Click HERE to access the FSInsight COVID-19 Daily Chartbook.
STRATEGY: China market post-pandemic leadership? Epicenter
We thought it would be helpful to take a look at the China markets YTD. After all, the first cases of COVID-19 were in China. And China has managed to largely vanquish the disease (albeit extremely strict lockdowns, nothing that any other region followed suit). And since the pandemic’s start, take a look below. Feb 19, 2020 was the S&P 500 peak, so it is a good measurement point:
– China equity market is up 30% since Feb 19, 2020, a massive, massive rally
– Epicenter sectors accounted for half of the market cap increase
– Epicenter outperformed Technology
– Defensives actually posted the strongest return at 58%
Source: Factset and Fundstrat
If China is a roadmap, S&P 500 might rally >20% in 2021 with leadership from Epicenter…
I was surprised by the extent of the China market rally. 30% gains since February and with half of the market cap gains from Epicenter groups (Cyclicals). Granted, there are differences between the regions, sector composition, etc. So it is not necessarily comparable. But if the US follows China:
– will S&P 500 rally another 24% in 2021? Maybe
– US epicenter has lost $1 trillion in market cap since Feb 2020
– If we see a comparable Epicenter rally, this implies ~30% gain for Epicenter in 2021
At a minimum, this puts some context and credibility to the epicenter rally seen over the past few days.
Source: Factset and Fundstrat
Daily COVID-19 cases are accelerating and we could see >200,000 cases within a few weeks…
Daily COVID-19 cases are setting new highs every day in the past few days. The latest figure is 129,675, and up >40,000 vs 7D ago. At this pace, we will see >200,000 cases before Thanksgiving. Wave 3 is gaining momentum. But the surge in cases has some glimpses of mitigation:
– Signs of peaking in the 6 states with the fastest growth, WI, IL, ID, ND, SD, UT, or WIINSU. 4 of the states seem to see daily cases rolling over (see below)
– Daily deaths are rising but the steepness is far lower than implied by the surge in cases
– But Miami is seeing a resurgence
– Wave 3 is still unfolding
There is a new peer-reviewed and comprehensive study, discussed in Point #3, looking at the sources of infections in the US. This is based upon cellphone mobility for 98 million users. The takeaway?
– Restaurants are, by a country mile, the largest source of spread in the US
– The authors recommend limiting dining capacity
Source: COVID-19 Tracking Project and Fundstrat
ADDENDUM: We are attaching the stock lists for our 3 portfolios:
We get several requests to give the updated list for our stock portfolios. We are including the links here:
– Granny Shots –> core stocks, based on 6 thematic/tactical portfolios
– Trifecta epicenter –> based on the convergence of Quant (tireless Ken), Rauscher (Global strategy), Sluymer (Technicals)
– Biden vs Trump –> based on correlation to either candidate odds
Granny Shots:
–> Click here
Trifecta Epicenter:
–> Click here
Biden White House vs. Trump White House:
–> Click here
POINT 1: Daily cases 129,675, +43,239 vs 7D ago — on pace to hit 200,000 by mid-Nov
The latest COVID-19 daily cases came in at 129,675, up +43,239 vs 7D ago. Wave 3 is gaining momentum, so we are not really near a peak in daily cases
– the spread of cases across the US is widening
– the fastest spread remains in the wave 3 states, in particular, WI, IL, ID, ND, SD, UT, or WIINSU.
– but other states are seeing higher cases and dominating top 10 are essentially all previously “unscathed” states
– we all should be cognizant that cooler weather is making spread faster, perhaps due to weaker immune systems or “indoor” time
Source: COVID-19 Tracking Project and Fundstrat
7D delta is now running at >40,000, which means we could be at 200,000 cases in two weeks
Again, the daily change vs 7D ago, in our view, is the leading indicator as it is what influences the 7D moving average.
– Daily cases are rising vs 7D ago,
– It is rising at >40,000 7D delta
At this pace, we could see daily cases rise to >200,000 within two weeks. So wave 3 is clearly gaining momentum.
Source: COVID-19 Tracking and Fundstrat
Source: COVID-19 Tracking and Fundstrat
Source: COVID-19 Tracking and Fundstrat
POINT 2: Wave 3: WIINSU county-level cases could be peaking in some states
We have been looking at different ways to give the best context to Wave 3. Up until now, Wave 3 for COVID-19 differs from Wave 1 and wave 2 for several reasons:
– it is spreading across states previously unscathed in wave 1 and wave 2
– it is more geographically disperse but mostly in the Mountains region
– 6 states are seeing the fastest spread, WI, IL, ID, ND, SD, UT, or WIINSU
– Unlike Wave 1 and wave 2, states caught up in wave 3 are largely laissez-faire, without any policy intervention
New:
– Daily cases per 1mm for wave 1 (NY tristate) and wave 2 (F-CAT) are identical for the first time
4 of 6 states in WIINSU seem to be seeing a potential rollover of daily cases…The most rapid spread of cases in the US is taking place in roughly 22 states, but concentrated in 6 states — WI, IL, ID, ND, SD and UT, or WIINSU. The rapid case growth in these areas surpasses that of NYC during its worst periods.
– of these, 4 states seem to be showing a potential peak/rollover of daily cases
– the states are WI, IL, ND and SD
Source: Johns Hopkins and Fundstrat
We have discussed how these 6 states are now the template for wave 3. Thus, if we see a peak in daily cases here, we can get a sense of how COVID-19 spread occurs in the rest of the US. Our base case, relying on data from forecasters such as IHME, is that wave 3 would not peak until mid-February 2021.
Daily case surge in Miami is not very encouraging however…
Below is the updated county-level case data for 3 large areas in Florida. These daily cases are scaled to “daily cases per 1mm residents”
– Miami is reporting 600 daily cases per 1mm which is a huge jump since September
– Ft Lauderdale and Orlando seem to be seeing a more muted wave 3
Miami’s daily cases are nearly 3X the US level and a reminder that COVID-19 is surging across many parts of the US. I think the wisest thing for any of us is to be vigilant.
Source: Johns Hopkins and Fundstrat
POINT 3: New study shows restaurants + gyms are primary source COVID-19 spread
A new study, published today in Nature.com (and peer-reviewed) used anonymous data to track sources of COVID-19 spread. There are multiple authors for this study (Serina Chang, Emma Pierson, Pang Wei Koh, Jaline Gerardin, Beth Redbird, David Grusky
& Jure Leskovec) and looked at the mobility of 98 million individuals across several major cities. We first saw reference to this study in the below Washington Post article.
– the study is unique because of the vast scale of the mobility data used, 98 million and matching this with infection data
https://www.washingtonpost.com/health/2020/11/10/coronavirus-restaurants-gyms-hotels-risk/
The report itself is 28 pages (link –> Study here) and we have included some charts and observations below. The authors tracked user movements hourly and built a predictive model of infection, based on their locations. These locations fell into roughly 20 groups and in 10 metro areas.
Their model has only three free parameters:
(1) transmission rates at points of interest (POIs),
(2) transmission rates at Census Block Group, or geographic areas (CBGs), and
(3) the initial proportion of exposed individuals
All three parameters remain constant over time.
Source: nature.com https://www.nature.com/articles/s41586-020-2923-3
Their conclusion is that a few venues are responsible for the majority of infections. In their words, “superspreader” POIs account for the large majority of infections:
– Restaurants
– Gyms
In other words, of the 20 or so types of venues tracked, this is the source of the vast majority of infections. They also found that lower-income CBGs or areas, had less ability to reduce mobility, which accounted for the surge in cases.
Source: nature.com https://www.nature.com/articles/s41586-020-2923-3
This is their model estimated impacts of various venues. The x-axis scale is log-scale, so each increment is 10X. As shown, topping the list are:
– Full-service restaurants at 10X more likely source of infections versus any other place
– a close second is fitness centers
– FYI, apparently new car dealers are the safest place to spend time
Source: nature.com https://www.nature.com/articles/s41586-020-2923-3
And when looking at metro areas, we can see how large the impacts of restaurants are to spread. The blue shaded areas are restaurants.
– the takeaway from the study is not “close restaurants” but rather to limit capacity
– in their view, the best tool is limiting capacity
– look at the massive impact in NYC and Philadelphia from restaurants
Source: nature.com https://www.nature.com/articles/s41586-020-2923-3