy

TherapeuticsDiscovery Vaccine

Brilacidin Innovation Pharmaceuticals Phase II Antibody

Protein subunit

vaccineUniversity of Queensland Discovery Vaccine Antibodies

Regeneron

PharmaceuticalsDiscovery Antibody

SARS-CoV-2

vaccine

Medigen' National

Institutes of HealthDiscovery Vaccine

Monoclonal

antibodiesVir Biotechnology Discovery Antibody

Protein subunit

vaccineSanofi Pasteur Discovery Vaccine mRNA-1273 Moderna Therapeutics Discovery Vaccine

Anti-SARS-CoV-2

programNanoviricides Discovery Nanoviricide

Coronavirus

vaccineVaxart Discovery Vaccine Antibodies

Immunoprecise

AntibodiesDiscovery Antibody

Source: Cortellis, Bioworld, Johns Hopkins, JPMAM. As of March 5, 2020.

13

China equity markets and infections

2800

2900

3000

3100

3200

3300

0

100

200

300

400

500

600

700

800

900

1,000

Jan 23 Jan 31 Feb 08 Feb 16 Feb 24 Mar 03 Mar 11 Mar 19

Source: Bloomberg, Johns Hopkins University. March 18, 2020.

Chinese daily infections versus Chinese equitiesDaily number of cases Index level

Chinaexcluding Hubei

Shanghai Stock Exchange A Share

Index

14

A key litmus test for the world: what will happen to infection rates in China as lockdown provisions and quarantine provisions are relaxed? Risks of a “second wave” of infections

3/1

4

2/2

5

3/1

7

3/1

7

3/1

7

2/1

8

3/1

2

3/1

1

0%

20%

40%

60%

80%

100%

Railwaycoal

deliveries

Electricityuse

/factorycapacity

Trafficjams

Coalconsum.

Homesales

Roadand railtravel

Transporthub

passeng.flows

Boxoffice

revenues

20 days after Chinese New Year (2/14)

Most recent level

High frequency Chinese economic indicatorsIndicated level as a % of historical average

Source: J.P. Morgan Emerging Markets Research, Goldman Sachs. Mar 18, '20.

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Jan 23 Jan 31 Feb 08 Feb 16 Feb 24 Mar 03 Mar 11 Mar 19

Source: Bloomberg, Johns Hopkins University. March 18, 2020.

Chinese daily infections: Hubei vs ex-HubeiDaily number of cases

Hubei

China ex-Hubei

15

One possible scenario for the US

Best guess epidemiology outcomes for the US

James Lawler, MD, MPH, FIDSA, University of Nebraska

Region VII disaster health response ecosystem webinar

Reproductive number 2.5

Doubling time 7-10 days

Community attack rate 30-40%

Cases 96 million

Hospital admissions 4.8 million (5%)

Cases requiring ICU care 1.9 million (1-2%)

Cases requiring ventilatory support 1%

Deaths 480,000 (0.5%)Source: Region VII Disaster Health Response Ecosystem. Feb 27, 2020.

16

Where “flattening the curve” comes from

0

50

100

150

200

250

300

Mar '20 Apr '20 May '20 Jun '20 Jul '20 Aug '20 Sep '20 Oct '20

Do Nothing

Closing schools and universities

Case isolation

Case isolation and household quarantine

Case isolation, home quarantine, socialdistancing of >70s

Source: "Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand", N Ferguson et al, Imperial College of London, March 2020.

Great Britain critical care beds occupied per 100,000 of population

Surge critical care bed capacity

17

Mortality as a % of reported infections

Pandemic measures:

(a) population of a given geographical area

(b) infected individuals, including both asymptomatic

people and people that get sick

(c) people that are infected, get sick and self-report

(d) number of people that die

During the haze of a pandemic, best estimates that

entities like the World Health Organization often derive

are based on (a), (c) and (d), and even things like (d) are

complicated by pandemics affecting older individuals

with pre-existing conditions. They do not know (b)

upfront, and sometimes it is never known, or only known

with the passage of time. Swine Flu (H1N1/2009)

example. Early mortality rate estimates in fall 2009:

1.0%-1.3%. Four years later: just 0.02%.

GIMBE Foundation: Italy infections likely ~100,000,

which would reduce observed mortality rate to 2%

Diamond Princess cruise ship: ability to observe both

symptomatic and asymptomatic individuals

Wuhan, 5.0%

Hubei, 4.6%

China, 4.0%

Italy, 8.3%

Iran, 6.5%

Beijing, 1.7%Henan, 1.7%

World ex China, 4.1%

Chongqing, 1.0%

Shanghai, 0.8%China ex-Hubei, 0.9%

Diamond Princess, 1.0%South Korea, 1.0%

Anhui, 0.6%Guangdong, 0.6%

Hunan, 0.4%Jiangxi, 0.1% Germany, 0.2%

Spain, 4.5%

France, 1.6%

Switzerland, 0.9%

United States, 1.5%

Netherlands, 2.8%

Norway, 0.4%

United Kingdom, 2.7%

Belgium, 0.9%

Austria, 0.2%

Cholera (2010), 3.2%

Spanish flu (1918-1920), 3.5%

Swine Flu (2009/Initial), 1.3%

US Flu, 2019, Age 65+, 0.8%Measles, 0.7%

US Flu, 2019, 0.1%

Hepatitis A, 0.5%Swine Flu (2009/Revised), 0.0%

West Nile Virus (2013), 4.2%

Yellow Fever, 4.9%

Lyme disease, Chicken Pox, 0.0%0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

5.5%

6.0%

6.5%

7.0%

7.5%

8.0%

8.5%

COVID-19

Other diseases

Mortality rates: COVID-19 vs other diseases, and the impact of Wuhan/HubeiMortality rate; bubble size indicates relative number of fatalities for COVID-19 only

Mortality rates shown for all countries with at least 1,000 infections to date. Sources: CDC, China National Health Commission, Center for Health Protection (HK), Global Health Data Exchange, Johns Hopkins University, Netherlands Institute for Health Services Research, ImperialCollege of London, Mayo Clinic, World Health Organization, JPMAM. March 18, 2020.

China Rest of World

18

Infection and mortality rates

Card

iova

sc

ula

r d

ise

as

e

Dia

be

tes

Ch

ron

ic r

es

pir

ato

ry d

ise

as

e

Hyp

ert

en

sio

n

Can

ce

r

No

pre

-ex

isti

ng

co

nd

itio

ns

0%

2%

4%

6%

8%

10%

12%

Source: Chinese Center for Disease Control and Prevention. February 2020.

Coronavirus mortality rate based on pre-existing conditionsCoronavirus mortality rate based on pre-existing conditions

Current mortality rate

0%

2%

4%

6%

8%

10%

12%

14%

16%

0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80+

Source: Chinese CDC, WHO. February 2020.

Coronavirus mortality rate by age

Current mortality rate (3/18/2020)

Study mortality rate (2/17/2020)

19

Infection and mortality rates

0%

5%

10%

15%

20%

25%

30%

35%

0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80+

Source: Chinese Center for Disease Control and Prevention. February 2020.

Distribution of COVID-19 mortality and infections by age% of total infected or deceased population

Infections

Mortality

0

1

2

3

4

5

6

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75

Influenza fatality rate during the Spanish flu (1918-19)

Influenza fatality rate after the Spanish flu (1928-29)

Source: Taubenberger and Morens. 2006.

Case fatality rate during and after the Spanish fluFatalities per 100 infected persons

Age

In Italy, mortality distribution even more skewed to the elderly: 88% of deaths

occurred in population 70+, compared to 50% in China

20

Lessons learned 100 years ago, ignored in China

• 100 years of history: get ahead of a pandemic

• Jan 1: Chinese officials required hospitals not to

transfer fever patients to another medical facility,

prevented doctors from publishing diagnosis and

treatment information for COVID-19

• Jan 1: Chinese government punished doctors for

discussing outbreak, required them to sign

documents saying they were spreading lies

• Jan 14: Wuhan Health Commission reported that

there were no new coronavirus cases, and that risk

of human-to-human transmission is low

• During first three weeks of Jan, Wuhan hospitals

didn’t treat infected or asymptomatic outpatients as

potentially infectious

• 40 infectious patients visiting clinics on Dec 31

ended up exposing 18,000 people before city shut

down on Jan 23

Faster public health response times =

lower mortality rates

200

300

400

500

600

700

800

-15 -10 -5 0 5 10 15 20 25 30 35

Source: Markel et al, University of Michigan. 2007.

Excess pneumonia & influenza mortality in 43 US cities, 1918-1919, Excess deaths per 100,000 population

Public health response time (days)

21

Beds and testing

IRN

KOR

ITA

JPN

SGP

FRA

DEU

GBR

ESP

SWI

USA

SWE

BEL

NOR

NLD

MAL

AUT

CAN

0

2

4

6

8

10

12

14

0 5,000 10,000 15,000 20,000 25,000

Source: WHO, World Bank. March 16, 2020.Number of infections

Hospital beds vs number of 2019-nCoV infectionsHospital beds per 1,000 people

So

uth

Ko

rea M

ar-

17

Norw

ay M

ar-

16

Chin

a –

Guangdong F

eb-2

4

Italy

Mar-

17

Denm

ark

Mar-

17

Austr

alia

Mar-

17

Austr

ia M

ar-

17

Canada M

ar-

17

Russia

Mar-

16

Ta

iwan M

ar-

17

United K

ingdom

Mar-

17

Czech R

epublic

Mar-

17

Sw

itzerla

nd M

ar-

07

Isra

el M

ar-

09

Irela

nd M

ar-

09

Neth

erla

nds M

ar-

07

Cro

atia

Mar-

17

Po

land M

ar-

16

United S

tate

s M

ar-

13

Fra

nce M

ar-

08

Fin

land M

ar-

11

Japan M

ar-

17

New

Ze

ala

nd M

ar-

17

Th

aila

nd M

ar-

17

Vie

tnam

Mar-

17

South

Afr

ica M

ar-

11

India

Mar-

13

0

1,000

2,000

3,000

4,000

5,000

6,000

Source: Countries statistical reports by Esteban Ortiz-Ospina, IMF. Mar 17, '20

COVID-19 tests per million people

22

Equity markets

-6.0x

-5.5x

-5.0x

-4.5x

-4.0x

-3.5x

-3.0x

-2.5x

-2.0x

-1.5x

-1.0x

-0.5x

0.0x

90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20

Source: JPMAM. IBES, Datastream, Bloomberg. March 18, 2020.

S&P 500 multiple deratingForward 12 month P/E, difference versus previous month

10x

12x

14x

16x

18x

20x

22x

24x

26x

'90 '92 '94 '96 '98 '00 '02 '04 '06 '08 '10 '12 '14 '16 '18 '20

S&P 500 price/earningsPrice / forward 12 month earnings per share

Source: JPMAM. IBES, Datastream, Bloomberg. March 18, 2020.

23

Equity markets

0

10

20

30

40

50

60

70

80

90

100

1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019

Source: Bloomberg. March 18, 2020.

S&P 100 implied volatility indexIndex level

3/18/2020 level

24

Equity markets

0%

1%

2%

3%

4%

5%

6%

7%

Jan-16 Jul-16 Jan-17 Jul-17 Jan-18 Jul-18 Jan-19 Jul-19 Jan-20

Source: JPM Global Markets Strategy Flows & Liquidity. March 16, 2020.

Quantity-On-Loan of the SPY US ETFOn loan quantity as a % share of share outstanding

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

2012 2013 2014 2015 2016 2017 2018 2019 2020

Source: JPM Global Markets Strategy Flows & Liquidity. March 17, 2020.

Positions in US equity futures by leveraged funds and asset managers, Spec positions as a percentage of open interest

Extrapolated to March 17th using open interest changes

25

Credit markets

-200

0

200

400

600

800

1,000

1,200

1,400

1,600

2000 2004 2008 2012 2016 2020

Source: Bloomberg. March 18, 2020

Fixed rate preferred securities option adjusted spreadPOP1 index, basis points

50

100

150

200

250

300

350

400

450

500

550

600

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Source: Bloomberg, J.P. Morgan. March 18, 2020.

US investment grade corporate bond spreadsJULIS index, basis points

100

200

300

400

500

600

700

800

900

1,000

2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Source:Bloomberg, J.P. Morgan. March 18, 2020.

Emerging market sovereign bond spreadsJPSYAGSW index, basis points

100

150

200

250

300

350

'05 '06 '07 '08 '09 '10 '11 '12 '13 '14 '15 '16 '17 '18 '19 '20

Source: Bloomberg. March 18, 2020.

30Y fixed mortgage - 10Y US Treasurybasis points

-500

50100150200250300350400450500550600650

'98 '00 '02 '04 '06 '08 '10 '12 '14 '16 '18 '20

Source: J.P. Morgan. March 18, 2020.

AAA asset backed securities spreadsbasis points

Prime auto

Credit card Commercial real estate

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2014 2015 2016 2017 2018 2019 2020

Source: Bloomberg, JPM HY Strategy team. March 18, 2020.

US high yield corporate bond spreadsJPDFHYI index energy and ex-energy, basis points

Ex Energy

Energy

26

Credit markets

0

10

20

30

40

50

60

70

80

90

100

2015 2016 2017 2018 2019 2020

Source: Bloomberg. March 18, 2020.

Libor - federal funds rate basis points

27

Emergency facilities, 2008-2009

Peak Outstanding

Balance ($ bn)

Term Auction Facility $493

Commercial Paper Funding Facility $348

Term Securities Lending Facility $236

Asset-Backed Commercial Paper Money Market

Mutual Fund Liquidity Facility$152

Primary Dealer Credit Facility $147

Term Repurchase Transactions $80

AIG Revolving Credit Facility $72

Term Asset-Backed Securities Loan Facility $48

Source: Levy Economics Institute, Bard College. 2011.

Emergency facilities created by the Federal Reserve during

the Financial Crisis

28

How far do earnings fall in a recession?

-100%

-90%

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

1870 1890 1910 1930 1950 1970 1990 2010

S&P 500 earnings drawdownsMaximum drawdown of earnings per share

Reported earnings

Operating earnings

Source: Robert J. Shiller, S&P Dow Jones Indicies. Q4 2019.

29

Earnings drawdowns, US vs Europe

-100%

-80%

-60%

-40%

-20%

0%

70

72

74

76

78

80

82

84

86

88

90

92

94

96

98

00

02

04

06

08

10

12

14

16

18

20

France Germany

Italy USA

European profits more sensitive to recessionsMaximum drawdown of earnings per share for respective MSCI country index

Source: J.P. Morgan Securities Inc., MSCI, Bloomberg. February 2020.

30

What are equity markets now pricing in regarding S&P 500 earnings?

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Source: Bridgewater. March 17, 2020.

US EPS level implied by dividend futures% of pre-virus level

Pricing today

Pricing on Jan 20

31

What kind of crises play out over many years instead of over shorter periods?

32

Time capsule: disaster, ruin and recovery

“What has so often excited wonder, is the great rapidity with which countries recover from a

state of devastation, the disappearance in a short time, of all traces of mischief done by

earthquakes, floods, hurricanes, and the ravages of war. An enemy lays waste a country by

fire and sword, and destroys or carries away nearly all the moveable wealth existing in it: all

the inhabitants are ruined, and yet in a few years after, everything is much as it was before.”

John Stuart Mill, Principles of Political Economy, 1848

33

A lot has changed in medical science in 100 years

0

10

20

30

40

50

60

70

80

90

100

Military samples Civilian samples Total

Source: "Predominant Role of Bacterial Pneumonia as a Cause of Death in Pandemic Influenza," National Institute of Allergy and Infectious Diseases, Morens et al, 2008

Spanish Flu (1918): % of cultures containing bacteria causing secondary respiratory infections/pneumonia

Bacteria causing secondary respiratory infections (Streptococcus pneumoniae/hemolyticus, Staphylococcus

aureus, other/mixed pneumopathogens)

All other bacteria

No bacteria found

35

40

45

50

55

60

65

70

75

80

85

1900

1905

1910

1915

1920

1925

1930

1935

1940

1945

1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

2010

2015

Female

Source: US CDC; Andrew Noymer, Public Health Dep't, UC Irvine. 2020.

US life expectancy at birthyears

Male

34

A lot has changed in medical science in 100 years

10

20

30

40

50

60

70

80

1740 1770 1800 1830 1860 1890 1920 1950 1980 2010

Source: French Institute for Demographic Studies (INED). 2018.

Male life expectancy in Franceyears

Absence of data during French Revolution

Napoleonic wars

War of 1870World War I(1914-1918)

World War II(1939-1945)

This chart is a proxy for two things:

[1] astounding medical achievements of the

20th century, including tools scientists are now

using to develop vaccines and anti-viral

medications to combat COVID-19

[2] greater threats to life expectancy and

prosperity have in modern times resulted less

from pandemics and natural disasters, and more

from what people do to each other in times of

war

35

Time capsule: disaster, ruin and recovery

84

88

92

96

100

104

108

1859 1862 1865 1868 1871 1874 1877 1880

Post Civil War recovery in Confederate farm incomeIndex, 100 = 1859

Source: "Economic Behaviour in Adversity", Jack Hirshleifer, The University of Chicago Press, 1987.

US Civil War: deadliest conflict in US history,

with 6x mortality rate as World War II...it left

the southern US in complete shambles… fought

mostly on southern soil, leaving many cities in

ruins with thousands of people lacking food,

clothing, or shelter… Federal government did

very little to assist them…and yet, look how

quickly Confederate farm income rebounded

after the war

36

What kind of crises require years for economies to recover?Colossal wartime destruction…

100

150

200

250

300

350

400

450

500

550

600

1930 1935 1940 1945 1950 1955 1960

Germany

Japan

It took a full decade for Germany and Japan to recover from WWII, Real per capital GDP, 1990$, thousands

Source: Angus Maddison (Historical Statistics of the World Economy), JPMAM. 2020.

By 1945, 20% of Germany’s housing stock was

destroyed, food production was half of 1938 levels,

industrial production was down by a third and caloric

intake was around 1,250 calories per day (average

American consumers 3,600 per day)

As for Japan, around 40% of its capital stock, a quarter

of all housing and 180 miles of 67 cities were

destroyed by the war

37

What kind of crises require years for economies to recover?Or colossal economic mismanagement…

5%

10%

15%

20%

25%

30%

1,500

1,700

1,900

2,100

2,300

1955 1956 1957 1958 1959 1960 1961 1962 1963 1964

Source: "Visualizing the Effects of the Great Leap Forward", Basil Ashton, '84.

China's disastrous Great Leap ForwardPercent Calories/day

Mortality rate (LHS)

Calories/Day (RHS)

Dutch historian Frank Dikotter,

US historian R. Joseph Rummel:

Great Leap Forward was the largest

democide in human history

38

Concluding with a time capsule of markets bottoming while fundamentals were still getting worse

39

Time capsule: high yield markets tend to bottom well before defaults peak

0

50

100

150

200

250

300

0

200

400

600

800

1,000

1,200

1987 1988 1989 1990 1991 1992 1993

Source: J.P. Morgan Securities LLC. February 2014.

Savings and Loan CrisisSpread-to-worst # of Issuers

High Yield credit spreads

Cumulative defaults

55%

0

50

100

150

200

250

300

350

400

450

500

0

200

400

600

800

1,000

1,200

1999 2000 2001 2002 2003 2004

Source: J.P. Morgan Securities LLC. February 2014.

Tech collapseSpread-to-worst # of Issuers

High Yield credit spreads

Cumulative defaults

76%

0

50

100

150

200

250

0

500

1,000

1,500

2,000

2,500

2006 2007 2008 2009 2010 2011 2012 2013

Source: J.P. Morgan Securities LLC. February 2014.

Financial crisisSpread-to-worst # of Issuers

30%

High Yield credit spreads

Cumulative defaults

40

Time capsule: bank stocks tend to bottom well before the peak in bank failures

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

40

50

60

70

80

90

100

110

120

Mar-88 May-89 Jun-90 Jul-91 Aug-92 Sep-93 Oct-94

S&P 500 Bank Index

Cumulative Bank Failures

Savings and Loan Crisis: Bank stocks vs. bank failuresIndex level

Source: FDIC, Bloomberg. March 2014.

Total institutions

63%

0

100

200

300

400

500

0

50

100

150

200

250

300

Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14

SCAP

Financial crisis: Bank stocks vs. bank failuresIndex level

Source: FDIC, Bloomberg. March 2014.

Total institutions

S&P 500 Bank Index

8%

Cumulative Bank Failures

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

0

50

100

150

200

250

300

350

400

Jan-29 Oct-29 Aug-30 Jun-31 Apr-32 Feb-33 Dec-33

Dow Jones Industrial Average

Cumulative Bank Failures

The Great Depression: Equity market vs. bank failuresIndex level Total institutions

Source: FDIC, Bloomberg. March 2014.

48%

41

Time capsule: credit markets tend to bottom way before default rates peak

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

0

200

400

600

800

1,000

1,200

1,400

1,600

2006 2007 2008 2009 2010 2011 2012 2013 2014

AAA CMBS Spread

60+ delinquency rate

CMBS spreads vs. delinquency rates: 2006 to 2014AAA CMBS Spread (basis points) 60+ day delinquency rate

Source: Trepp, J.P. Morgan Securities LLC. February 2014.

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

60

65

70

75

80

85

90

95

100

105

2006 2007 2008 2009 2010 2011

Leveraged Loan prices vs. defaults: 2006 to 2011Price index Default rate

Defaults over trailing 12 months

Leveraged LoanPrice Index

Source: J.P. Morgan Securities LLC, Standard and Poor's, S&P/LSTA Leveraged Loan Index. February 2014.

42

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