Using Quantitative Analysis to Understand Our Crisis
There is a wide range of opinion about how bad the economic crisis that we are in will be and if and when we will ever recover. Quantitative analysis can shed real light on this.
In the financial world, we normally think of quantitative analysis, or QA, as the study of the movement of asset prices to gain more insight into where they may be headed. QA can be quite useful for other things as well, for instance trying to get a better handle on the progression of COVID-19 which is behind the economic crisis that we are currently facing.
What QA seeks to do is to take incomplete information and look to delve into probabilities, such as the probability of a stock’s price continuing to rise or the risk of things reversing. While this does include things like measuring and comparing trends, the entire task involves anything that is quantifiable that can help us understand the data that we do have, and continue to revise our projections as more and more data becomes available.
It is not enough to just study the data, as there is a clear qualitative aspect to doing QA well, making sure that we look at the right things and understand them the right way. The COVID-19 situation provides us an excellent opportunity to demonstrate the right and wrong way to do this, and this has taken on particular importance given that our approach to this data will influence how quickly we recover from the economic aftermath that has been left in its wake.
There is a wide divergence of predictions about this, and these economic projections cannot be simply discovered by looking, as this will all depend on predicting well how our response to the virus will play out as we gain more and more data on that front. Even if we knew exactly what the economic impact will be today, this requires that we get to normal right now in order to be valid, and we know that that won’t happen for a little while anyway.
Those who are seeking to predict the virus side of things are using QA to a great extent, whether they are aware of it fully or even not at all. We not only need to understand the actual situation as well as we can, we also need to understand where others have gone wrong because that is what will actually have to change to get to a more correct viewpoint and ensure that we are acting appropriately and not just guessing badly.
We started out with some pretty fantastic projections, with talk of this being as bad or worse than the Spanish flu. Even at this point in time, when so much has played out and we have a much better picture of things than we did when this first started, there are still some models out there which some hold to be valid which has COVID-19 several times worse than the Spanish flu, which caused upwards of 100 million deaths worldwide about 100 years ago.
If there was any validity to this, it would be appropriate to panic, and so this is the first place we need to start using QA to assess what risk such a thing would present. We’ve come a long way since these early models, but much of the public still has lingering fears about the risk of this, and this does continue to guide public policy to some degree even though we have seen this horror story being less and less regarded each day now.
We are seeing the people who foresee millions or even hundreds of millions of people show their work more now though, and in this particular model that is currently making the rounds in the media, the assumption is that 80% of the world’s population may become infected, with a mortality rate of 5%. Sure enough, that’s around three times the death toll of the Spanish flu, coming in at around 300 million deaths.
The 80% infection rate does not seem unreasonable or unrealistic, so if the mortality rate of this disease really is that high, 5%, we are in real trouble. Even if it were just 1%, a number that people find much more realistic these days, that still makes things almost as bad as the Spanish flu, with 60 million deaths. That at least would be a death toll of truly epic proportions and something we may indeed wish to take extreme measures against, such as the lockdowns we’re using.
Our current program of restriction is about as severe as we could ever manage and not starve people to death, as we still have to let them shop for food and other essentials, even though we may not wish them to travel, shop at other stores, and generally avoid personal contact when possible.
With the death rate among those cases with an outcome currently at 21% worldwide and 39% in the U.S., that might seem pretty ominous. Right off the bat though we can reason that we can’t rely on this data, because while we can be confident about the number of deaths, we can’t assume that those known to be infected will continue to die at that rate, since it generally takes longer to recover than to die from this.
No one is using numbers like that, and even the most horrendous models assume a much lower mortality rate than 21%. If we look at those diagnosed versus the mortality rate, we get a lower number at least, but 8.8% is still unreasonably high, and no one is using such a high number either.
We then need to ask why not, and answering this question by looking at it from a QA perspective will actually explain why even 1% is so unrealistically high. In order to discover the mortality rate of something, we need to compare the number of deaths with at least some reasonable idea of how many cases of infection we have.
We actually do this, but if we underestimate the number of infections, we will in turn overestimate the mortality rate. This is where things can get tricky, although perhaps not as tricky has it has been for a lot of people looking to figure this out.
We know, from even the most simplistic understanding of statistics, that at any given time, there has to be a lot more people that have been infected with this virus thus far than the number of positive tests indicate. We can use the U.S. as an example, where the probability of positive tests has hung around 1 in 5 for quite some time now.
QA Tells Us That There Are a Lot More People That Got This Virus Than We Thought
Using just the testing results we have and then projecting this upon the population, getting the same number of deaths spread across 112 times more people, this will understate the mortality rate, because with the selective testing that we have used, those who are ill represent a disproportionately large amount, with those less sick or asymptomatic representing a disproportionately small amount.
If we had this data separated well enough, and we did enough testing, we would have a better idea of what the true mortality rate would be from this, but we do not, so we are left to do some pretty broad estimating. We still need to make sure that these estimates are reasonable though.
We know from the data that we have about the spread rate from epidemiologists that this does spread pretty easily, more easily than the flu and far higher than the other “pandemics” that we have had in the past, like SARS. This is not even something that we could dispute very much, and is confirmed in the lab and not just a wild guess.
When we put together this spread rate with the infection rate gathered by the testing data, we’re talking about a lot of people indeed being infected. We offered an educated guess of 5% a while ago, but time as passed since then and this could be even higher in the U.S. now.
If the sample that we have gathered so far was representative, this would mean that we would have 65 million infections so far, but once again, we can’t just project this rate upon the entire population due to the statistical bias of testing more sick people rather than a random sample. When we get some significant serology data, which we can sample more randomly, we’ll have a better idea then, but we still need to make an educated estimate of this because this is important to know now.
The actual number lies somewhere in between the half a million that we have discovered already and this 65 million. It doesn’t really matter whether this is only 15 million, a low estimate, or 30 million, because both numbers are well beyond any projections of doom or even close to it.
This may not provide any real level of accuracy in estimating the number of cases or the actual mortality rate, but it does allow us to exclude the crazy numbers such as deaths in the millions, and we thankfully have a good model now, the one that has us around 60,000 in total. We finally got around to getting a much better estimate on how many people probably have or have had COVID-19 now, a lot more than we thought, and it’s serving to soothe nerves, although not as much as it should as it turned out.
The reason why we really need more realistic numbers is that we use this to estimate how many more infections are to come. If we’re halfway to the final number, this would generally involve multiplying the number of deaths by two, or if we’re only a third of the way there, we’d be multiplying this by three.
This is not an aspect that we’ve put enough thought into though, as even the latest models tell us that they are assuming a total shutdown until completion. This tells us that their estimate of the reach of this is quite small, especially when we hear that if we don’t keep things shut down this could be far worse, where the monster that we used to refer to as on the way still lies.
One of the major purposes of QA is to allow for comparative analysis, and thankfully we do have such data to work with. If their assumptions were true, then in places that have not locked anything down, we would surely see this explosion, and if we do not, this would serve as convincing evidence that this belief is simply overblown.
The fact that stay at home orders even help very much is not clear at all, and in fact, by looking at the data, its effect is slight at best. The vast improvement that is believed to be achieved happens to be one of the assumptions of the model, but when reality has a different story to tell, it should not be difficult to see who is right, the wild guesses or what has actually happened.
The experience in Sweden, for instance, isn’t remarkably different from the average among countries that do have mandated stay at home orders in place. This tells us a lot, and not just that the difference with or without a lockdown isn’t really that meaningful, as it also tells us quite a bit about how much this virus spreads during a lockdown, which is even more important.
Sweden actually has a considerably lower percentage of their population infected, even though the reach of their tests has been so much less. The U.S. is up to testing almost one percent, while Sweden is still around only half a percent. This means that the focus in Sweden has been more concentrated on those actually sick, where we would expect a higher percentage of infections from than the U.S., not a lower percentage.
What’s even more notable and encouraging is Sweden’s numbers being on the decline in spite of no lockdown. If we believe that our numbers will greatly escalate if we return to normal, and another area who has never had any of these restrictions hasn’t had that happen to them, this idea should be seen to fall on its face.
You don’t even have to look outside the U.S. to see this at work, as there still are states out there who haven’t gotten with the program, but do not have an experience that is remarkably different from the country averages. Not only is the Bogeyman not here, he isn’t around the corner either, and isn’t even associated with this virus. It isn’t real in the bad dreams of kids either though, but can still pull much weight.
We Need Understand the Real Risks If We Want to Recover our Lives and Minds
If we can kill this mythical monster, this will make all of the difference in our getting back to normal. It may be dying, but far too slowly. We worried about the Bogeyman taking over the world at one time, a monster greater than we have ever seen before, and then moved to “if you say your prayers, he won’t come.” We need to take this one step further and banish him because he simply is not real.
The 60,000 deaths are not from the Bogeyman, that’s more like a mouse running around your floor, equal to a bad flu season. The real monster is the one that is supposed to kill millions of Americans alone, the one that we dreamed up and still do so to some degree.
Then there are the Bogeymen to come. Once this does virtually go away, at a threshold that becomes simply meaningless like it is already in Asia, then we’re still supposed to be this scared, as this monster may just be hiding under the bed and may come out an attack us in October or at some other time in our near future. Many believe we will never be rid of these monsters, and they will somehow continue to haunt us for all time.
Once again, we need to put on our QA hats and do some comparative analysis as well as a little simple reasoning. There are some viruses, like various forms of what we call the common flu, that persist, but they do so by way of mutation. Like bacteria, we kill these viruses but not completely, but they morph into a different form and attack us again next year.
This might seem like a legitimate threat, but the idea of this being a seasonal virus is pure speculation at this point. It is fine to speculate, and sometimes that’s all you can do, but there is good speculation and the poor kind, and even if we have limited data that we have to use what we have.
COVID-19, from what we know about it so far, is more like other coronaviruses rather than like influenza. Even the worst outbreaks of the flu though, including the Spanish flu, are not enduring, as people develop immunity to them and they don’t come back to hammer us again like they did once this has been achieved. This gets achieved quite naturally, without the need of vaccination, due to what is called herd immunity.
Whether or not you can get affected with COVID-19 again once you’ve had it hasn’t been shown yet, and we’re left to speculate once again, but this remains unlikely. We need to keep our fear of monsters confined to the real ones, and need to wait until they actually show their face.
The idea that we need a vaccine to put this one to bed is another product of our wild imaginations these days, and even the models are telling us that this will go away soon. It is already gone in other countries and you don’t need a vaccine when people aren’t even getting infected anymore on any meaningful scale. Otherwise, there’s nothing to vaccinate against.
Even if this does come back, it comes back to a far lesser degree, as this is just how viruses work, due to herd immunity. If, by some strange stroke of improbability, we do need a vaccine to control this, that is one thing, but people are speaking as if this is certain when this is far from the case.
The most interesting data though by far is the actual data that we have, although many people do not seem to be paying attention. This is serving to calm things down more these days, but nowhere near enough yet.
There are even people in the financial world who are looking to predict the extent of the economic damage who believe that this viral infection will not peak until the summer. Someone needs to point out to them that cases in the U.S. peaked 10 days ago, and are now in significant decline. Just in the last 4 days, the cases have declined each day to a total of 20% less. This is all going on while we ramp up testing more and more, which would produce the opposite effect if the rate wasn’t going down by quite a bit.
This is not to say that there isn’t the potential for a relapse, but it’s far less likely than not. We’re dealing with probabilities here, and you have to go with the probabilities because that’s all you have to work with.
We’re also seeing a significant decline in other countries, especially those that have been hit the hardest, like the U.S. has been. Countries like Spain, Italy, and Germany all peaked over two weeks ago and are now down to less than half of the daily infections that they once suffered from. Numbers are going down in other major countries as well, and the U.S. is actually the laggard here.
This data tells us more than things winding down, they are telling us that we are developing the herd immunity that people long for and assume we won’t get. This is more than just speculation, as there actually isn’t another good explanation for the numbers to decline so much this soon.
We know that this virus does spread pretty rapidly, and if it does spread at twice the rate of the flu, that’s a lot of spread indeed as the flu spreads at a very high rate. The spread rates that the epidemiologists came up with is one thing that they have seemed to calculate well, and would be on the low side if anything given that stay at home orders haven’t been shown to make that big of a difference.
The reason why this is so significant is that we have to achieve a critical mass before we see inflection rates decline, where so many people who become exposed to it already have immunity that the rate of new infections actually declines.
This in itself is the most significant observation that QA can provide us, by looking at these trends and being able to decide that this could not be from the small percentage of people being infected by this that people are assuming.
The spread rate is the constant here, with people being exposed at a given rate whether we are mostly staying at home or not, because this practice did not change over the period we are looking at. More and more testing with less and less infections, with the same number of people being exposed, means that less and less people are prone to it, meaning more and more of us have achieved immunity.
This strongly supports the idea that there are a lot more infections out there than just the ones we have discovered, because this has to be the case or the numbers would just keep going higher and higher until we achieved enough immunity.
In the end though, the numbers will bear this all out, and we don’t even have to be thinking analytically to realize that this is going away more and more each day these days and this is a trend we can rely on continuing.
Even people like Gov. Cuomo and Dr. Fauci are starting to come around more now, both suggesting that we could start opening things up on a limited basis at least very soon. There still is a strong underlying current toward continued restriction, with some even calling this the new normal, even though considering something that would lead to our demise normal is a very dangerous idea.
Quantitative analysis does not take us as far as the political realm, but it can help us understand what the risks actually are much better, providing a more realistic outlook on what we are up against. With a given degree of risk, we can still be risk averse, but people can always choose this themselves according to their means and preferences without being held hostage for longer than it would be reasonable to.
Restricting people’s freedom in the manner we have chosen really does need to be reserved as a last resort, where the risk is so dire that it would be foolish not to. Whether or not this means that it was a good idea in the first place, as the risk melts more and more toward virtually zero, we need to keep asking ourselves whether it makes any sense at all to see ourselves above this high threshold of risk.
This won’t even last in a meaningful way until the summer, and we have the trends to show this. As the data continues to unfold, and as we discover much more valid the interpretations of QA have turned out to be, we will come to appreciate that this process did not underestimate the threat, it just sought to better understand it and continues to do so. We can then be as risk averse as we wish, but knowing what the risks really are does help.
If we can leverage our skills as traders to help figure this all out, that places us in a position to interpret both the movement of stocks and how they may move in the near future, by envisioning how the other battle, the one against this virus, will proceed as well.
You don’t see thinking like a securities trader having much application in the real world, but sometimes you do.
Editor, MarketReview.com
Robert really stands out in the way that he is able to clarify things through the application of simple economic principles which he also makes easy to understand.
Contact Robert: robert@marketreview.com
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