Coronavirus update: COVID-19 and the markets
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Coronavirus update: COVID-19 and the markets
March 20, 2020
Michael Cembalest
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1Infection counts
Coronavirus T days after respective region's outbreak
Cumulative number of cases
140,000
120,000
100,000
China
80,000
60,000 World
40,000 ex-China
20,000
0
T12
T15
T18
T21
T24
T27
T33
T36
T39
T42
T45
T48
T54
T9
T30
T51
T0
T3
T6
Source: JHU. March 18, 2020. T0: China = Jan 22, Outside China = Feb 4.
2East vs West: cultural differences; SARS impact on behaviors; ability of federal and local governments
to monitor and enforce population movement restrictions; testing capabilities, etc
Infections per 1 million people by region
200
Hubei (China)
180
Europe
160
Dev Asia (Sing, HK, SKor, Jpn, Tai)
140
Can-US
120
China ex Hubei
100
80
60
40
20
0
Jan 22 Feb 01 Feb 11 Feb 21 Mar 02 Mar 12
Source: Johns Hopkins University, IMF, JPMAM. March 18, 2020.
3The 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
4Infection rates
Reported infections per 1 million people for countries with over 100 reported cases for at least the last 5 days
Hubei
600 Italy
Italy
Switzerland
550 Spain
Norway
Iran
500
Austria
Denmark
450 South Korea
Germany
400 France
Switzerland Belgium
Sweden
350 Netherlands
Spain Finland
300 Ireland
Norway Singapore
Israel
250 Portugal
Iran
DenmarkAustria Greece
200 South Korea U.K.
Malaysia
France Hong Kong
150 Germany U.S.
Sweden Australia
100 Finland Canada
Romania
50 Singapore China ex Hubei
Japan Japan
U.S. Poland
0 Saudi Arabia
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 Iraq
Egypt
# of days after total reported cases reaches 100 Philippines
Source: Johns Hopkins University, IMF, J.P. Morgan Asset Management. March 18, 2020. Brazil
India
5Reported 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
Global reported infections by latitude
0 4,000 8,000 12,000 16,000 20,000 24,000 28,000 32,000 36,000 40,000
72.5° Greenland
67.5°
Finland, Sweden, Iceland 95% of all infections in a latitude
62.5° Norway, Alaska
57.5°
Estonia, Russia band encompassing 55% of the
UK, Denmark
52.5°
Ireland, Quebec, Saskatchewan, Belarus
Germany, Belgium, Netherlands, Poland, Ontario
world’s population
BrColumbia, Ukraine, N Dakota, Slovakia, Heilongjiang
47.5° Croatia, Switzerland, Romania, Washington, Minnesota, France
Italy, Oregon, Wisconsin, Michigan, Jilin
42.5° NY, Massachusetts, Illinois, Pennsylvania, Ohio, Beijing, Xinjiang
Spain, Greece, Colorado, Portugal, Virginia, Maryland, Hebei, Shanxi, Tianjin, Turkey Infections and world population as a function of latitude
37.5° Japan, California, Oklahoma, N. Carolina, S.Korea, Shandong, Qinghai 45%
Arizona, Arkansas, Mississippi, Iraq, Afghanistan, Henan, Jiangsu
32.5° Pakistan, Texas, Louisiana, Iran, Hubei, Anhui, Shanghai, Tibet 89k 40%
Nepal, Algeria, Florida, Hunan, Jiangxi
27.5° Egypt, Qatar, Fujian 35%
UAE, Mexico, Saudi Arabia, Bangladesh, Guangdong, Guangxi, Taiwan
22.5° India, Hong Kong, Macau, Cuba, Oman 30%
Dominican Republic, Hainan, Jamaica 25%
17.5° Vietnam, Honduras
Thailand, Philippines, Sudan, Senegal 20%
12.5° Cambodia, Burkina Faso, Trinidad % of infections
Nigeria, Costa Rica, Panama, Ethiopia 15%
7.5° Sri Lanka, Venezuela % of world population
10%
Cameroon, Colombia, Maldives, Guyana, Brunei
2.5° Singapore, Malaysia 5%
Everything below 2.5 N: Argentina, Australia, Bolivia, Brazil, Chile, Congo, Ecuador, Indonesia, Kenya,
New Zealand, Paraguay, S Africa 0%
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°
Source: Johns Hopkins, JPMAM. March 18, 2020
Source: Johns Hopkins University, NASA, JPMAM. March 17, 2020.
6Infections 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
Temperature (Celsius)
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
7What 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
8COVID-19 (SARS-CoV-2) and surfaces: rapid time-decay of viral load
Decay of SARS-CoV-2 on Copper Decay of SARS-CoV-2 on Cardboard
Viral load measure, TCID50 per ml of medium Viral load measure, TCID50 per ml of medium
10,000 10,000
1,000 1,000
100 99% dissipation in 8 hrs 97% dissipation in 8 hrs
100
10
10
1
0 10 20 30 40 50 60 70 80 1
0 10 20 30 40 50 60 70 80
Hours
Hours
Decay of SARS-CoV-2 on Stainless Steel Decay of SARS-CoV-2 on Plastic
Viral load measure, TCID50 per ml of medium Viral load measure, TCID50 per ml of medium
10,000 10,000
45% dissipation in 24 hrs
1,000 1,000
97% dissipation in 24 hrs 98% dissipation
100 in 48 hrs
100
99.8% dissipation
in 48 hrs
10 10
1 1
0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80
Hours Hours
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.
9Some promising news in development of anti-viral medications
Remdesivir tests against 2019-nCoV in cell cultures Chloroquine tests against 2019-nCoV in cell cultures
% virus inhibition % cytoxicity % virus inhibition % cytoxicity
120% 120% 120% 120%
100% 100% 100% 100%
80% Inhibition 80% 80% 80%
60% 60% 60% 60%
Inhibition
40% 40% 40% 40%
20% 20% 20% 20%
Cytoxicity
0% 0% 0% 0%
-20% -20% -20% -20%
Cytoxicity
-40% -40% -40% -40%
0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100
Dosage (micrometers) Dosage (micrometers)
Source: Wuhan Institute of Virology. February 4, 2020. Source: Wuhan Institute of Virology. February 4, 2020.
10Some promising news in development of anti-viral medications
Treatment results of patients with COVID-19
% of patients that test positive for infection
100%
90%
80%
70% Control group
60%
50%
40% Hydroxychloroquine only
30% Hydroxychloroquine
20% and azithromycin
10% combination
0%
0 1 2 3 4 5 6
Days
Source: Gautret et al, IHU-Méditerranée Infection. March 2020.
11Drug development underway:
vaccines, direct viral inhibitors and immunomodulators
Drug Companies Status Type Drug Companies Status Type Drug Companies Status Type
Beijing Advaccine Beijing Dingcheng
Fujifilm; Medivector; Zhejiang Dendritic cell
Favipiravir Launched Antiviral INO-4800 Biotech; GeneOne Life Preclinical Vaccine Taiyuan Biotechn; Discovery Vaccine
Hisun Pharmaceutical vaccine
Science; Inovio Betta Pharma
Immuno- Celularity; Sorrento Recombinant Clover
Actemra Genentech/Roche Launched CYNK-001 Preclinical Cell Therapy Discovery Vaccine
modulator Therapeutics vaccine Biopharmaceuticals
Chongqing Zhifei
Aim Immunotech; GP Pharm Immuno- SARS-CoV-2 Live-attenuated Codagenix; Serum
Rintatolimod Launched Biological; Institute of Preclinical Vaccine Discovery Vaccine
SA; Goethe University modulator vaccine vaccine Institute of India
Microbiology
Adjuvant/COVID- SARS-CoV-2
ASC-09 + ritonavir Ascletis Pharma Phase III Anti-retroviral Novavax Preclinical Vaccine Curevac AG Discovery Vaccine
19 vaccine mRNA vaccine
Dyadic International;
Sichuan Kelun Prophylactic Monoclonal Antibody/
Remdesivir Gilead Phase III Antiviral S-protein/ACE2 Preclinical Israel Institute for Discovery
Pharmaceutical polypeptide antibodies/vaccine Vaccine
Biological Res
Immuno- ChAdOx1 nCoV- SARS-CoV-2 Fudan University; ID
Kevzara Regeneron/Sanofi Phase III/II Jenner Institute Preclinical Vaccine Discovery Vaccine
modulator 19 vaccine Pharma
Mesenchymal Wuhan Hamilton Guanhao Biotech; Zy
BDB-1 Beijing Defengrei Biotechnology Phase II Antibody Preclinical Cell Therapy Z-VacciRNA Discovery Vaccine
stem cells Biotechnology Therapeutics
Brilacidin Innovation Pharmaceuticals Phase II Antibody
Protein subunit Regeneron SARS-CoV-2 Medigen' National
University of Queensland Discovery Vaccine Antibodies Discovery Antibody Discovery Vaccine
vaccine Pharmaceuticals vaccine Institutes of Health
Monoclonal Protein subunit
Vir Biotechnology Discovery Antibody Sanofi Pasteur Discovery Vaccine mRNA-1273 Moderna Therapeutics Discovery Vaccine
antibodies vaccine
Anti-SARS-CoV-2 Coronavirus Immunoprecise
Nanoviricides Discovery Nanoviricide Vaxart Discovery Vaccine Antibodies Discovery Antibody
program vaccine Antibodies
Source: Cortellis, Bioworld, Johns Hopkins, JPMAM. As of March 5, 2020.
12China equity markets and infections
Chinese daily infections versus Chinese equities
Daily number of cases Index level
1,000 3300
China
900 excluding Hubei
800 3200
700
600 3100
500
400 3000
300 Shanghai Stock
Exchange A Share
200 2900
Index
100
0 2800
Jan 23 Jan 31 Feb 08 Feb 16 Feb 24 Mar 03 Mar 11 Mar 19
Source: Bloomberg, Johns Hopkins University. March 18, 2020.
13A 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
High frequency Chinese economic indicators Chinese daily infections: Hubei vs ex-Hubei
Indicated level as a % of historical average Daily number of cases
100% 4,000
20 days after Chinese New Year (2/14)
Most recent level 3,500
3/14
80% 2/25 Hubei
3/17
3/17
3,000
3/17
60%
2,500
2/18
40% 2,000
3/12
1,500
3/11
20%
1,000
0%
Railway Electricity Traffic Coal Home Road Transport Box 500 China ex-
coal use jams consum. sales and rail hub office 0 Hubei
deliveries /factory travel passeng. revenues Jan 23 Jan 31 Feb 08 Feb 16 Feb 24 Mar 03 Mar 11 Mar 19
capacity flows
Source: J.P. Morgan Emerging Markets Research, Goldman Sachs. Mar 18, '20. Source: Bloomberg, Johns Hopkins University. March 18, 2020.
14One 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. 15
Where “flattening the curve” comes from
Great Britain critical care beds occupied per 100,000 of population
300
Do Nothing
250 Closing schools and universities
Case isolation
200
Case isolation and household quarantine
150 Case isolation, home quarantine, social
distancing of >70s
100
50
Surge critical care
bed capacity
0
Mar '20 Apr '20 May '20 Jun '20 Jul '20 Aug '20 Sep '20 Oct '20
Source: "Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and
healthcare demand", N Ferguson et al, Imperial College of London, March 2020.
16Mortality as a % of reported infections
Mortality rates: COVID-19 vs other diseases, and the impact of Wuhan/Hubei
Mortality rate; bubble size indicates relative number of fatalities for COVID-19 only
Pandemic measures:
8.5%
Italy, 8.3% (a) population of a given geographical area
8.0% COVID-19 (b) infected individuals, including both asymptomatic
7.5% Other diseases people and people that get sick
7.0% (c) people that are infected, get sick and self-report
6.5% Iran, 6.5% (d) number of people that die
6.0%
5.5% During the haze of a pandemic, best estimates that
5.0% Wuhan, 5.0%
entities like the World Health Organization often derive
Yellow Fever, 4.9%
4.5% Hubei, 4.6% Spain, 4.5%
are based on (a), (c) and (d), and even things like (d) are
4.0% China, 4.0% World ex China, 4.1% West Nile Virus (2013), 4.2% complicated by pandemics affecting older individuals
3.5%
with pre-existing conditions. They do not know (b)
Spanish flu (1918-1920), 3.5%
Cholera (2010), 3.2% upfront, and sometimes it is never known, or only known
3.0%
Netherlands, 2.8% with the passage of time. Swine Flu (H1N1/2009)
2.5% United Kingdom, 2.7%
example. Early mortality rate estimates in fall 2009:
2.0% Beijing, 1.7%
Henan, 1.7% France, 1.6% 1.0%-1.3%. Four years later: just 0.02%.
1.5% United States, 1.5%
Chongqing, 1.0% Switzerland, 0.9% Swine Flu (2009/Initial), 1.3%
1.0% China ex-Hubei, 0.9% South Korea, 1.0%
Shanghai, 0.8%
Guangdong, 0.6%
Diamond Princess, 1.0%
Belgium, 0.9%
US Flu, 2019, Age 65+, 0.8%
Measles, 0.7%
GIMBE Foundation: Italy infections likely ~100,000,
Anhui, 0.6%
0.5%
Hunan, 0.4%
Norway, 0.4%
Austria, 0.2%
Hepatitis A, 0.5%
Swine Flu (2009/Revised), 0.0%
which would reduce observed mortality rate to 2%
0.0% Jiangxi, 0.1% Germany, 0.2% US Flu, 2019, 0.1%
China Rest of World Lyme disease, Chicken Pox, 0.0%
Mortality rates shown for all countries with at least 1,000 infections to date. Sources: CDC, China National Health Commission, Center for Diamond Princess cruise ship: ability to observe both
Health Protection (HK), Global Health Data Exchange, Johns Hopkins University, Netherlands Institute for Health Services Research, Imperial
College of London, Mayo Clinic, World Health Organization, JPMAM. March 18, 2020. symptomatic and asymptomatic individuals
17Infection and mortality rates
Coronavirus mortality rate by age Coronavirus mortality rate based on pre-existing conditions
16% 12%
14%
Chronic respiratory disease
10%
No pre-existing conditions
12%
Cardiovascular disease
10% 8%
Current mortality rate
8% 6%
Hypertension
6%
Current mortality rate (3/18/2020) 4%
4%
Diabetes
Cancer
2% 2%
Study mortality rate (2/17/2020)
0%
0%
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80+
Source: Chinese CDC, WHO. February 2020. Source: Chinese Center for Disease Control and Prevention. February 2020.
18Infection and mortality rates
Distribution of COVID-19 mortality and infections by age Case fatality rate during and after the Spanish flu
% of total infected or deceased population Fatalities per 100 infected persons
35% 6
Mortality
Influenza fatality rate during the Spanish flu (1918-19)
30%
5
Influenza fatality rate after the Spanish flu (1928-29)
25%
4
Infections
20%
3
15%
2
10%
1
5%
0
0% 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80+ Age
Source: Chinese Center for Disease Control and Prevention. February 2020. Source: Taubenberger and Morens. 2006.
In Italy, mortality distribution even more skewed to the elderly: 88% of deaths
occurred in population 70+, compared to 50% in China
19Lessons learned 100 years ago, ignored in China
Excess pneumonia & influenza mortality in 43 US cities, • 100 years of history: get ahead of a pandemic
1918-1919, Excess deaths per 100,000 population
800 • Jan 1: Chinese officials required hospitals not to
700
transfer fever patients to another medical facility,
prevented doctors from publishing diagnosis and
600
treatment information for COVID-19
500 • Jan 1: Chinese government punished doctors for
400
discussing outbreak, required them to sign
documents saying they were spreading lies
300
Public health response • Jan 14: Wuhan Health Commission reported that
time (days)
200 there were no new coronavirus cases, and that risk
-15 -10 -5 0 5 10 15 20 25 30 35
Source: Markel et al, University of Michigan. 2007.
of human-to-human transmission is low
• During first three weeks of Jan, Wuhan hospitals
Faster public health response times = didn’t treat infected or asymptomatic outpatients as
lower mortality rates potentially infectious
• 40 infectious patients visiting clinics on Dec 31
ended up exposing 18,000 people before city shut
down on Jan 23
2021
0
4
8
2
6
12
14
0
10 AUT
SGP
JPN
MAL
BEL
NLD
CAN
SWI
5,000
USA
NOR
DEU
SWE
GBR
Beds and testing
FRA
ESP
KOR
Hospital beds per 1,000 people
10,000
Source: WHO, World Bank. March 16, 2020.
15,000
Number of infections
IRN
20,000
Hospital beds vs number of 2019-nCoV infections
25,000
ITA
0
1,000
2,000
3,000
4,000
5,000
6,000
South Korea Mar-17
Norway Mar-16
China – Guangdong Feb-24
Italy Mar-17
Denmark Mar-17
Australia Mar-17
Austria Mar-17
Canada Mar-17
Russia Mar-16
Taiwan Mar-17
United Kingdom Mar-17
Czech Republic Mar-17
Switzerland Mar-07
COVID-19 tests per million people
Israel Mar-09
Ireland Mar-09
Netherlands Mar-07
Croatia Mar-17
Poland Mar-16
United States Mar-13
France Mar-08
Finland Mar-11
Japan Mar-17
New Zealand Mar-17
Thailand Mar-17
Vietnam Mar-17
South Africa Mar-11
Source: Countries statistical reports by Esteban Ortiz-Ospina, IMF. Mar 17, '20
India Mar-13Equity markets
S&P 500 multiple derating S&P 500 price/earnings
Forward 12 month P/E, difference versus previous month Price / forward 12 month earnings per share
26x
0.0x
-0.5x 24x
-1.0x
-1.5x 22x
-2.0x 20x
-2.5x
-3.0x 18x
-3.5x 16x
-4.0x
-4.5x 14x
-5.0x
12x
-5.5x
-6.0x 10x
90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20 '90 '92 '94 '96 '98 '00 '02 '04 '06 '08 '10 '12 '14 '16 '18 '20
Source: JPMAM. IBES, Datastream, Bloomberg. March 18, 2020. Source: JPMAM. IBES, Datastream, Bloomberg. March 18, 2020.
22Equity markets
S&P 100 implied volatility index
Index level
100
90
80 3/18/2020 level
70
60
50
40
30
20
10
0
1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019
Source: Bloomberg. March 18, 2020.
23Equity markets
Positions in US equity futures by leveraged funds and Quantity-On-Loan of the SPY US ETF
asset managers, Spec positions as a percentage of open interest On loan quantity as a % share of share outstanding
30% 7%
25%
6%
20%
15% 5%
10%
4%
5%
0% 3%
-5% 2%
-10%
Extrapolated to March 17th 1%
-15% using open interest changes
-20% 0%
2012 2013 2014 2015 2016 2017 2018 2019 2020 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 17, 2020. Source: JPM Global Markets Strategy Flows & Liquidity. March 16, 2020.
24Credit markets
US high yield corporate bond spreads
US investment grade corporate bond spreads JPDFHYI index energy and ex-energy, basis points
Emerging market sovereign bond spreads
JULIS index, basis points JPSYAGSW index, basis points
600 2,200 1,000
550 2,000
900
500 1,800
1,600 800
450
1,400 Energy 700
400
350 1,200 600
300 1,000
500
250 800
400
200 600
400 300
150
100 200 Ex Energy 200
50 0 100
2014 2015 2016 2017 2018 2019 2020
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
Source: Bloomberg, J.P. Morgan. March 18, 2020. Source: Bloomberg, JPM HY Strategy team. March 18, 2020. Source:Bloomberg, J.P. Morgan. March 18, 2020.
Fixed rate preferred securities option adjusted spread AAA asset backed securities spreads 30Y fixed mortgage - 10Y US Treasury
POP1 index, basis points basis points basis points
650 350
1,600
600
1,400 550
500 300
1,200
450 Prime auto
1,000 400
350 250
800
300 Credit card
600 250 Commercial
real estate 200
200
400 150
200 100 150
50
0 0
-200 -50 100
2000 2004 2008 2012 2016 2020 '98 '00 '02 '04 '06 '08 '10 '12 '14 '16 '18 '20 '05 '06 '07 '08 '09 '10 '11 '12 '13 '14 '15 '16 '17 '18 '19 '20
Source: Bloomberg. March 18, 2020 Source: J.P. Morgan. March 18, 2020. Source: Bloomberg. March 18, 2020.
25Credit markets
Libor - federal funds rate
basis points
100
90
80
70
60
50
40
30
20
10
0
2015 2016 2017 2018 2019 2020
Source: Bloomberg. March 18, 2020.
26Emergency facilities, 2008-2009
Emergency facilities created by the Federal Reserve during
the Financial Crisis
Peak Outstanding
Balance ($ bn)
Term Auction Facility $493
Commercial Paper Funding Facility $348
Term Securities Lending Facility $236
Asset-Backed Commercial Paper Money Market
$152
Mutual Fund Liquidity Facility
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.
27How far do earnings fall in a recession?
S&P 500 earnings drawdowns
Maximum drawdown of earnings per share
0%
-10%
-20%
-30%
-40%
-50%
-60% Operating earnings
-70%
-80%
-90% Reported earnings
-100%
1870 1890 1910 1930 1950 1970 1990 2010
Source: Robert J. Shiller, S&P Dow Jones Indicies. Q4 2019.
28Earnings drawdowns, US vs Europe
European profits more sensitive to recessions
Maximum drawdown of earnings per share for respective MSCI country index
0%
-20%
-40%
-60%
-80%
France Germany
Italy USA
-100%
84
00
16
70
72
74
76
78
80
82
86
88
90
92
94
96
98
02
04
06
08
10
12
14
18
20
Source: J.P. Morgan Securities Inc., MSCI, Bloomberg. February 2020.
29What are equity markets now pricing in regarding S&P 500 earnings?
US EPS level implied by dividend futures
% of pre-virus level
20%
Pricing on Jan 20
10%
0%
-10%
-20%
-30%
Pricing today
-40%
-50%
2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Source: Bridgewater. March 17, 2020.
30What kind of crises play out over many years instead of over shorter periods? 31
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 32
A lot has changed in medical science in 100 years
US life expectancy at birth Spanish Flu (1918): % of cultures containing bacteria
years causing secondary respiratory infections/pneumonia
85 100 No bacteria found
80 90 All other bacteria
75 80
70 70
65 60
60 Female 50
40 Bacteria causing secondary respiratory infections
55 (Streptococcus pneumoniae/hemolyticus, Staphylococcus
30
50 aureus, other/mixed pneumopathogens)
20
45 10
40
Male
0
35 1975 Military samples Civilian samples Total
1990
2005
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1980
1985
1995
2000
2010
2015
Source: "Predominant Role of Bacterial Pneumonia as a Cause of Death in
Pandemic Influenza," National Institute of Allergy and Infectious Diseases,
Source: US CDC; Andrew Noymer, Public Health Dep't, UC Irvine. 2020. Morens et al, 2008
33A lot has changed in medical science in 100 years
Male life expectancy in France
years
80
This chart is a proxy for two things:
70 [1] astounding medical achievements of the
20th century, including tools scientists are now
60
using to develop vaccines and anti-viral
50 Absence of data during medications to combat COVID-19
French Revolution
[2] greater threats to life expectancy and
40 World War II prosperity have in modern times resulted less
(1939-1945)
30 from pandemics and natural disasters, and more
War of 1870 World War I from what people do to each other in times of
20 Napoleonic (1914-1918) war
wars
10
1740 1770 1800 1830 1860 1890 1920 1950 1980 2010
Source: French Institute for Demographic Studies (INED). 2018.
34Time capsule: disaster, ruin and recovery
Post Civil War recovery in Confederate farm income
Index, 100 = 1859
108
US Civil War: deadliest conflict in US history,
104 with 6x mortality rate as World War II...it left
the southern US in complete shambles… fought
100 mostly on southern soil, leaving many cities in
96
ruins with thousands of people lacking food,
clothing, or shelter… Federal government did
92 very little to assist them…and yet, look how
quickly Confederate farm income rebounded
88 after the war
84
1859 1862 1865 1868 1871 1874 1877 1880
Source: "Economic Behaviour in Adversity", Jack Hirshleifer, The University
of Chicago Press, 1987.
35What kind of crises require years for economies to recover?
Colossal wartime destruction…
It took a full decade for Germany and Japan to recover from
WWII, Real per capital GDP, 1990$, thousands
600
By 1945, 20% of Germany’s housing stock was
550
Germany destroyed, food production was half of 1938 levels,
500
450 industrial production was down by a third and caloric
400 intake was around 1,250 calories per day (average
350 American consumers 3,600 per day)
300
250 Japan As for Japan, around 40% of its capital stock, a quarter
200 of all housing and 180 miles of 67 cities were
150 destroyed by the war
100
1930 1935 1940 1945 1950 1955 1960
Source: Angus Maddison (Historical Statistics of the World Economy),
JPMAM. 2020.
36What kind of crises require years for economies to recover?
Or colossal economic mismanagement…
China's disastrous Great Leap Forward
Percent Calories/day
30% 2,300
Dutch historian Frank Dikotter,
25% US historian R. Joseph Rummel:
2,100
Calories/Day Great Leap Forward was the largest
20% (RHS) democide in human history
1,900
15%
1,700
10%
Mortality rate
(LHS)
5% 1,500
1955 1956 1957 1958 1959 1960 1961 1962 1963 1964
Source: "Visualizing the Effects of the Great Leap Forward", Basil Ashton, '84.
37Concluding with a time capsule of markets bottoming while fundamentals were still getting worse 38
Time capsule: high yield markets tend to bottom well before defaults peak
Savings and Loan Crisis Tech collapse Financial crisis
Spread-to-worst # of Issuers Spread-to-worst # of Issuers Spread-to-worst # of Issuers
1,200 300 1,200 500 2,500 250
High Yield credit 450
1,000 High Yield 250
spreads
1,000 High Yield credit
credit spreads 400 2,000
spreads
200
350
800 200 800
300 1,500 150
76%
600 150 600 250 Cumulative defaults
55% 200 1,000 100
400 100 400
150
Cumulative defaults Cumulative defaults 30%
100 500 50
200 50 200
50
0 0 0 0 0 0
1987 1988 1989 1990 1991 1992 1993 1999 2000 2001 2002 2003 2004 2006 2007 2008 2009 2010 2011 2012 2013
Source: J.P. Morgan Securities LLC. February 2014. Source: J.P. Morgan Securities LLC. February 2014. Source: J.P. Morgan Securities LLC. February 2014.
39Time capsule: bank stocks tend to bottom well before the peak in bank failures
The Great Depression: Equity market vs. bank failures Savings and Loan Crisis: Bank stocks vs. bank failures Financial crisis: Bank stocks vs. bank failures
Index level Total institutions Index level Total institutions Index level Total institutions
400 10,000 120 1,800 300 500
9,000 1,600
350 110 Cumulative
Bank Failures 250
Dow Jones Industrial 8,000
1,400 S&P 500 Bank Index 400
300 Average 100
7,000
1,200 200
250 90 S&P 500
6,000 300
Bank Index 1,000 SCAP
200 5,000 80
63% 150
48%
800
4,000 200
150 70
600 100
3,000
100 Cumulative Bank 60 Cumulative Bank
Failures 2,000 400 Failures 100
50
50 50 200 8%
1,000
0 0 40 0 0 0
Jan-29 Oct-29 Aug-30 Jun-31 Apr-32 Feb-33 Dec-33 Mar-88 May-89 Jun-90 Jul-91 Aug-92 Sep-93 Oct-94 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14
Source: FDIC, Bloomberg. March 2014. Source: FDIC, Bloomberg. March 2014. Source: FDIC, Bloomberg. March 2014.
40Time capsule: credit markets tend to bottom way before default rates peak
Leveraged Loan prices vs. defaults: 2006 to 2011 CMBS spreads vs. delinquency rates: 2006 to 2014
Price index Default rate AAA CMBS Spread (basis points) 60+ day delinquency rate
105 9% 1,600 9%
100 8% 1,400 8%
95 7% 1,200 7%
60+ delinquency rate
90 6% 6%
Leveraged Loan 1,000
85 Price Index 5% 5%
800
80 4% 4%
600 AAA CMBS
75 3% Spread 3%
70 2% 400
Defaults over 2%
65 trailing 12 months 1% 200 1%
60 0% 0 0%
2006 2007 2008 2009 2010 2011 2006 2007 2008 2009 2010 2011 2012 2013 2014
Source: J.P. Morgan Securities LLC, Standard and Poor's, S&P/LSTA
Leveraged Loan Index. February 2014. Source: Trepp, J.P. Morgan Securities LLC. February 2014.
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