If the question posed was, “What do you get when you combine an emerging and atypical deadly pandemic, a near-global economic cease-and-desist order, a worldwide oil price war, partisan and dysfunctional political maneuvering, and seemingly untethered and limitless monetary expansion by central banks?” : the answer would have to be “the month of March in the year 2020.” The first quarter came in like a lamb, modestly building on last year’s substantial gains, but March arrived like a lion. A very angry lion. The Dow Jones Industrial Average saw the most precipitous decline in its history, losing almost 34% of its market value over 22 trading days. In 1987, the Dow lost 33% in 38 trading days; in 1929 the Dow lost 29% in 43 trading days; and in 2007, the Dow lost 14% over 75 trading days. This year’s decline was quicker and steeper. The S&P 500 Index saw two of the six largest single-day percentage declines during this period: a 9.5% decline on March 12th and a 12.0% decline on March 16th.
The CBOE Volatility Index (the VIX, or the so-called “fear index”) surged to over 80, after spending most of the previous decade within a stone’s throw of single-digits. Yield spreads blew out, as well. In January, investors demanded less than a percentage point premium in yield over Treasuries for investment grade bonds. That premium tripled by late March. In January, junk bond investors required a 3.4 percentage premium over Treasury interest rates, but by late March they demanded a premium of 10.1 percentage points. By March 23rd, the Dow was down 34.9% for the year, the S&P 500 was down 30.7% and the Nasdaq Composite had declined 24.0%. Almost all individual international country indices were down in the 30-40% range. And then things turned and markets caught a bid. Italy saw new COVID-19 cases level out. Congress got serious about emergency legislation, and moved toward an aid package that was over three-times larger than initial proposals. Investors began to reconsider their assessment of unlimited quantitative easing by the Federal Reserve. By the end of the quarter, the Dow Jones Industrial Average was down 23.2% for the year, the Standard & Poor’s 500 Index had fallen 20.0% and the Nasdaq Composite had declined 14.2%. The equity markets continued to rebound through early April, with the S&P 500 Index up about 25% from its March lows, but still down 11.0% year-to-date. Other than that, Mrs. Lincoln, how did you enjoy the play?
There is no downplaying the breadth and potential depth of the COVID-19 pandemic. There is also no downplaying the breadth and potential depth of the economic consequences of the measures already undertaken to retard COVID-19’s manic acceleration. There are no good choices, merely painful trade-offs. The abrupt shut-down of global economic activity to minimize infectious contacts is a draconian measure. And, to be sure, it is an experiment. In the U.S., the economic effect can be seen in unemployment filings. In February, the U.S. unemployment rate was 3.5%. In March, the rate climbed to 4.4% as the economy went from creating 275,000 jobs to losing 701,000 jobs. These numbers will be revised upward, undoubtedly. In February, there were 5.8 million unemployed Americans out of a labor force of 162.9 million. Since then, over 22 million Americans have filed for unemployment insurance. This suggests an unemployment rate of at least 17% and growing.... a lot. To put this in context, during the depth of the Depression, American unemployment was estimated to peak at close to 25%.
Stay-at-home measures will blow a huge hole in the income and wealth of both the labor force and the business community. To fill these holes, extraordinary fiscal and monetary actions have been commenced. On the monetary side, the Federal Reserve committed to expand its Permanent Open Market Operations (POMO) to purchase an additional $500 billion of Treasuries and $200 billion of Agency Mortgage-backed securities. After the market dismissed this effort, on March 23rd the Fed expanded its operations to unspecified “amounts needed to support smooth market functioning.” In other words, more. At the height of the Great Financial Crisis, the Fed expanded its balance sheet through quantitative easing to 25.5% of U.S. GDP from only 5.9% of GDP before the crisis. Wall Street estimates that the Fed’s POMO will expand its balance sheet 140% to the $10.0 trillion range. The Federal Reserve also greatly expanded Temporary Open Market Operations by $1.0 trillion to bring liquidity to the short-term funding market, reintroduced a commercial paper funding facility, restarted a Money Market Liquidity Facility and a Primary Dealer Credit Facility, to support money market mutual funds and encourage financial institutions to purchase Treasuries directly from the government. Additionally, the Fed instituted the Primary Market Corporate Credit Facility to support the investment-grade corporate funding market. This is unprecedented. It also established Secondary Market Corporate Credit Facility, which would allow it to buy corporate bonds and corporate bond ETFs in the secondary market. This is really unprecedented… and, probably illegal. Finally, the Fed expanded foreign exchange swap lines to assure that dollars, the world’s reserve currency, are readily available to other central banks. The Fed has gone to extraordinary lengths to fill the hole in wealth and income created by shutting down the economy. But, at the end of the day, it has not created wealth and income in any real sense. It has facilitated orderly markets by printing money, and that new supply of dollars will be evident sometime in the future.
On the fiscal side, Congress passed the Coronavirus Aid, Relief, and Economic Security (CARES) Act on March 27th. This 800-page monstrosity’s cost will tally to about $2.2 trillion. The bill was originally proposed at a cost of $650-$750 billion, but much can change in Washington over the course of a few weeks. It is filled with pork, which is unfortunate and infuriating. But, in all fairness, the breadth and economic impact of impending stay-at-home measures crystalized during negotiations for the final bill, and legislators realized that incentives were necessary to guarantee some level of compliance. The breakdown of the relief bill comes to approximately $600 billion in aid to individuals, $500 billion in aid to large companies (like airlines), $380 billion in aid to small businesses, $340 billion to state and local governments, $160 billion for public health and a few hundred billion dollars for Education, safety-net provisions, pork, bribes and Congressional pay-offs. As we write this, Congress is negotiating to supplement the small business aid by adding $300 billion to the Paycheck Protection Program. These fiscal measures are of a size never seen before. The budget deficit was hovering around $1.0 trillion before the pandemic; now it is difficult to imagine that it will finish the year below $4.3 trillion. That is a lot of cabbage. The effort is global. The IMF estimates that the world’s twenty richest countries have earmarked 3.5% of their GDPs to the pandemic crisis, more than they spent at the nadir of the Great Financial Crisis. It further estimates that gross fiscal debt in advanced economies will expand 16% this year, to 122% of GDP. We now have an idea of the global resources being thrown at COVID-19. It is a mind-numbing amount. What do we get for this exorbitant cost?
Here it is crucial to be ruthlessly objective and realistic in our expectations. We need to be honest in our assessments of three important factors: 1) What the near-global stay-in-place experiment was meant to accomplish; 2) Who bears the preponderance of the burden of this disease; and 3) What do we know now and what do we not know.
Shutting down the economy was designed to reduce infectious interactions and contamination and to “flatten the curve” of new infections and related deaths. The effort was never intended to eradicate the virus, for that would be next to impossible without a vaccine. Flattening the curve was intended to buy some time to build more medical infrastructure so that hospitals and intensive care units would not be overwhelmed, resulting in excess deaths. Largely, it was designed to spread out the timing of deaths rather than to reduce their numbers. Additionally, although most COVID-19 mortality charts show both an accelerated curve and a flattened curve, almost none carry the projection period past this August. That is because the models used to project these mortality curves all anticipate another future acceleration of the death rate in the fall or winter of this year. The death humps are shown to continue, periodically, until a vaccine is developed in a year or 18-months, or herd immunity is achieved. We have always found this manner of presentation to be manipulative at best, and duplicitous at worst. In other words, the infection will outlast any economic pause and elevated death rates will resume in the future, according to these projections. The data used by these models is, however, incomplete.
The best data that we have concerns who will bear the greatest burden from COVID-19. Obviously, medical workers and first responders are disproportionately exposed to the virus, and are tragically at higher risk. In the general patient population, the data is clear. Fatality risk is highest among the old and sick. In New York State, 12,324 of the 13,869 COVID deaths had at least one comorbidity, with hypertension and diabetes being the most common. Heart disease, lung disease, dementia and cancer were all significant factors increasing fatality risk. In New York State, 84.2% of the fatalities were over the age of 60, and 37.8% were over the age of 80. Those from 50-59 experienced 9.8% of the total COVID deaths, the 40-49 cohort saw 3.7% of deaths, and those aged 30-39 saw 1.6% of deaths. Of the 13,869 deaths, only 63 were younger than 20, and only one was younger than 9 years old. Men represent about 60% of the deaths, and women 40%. Blacks and Hispanics were over-represented in the fatality totals relative to their share of the general population while Whites and Asians were under-represented. Fatalities originating in nursing homes and adult care facilities constituted about 25% of total fatalities. COVID-19 is harshest to the aged and the unhealthy, while the young and healthy tend to recover from an infection. About 15% of Americans are over the age of 65, and maybe a third of these have serious comorbidities. This is the part of the population that is likely at risk of a significantly higher death rate from COVID-19, about 15 million Americans. We should focus our efforts on protecting this population from exposure to the virus. If 100% of the currently projected COVID-19 deaths come from this cohort, the death rate would be 0.4%, or about four times the average morbidity rate of the seasonal flu. We will have expended $37 million per un-avoided death, or $2.2 trillion divided by 60,000 expected fatalities.
We need to be rigorous about what we know and what we don’t know. Pandemics are terrifying, and a novel virus with high contagion levels is even more terrifying. Public health officials will always err on the conservative side, eventually. Once out, there is no way to put the genie back in the bottle. Making matters worse, two of the first serious outbreaks happened in China and Iran, and there is little reason to be confident of the accuracy of the data they chose to release. Outbreaks were already established in China, Iran, Italy, South Korea, France and Spain when the first comprehensive projection of the likely trajectory of the pandemic was released by Imperial College London. Their model, released March 16th, projected up to 2.2 million COVID-19 deaths in the U.S. unless drastic and prolonged action were taken: "In the U.K. and U.S. context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases, and household quarantine of their family members. This may need to be supplemented by school and university closures." Even though Imperial College was the accepted authority on epidemiological modelling in the U.K., widespread statistical and medical questioning forced them to tone down their projections. But not before terrifying the entire world while refusing to publish their assumptions and model code.
The model that the Trump Administration’s public health experts seem to be following was published by IHME (The Institute for Health Metrics and Evaluation) at the University of Washington. IMHE originally projected between 100,00 and 240,000 COVID-19 deaths in the U.S. with strict social distancing practices. This was at a time when fewer than 4,600 total cases were identified in the entire U.S. The IMHE model also projected an extreme shortage of hospital beds, ICU beds and ventilators. Over time, the IMHE has reduced its central projection to about 60,000 U.S. deaths from COVID-19 this year (down from a projection of 68,000 last week). Specific projections for New York overshot expected deaths, and really overestimated the demand for facilities and ventilators. The IMHE model always assumed the type of draconian social distancing methods that we are employing, so the reduction in projected fatalities should be unrelated to the shutdown.
Professor George E.P. Box, a statistician, said, “All models are wrong; some are useful.” We would hate to have to model the pandemic with the data that is currently available, but if forced, our confidence corridors would have been decisively larger than either Imperial College or IMHE. Epidemiologists and public health statisticians are missing crucial variables: rate of contagion, case fatality rate, infection fatality rate, general population susceptibility rate, symptomatic versus asymptomatic infection rate, reinfection susceptibilities and frequency and infectious exposure periods. Additionally, random population data sample testing, which could fill in some of these data deserts, seems woefully inadequate worldwide, not just in the U.S. It almost seems like willful professional ignorance to our inexpert eye. The IMHE model appears to be a data-fitting math model of the epidemic, with machine-learning to adjust the projections according to new data inputs. The Imperial College model appears to be a classic SEIR epidemiological model that makes assumptions regarding population Susceptibility, projected susceptible population Exposure levels, Infection rates and Resolution (death or recovery), and spits out a range of death rates. Anyone who has done any Bayesian modelling knows that things can go off the rails pretty quickly when one early factor is really wrong. Maybe false precision was the issue at Imperial College. In any case, their model was not useful.
Meanwhile, the 1,000 or so research papers published in scientific journals seem to be practically ignoring the COVID-19 Rosetta Stone, inadvertent lab experiments. The Diamond Princess cruise ship had a COVID-19 outbreak in late January. The ship was quarantined for a month. Of the 3,711 passengers and crew, 712 eventually tested positive for COVID-19 with about half symptomatic and half asymptomatic. Twelve passengers eventually died, all over 70 years old, and the majority were men. We can not think of a laboratory more conducive to encouraging infection and studying contagion and resolution. Confined quarters, recirculated and air-conditioned ventilation, isolation from exogeneous influences, monitored behavior and spacing…and great Daiquiris and Margaritas. We are not aware of any follow-up serological studies that have been taken among the crew and passengers to identify antibody prevalence, which is a shame. This is a data treasure trove, despite any quibbles one might have with a non-randomly selected population. Subsequent to the Diamond Princess outbreak, COVID-19 hit the U.S aircraft carrier USS Theodore Roosevelt. Data is still emerging here, but preliminary disclosures suggest that of 4,800 crew, 655 tested positive with almost 60% of those asymptomatic at the time of testing. To date, one sailor has died. If the CDC does not follow every crewmember with serological testing, the entire agency should be disbanded. The data from the two ships seem reasonably consistent, given what we know about mortality risk and the small and skewed sample sizes. The fact that neither ship experienced a majority of occupants infected, despite the ideal conditions, suggests to us that the pro-modelers might be overestimating general population susceptibility levels. We have no epidemiological or statistical expertise, but we try to be curious and practical. We are confounded by the lack of expert follow-through. We would guess that the ship results are more reliable than data either from China or Iran.
Given that we will be spending and borrowing an unimaginable sum, purposefully sending the economy into a bespoke depression, basing our hurried decisions on “known unknowns,” and ruining the economic foundation of millions of Americans, how will we know if we got our money’s worth? It almost sounds awkward when the question is posed as such. Especially when one considers that the entire exercise is focused on re-scheduling deaths rather than reducing them. We will probably never know for sure, but we think we know what the experts will tell us. Unless, of course, Sweden is successful. Unlike its neighbors, Denmark and Norway, Sweden did not institute mandatory shelter-in-place regulations. Sweden’s chief epidemiologist thought that the country’s hospitals could handle a surge in COVID cases, and thought that it was pointless to try to pace the development of the pandemic. While high schools and universities were closed, restaurants, shops and bars were allowed to remain open. Citizens were advised to take prudent precautions, but behavior was not mandated. Additional restrictions were suggested to protect at-risk patients at residences and in nursing homes. The Swedish government bought-in to the plan, reasoning that voluntary compliance could be maintained for a much longer duration than mandated compliance. It is too early to draw definitive conclusions, but so far, the medical infrastructure has not been overwhelmed. Net new cases of COVID-19 have been much higher than those of its neighbors, but the new case rate might be plateauing at a manageable level. Morbidity has been higher than in Denmark and Norway, and the hospitalized population has skewed younger. Comorbidities, as elsewhere, is a significant contributor to fatality risk. Nursing home COVID hotspots have been a problem in Sweden, as elsewhere. In the meantime, Sweden is growing the antibody pool in the population at a much faster rate than its neighbors. The government and most Swedes think the plan is working, although it is early days. Needless to say, Sweden’s strategy is very unpopular with those who have embraced a more top-down, restrictive model to deal with the pandemic. As far as we can ascertain, Sweden is the only developed country that has chosen not to shut down its economy. It faces withering criticism from both the left and the right to stop its irresponsible experiment immediately. Ironically, Sweden’s methods are not an experiment at all. Sweden is isolating the infectious while investing and spending on targeted resources. It is the rest of the world that is experimenting by isolating the uninfected and destroying both economic supply and demand. We have no idea whether Sweden’s strategy will prove to be effective, or even whether it was prudent to go down this path. But we do hope that they will continue as long as possible. The rest of the world could use data from an independent comparator.
Market gyrations like those experienced in the first few weeks of March can unnerve even the most experienced investors. We believe that proper and prudent asset allocation is crucial to portfolio design. We need your input to assure that your near-term cash needs are aligned with your longer-term portfolio strategy. We are in the midst of an unprecedented global experiment. Even if it does not end up well, we have a great deal of confidence in the American system and the American people to repair and, if necessary, remake our economy. Thank you for your support.
Your Team at Baxter Investment Management