Mutant SARS-CoV-2 Viruses, Perceived Risk, Actual Risk

This will be a slightly longer than usual post.

Here is a picture of the new strain of COVID-19 that the media is pumping up:

While this initially sent the markets into a panic (coupled with politicians panicking and shutting off the UK to the rest of the world), this global exercise in preying upon an utter lack of virology and immunology continues, and the true messages are coming out in the marketplace – it’s a nothing. You’d expect Carnival (CCL) or Royal Caribbean (RCL) to be a few percent down, but they’re not – down about 1% as I write this, which is market noise considering the S&P 500 is down for the day.

There are a significant number of people that actually think the news is a reliable source of information. Society has generally rewarded those that can think critically, but in this particular era, those that can are rewarded with mental health (i.e. you don’t have to live every day in fear of dying) and disproportionate gains in the financial marketplace.

So here is the story as I see it.

I am making an assumption that SARS-CoV-2 has to be the most globally tracked virus on the planet since HIV. Being a virus, it does mutate. Most people interpret the word “mutate” to be some sort of fictional character you see on fantasy movie, but a stealthy one that can’t be seen.

I’ll use HIV as an analogy for mutations. This was relevant for HIV as various anti-HIV drug cocktails started to lose their effectiveness as the surviving strains of HIV were resistant to various medications (this has more or less been eliminated with Viread and successors to the point where HIV concentrations are undetectable).

For SARS-CoV-2, just like all viruses, it has been mutating since day one. You can view a fancy map (you might want to do this on a higher powered desktop computer) of the various permutations.

Unlike the time when HIV was a real problem, today we have the advantage of rapid sequencing machines that can give a near real-time readout of viral genomes. Go look at the SARS-CoV-2 genome here.

I’m not a biologist or virologist or geneticist, but I understand enough of what I’m seeing to make a computer science analogy that what you’re looking at is assembly code for a program (virus). Even though I understand code and how assembly/machine language works from a very high level, if you give me a bunch of assembly code, I’ll have no idea what the heck it does (especially on x64 architecture!). Likewise, when looking at the various A-T, G-C base pairs, no clue.

A mutation changes the code slightly. Unlike in computer science where changing a line or two of code could break a program entirely (and indeed, the impact of such a change by a competent programmer can be predicted before hitting the “execute” button), in the biological world, changing a few lines of code has unpredictable impacts. In most cases, there is nothing seen.

Since I am using a lot of analogies in this post, it would be like measuring the performance response of your Toyota Corolla from the driver’s seat when you use 87 octane gasoline vs. the expensive 93 octane stuff.

The mechanism which SARS-CoV-2 is targeted with the Pfizer and Moderna vaccine uses a modified form of its spike protein in a manner which trains your immune system to recognize and fight it. Because the spike protein was identified early, they were able to create a vaccine in relatively quick order, early in 2020. It is only the clinical testing to prove effectiveness (and picking a proper dosage amount) that took time.

I would suspect that any mutations of the SARS-CoV-2 virus that changes the fundamental form of the spike protein to ‘evade’ immune response can also be identified fairly quickly and targeted with a vaccine. A virological cat and mouse game, so to speak.

Where else does this occur?

One example is with the seasonal flu shot vaccination.

Various strains of the flu (H1N1, H5N1, etc.) are picked based off of scientific judgement. Sometimes they pick wisely, sometimes they don’t. Unfortunately, it’s difficult to predict and measure after the fact.

It is like running an election campaign, and trying to ask yourself whether using message X helped you gain votes, lose votes or having no effect at all. You can’t “backtest” the election and run it again.

The claims of this new SARS-CoV-2 viral strain “may have increased the virus’ transmissibility by 70%” is most likely sensationalist, and a convenient political line to justify further sanctions on the populace. The underlying fact is that the virus has been mutating all the time.

Transmission is one factor, but more important is the severity the virus causes when you have it. Mutations, however, would have just as much of a chance of being less damaging than more damaging. In most cases, there is no impact clinically, similar to how HIV mutations caused AIDS.

Finally, we look at the overall clinical impact of SARS-CoV-2 infection.

British Columbia (and many other provincial/state jurisdictions) report COVID-19 statistics (search for “situation report” on this link).

In the most recent report, dated December 18, 2020, we have the following infection / ICU / death statistics to December 12, 2020:

There are differences between various regions (e.g. Alabama state will have a different profile than Washington State, in weather, demographics, etc.) but in all jurisdictions across the planet there is a very obvious trend – the number of people that SARS-CoV-2 kills is in line with the overall age morbidity. Hence in the chart above, the median age of death in British Columbia to COVID-19 is 86.

What we have been seeing over the past 9 months is healthcare dictated in a large part by political decree. Lockdowns, mandatory masks, and banning of spin and hot yoga, to name some. To name all of it would be the equivalent of the 613 decrees on the interpretation of the Jewish Torah. All of this is happening in real-time before us. Good luck being in perfect compliance!

Not surprisingly, when you get politicians making centrally planned decisions on how to deal with things, you get a very lowest common denominator response (i.e. everybody stop doing everything, except those that have curried the most favour with government). Political decisions made during this situation have likely added negative value to the whole overall situation, with relatively arbitrary and in many times contradictory instructions (e.g. the rationalizations of school openings vs. no outdoor social gatherings even of three people… oh, but it is OK to go walking together, as long as it isn’t a “social gathering” and you keep 2 meters apart!). No wonder why many people are going mentally ill – most are law-abiding citizens, but their minds can’t get around the fact that inherently the instructions are inconsistent and sometimes contradictory. Politicians behaving hypocritically adds fuel to the resentment fire.

Mainstream western societal culture has an expectation of zero risk. While this has driven safety improvements of all sorts, there is a diminishing return to the drive toward zero risk. An interesting paper to read is about risk and safety. When “one death is too many” is deemed to be the standard to live up to, you can be sure that this standard will be extremely expensive to implement.

Those jurisdictions with less exacting standards will inevitably gain huge competitive advantages of those that do not. There is obviously an optimal point of safety vs. cost, and we make this tradeoff all the time implicitly (e.g. when we get behind the wheel of a car, we are taking more of a risk than we perceive), but since COVID-19 is so front and center, there is a mass availability bias effect which overestimates the perception of risk.

There is a huge disconnection between the perception of risk and actual risk. People (and this includes governments, which are run by human beings that have the same flaws and have huge incentives to causing the fewest ripples which may compromise their position) react on perceptions, not actualities.

In the financial marketplace you can make a fortune when there is a situation where the perceived risk is high, but the actual risk is low. In fact, that is one of the main purposes of investment research – getting a feel of which risks and how much risk the market is pricing into a security versus your assessment of the actual risk of the financial instrument. When the perception of risk goes lower, the price will rise, regardless of whether the risk has changed or not.

My anticipation is that this “mutant strain” is a media construct that is designed to increase the perception of risk. The actual risk has not changed that much. From SARS-CoV-2, it remains very low.

Keep your wits and critical thinking minds on, since I do not anticipate this getting better until around April, and then there will be other fires to fight.

The push for yield at any cost – and a snippet on perception

It is amazing how markets cycle from panic to mania so quickly. It is a lot quicker now than it was a decade ago – one theory is that this acceleration of sentiment is fueled by social media.

I’ve been reading a bit more about perception and reality (e.g. ages ago, I linked to a TED talk that discusses the non-correlation being able to see reality and survival) and this is quite apt to describe what is going on in the financial marketplace.

Many participants in the market depend on “sources” such as BNN, CNBC, Jim Cramer, Reddit, Discus forums, Youtube, and for a very rare few, yours truly to come to their investment conclusions.

They are all trying to figure out how to put cash to use, because cash in a 10-year treasury bond yields 80 basis points at present. A million dollars gives you $8,000/year in (pre-tax) cash, which is a pittance compared to alternatives. Going one step up, you can find a 5-year GIC at 175 basis points, but again, it isn’t going to get you very far.

When markets appear to be stable, people reach for yield. A “reach for yield” market is exhibited when you see garbage rise, and a lot of sectors start incurring speculative fervor. We’re clearly in one of those market environments at present, a short temporal distance away from the March 23rd CoronaCrisis crash which lead everybody to the exits (yours truly was madly investigating opportunities) where quality was being thrown out the window. How times have changed – on very quick notice.

Institutions are in the same boat. They have to make their mandated returns otherwise pensioners don’t get paid and underperformance will cause capital to shift to those that bought and held Tesla at the beginning of the year.

I look at this Globe and Mail article about institutional managers buying Canadian apartments:

While many property deals are private transactions, Mr. Kenney cited some recent sales in mid-town Toronto that were completed at capitalization rates around 2 per cent, an astonishingly low level.

I ask myself what can justify 2%. For instance, CapReit (TSX: CAR.UN) in their last quarterly report stated their mortgage portfolio is an average of 1.93% at a term of 9.3 years.

While it isn’t clear whether the definition of cap rate in this instance included mortgage interest expenses (“cap rate” is not a standardized accounting term – you can make this number go up or down depending on how much leverage you employ), 2% is indeed a very low rate of return. Indeed, for it to make financial sense, you have to anticipate some degree of capital appreciation in the underlying property for the investment to make sense.

This low spread is not limited to real estate, it also includes the stock market.

(For the comparison above with CapREIT, I’ll tip the hat to Tyler (his Twitter) who has been discussing this concurrently and independently of the writing of this post, great minds think alike I guess!).

Let’s look at the S&P 500 top components. Apple, for instance, stock price $124, and the past year of 10-K earnings show $3.30/share, and relatively stable. So a bond-like earnings yield 2.7% for Apple stock. MSFT is $6 EPS and $214/share or about 2.8%. Facebook is about 2.5%, and so on. Of course in these cases you can make an argument that earning yields will grow over time and there is some franchise value. But it is shockingly close to these Toronto-area apartments that are selling for a current 2% (although given the choice of an investment in Apple or a Toronto apartment, I’d take Apple any day of the week).

Yields are very tiny now, and investors are going to chase them. High quality, such as Apple, will be rightfully expensive. But this yield chasing will make its way down the quality chain and companies that have no right to be chased down to 4% earnings yields will be done so because there is a huge liquidity avalanche out there that is looking for a home.

Realize when stocks trade, there is no cash or stock created or destroyed in the process; it is merely a transfer between buyer and seller. The amount of cash is the same, and this cash will circulate, being handed from account to account, while in the meantime the counter-transaction to that is the transfer of assets at higher and higher prices, until such a point that the amount of baked speculation on future yields will go to a low point.

If you believe those Toronto apartments will rise in price 10% a year for many years ahead, it would be completely rational to buy them even at single-digit negative cap rates, especially if you anticipate being ample future liquidity in case if you change your mind.

Likewise, for Apple, you could bake in a whole set of variables to justify purchasing it at a 200bps earnings yield, or 150bps, etc., citing a never-ending stream of inflation-shielded future cash flows. Indeed, that $124 stock price at 200bps would warrant an Apple stock price of $165, or a 33% gain from the current price!

I have no idea when this speculation house of cards will end, and can only conceive of a few scenarios of how it ends (one obvious “how it ends” would be the onset of inflation beyond that of asset prices – you’d see a 30-40% stock market crash). It is a very dangerous game of participants bidding asset prices higher and higher in the search for yield and appreciation. Apple today at 270bps sold to the next guy at 265bps, then to 260bps, etc., until the demand for that cash gets directed to some other supply that is not Apple equity.

Back in the dawn of the COVID-19 crisis when everybody thought we were going to die (April 5, 2020), I openly speculated the following:

This might sound a little crazy, but I can see the S&P 500 heading to 4000 before the end of the year.

Recall at this time when I wrote it, the S&P 500 was trading at around 2,500. Predicting a 4,000 index (a 60% rise) is crazy. I don’t think anybody on this planet did that except myself. We are living in a crazy world, where many are indeed going insane with COVID lockdowns and massive disruptions of a “normal life” that people are realizing is not coming back. And while the S&P 500 index will probably fall a hundred points short of 4000 before the new year, realize that going forward this is what it takes to be successful – not seeing reality as it is, but rather being able to adapt to what are inherently crazy circumstances in the minds of market participants.

Even if you see reality for what it is in the markets, it is not sufficient for your survival – you must understand the perceptions that surround the other participants.

Reminiscences of a Stock Operator

I’m currently reading Reminiscences of a Stock Operator. This book (the annotated version by Jon D. Markman) is so timely in relation to what is going on currently, it is unreal.

The modern day equivalents of bucket shops seem to be cryptocurrency exchanges.

And some notes on bull and bear markets and the value of sitting tight when things are in a bull market:

For all of my paranoid rantings, to exercise caution, etc., if I were to fall into a coma and wake up a couple years later, I feel reasonably confident that my portfolio would be fine.  I couldn’t say the same if I held XYZCoin or shares in Zoom or Tesla.

Gold is out, crypto (or almost anything else) is in – and FOMO

For the first time in ages, the Royal Canadian Mint ETR (TSX: MNT) is trading within a percentage point of its net asset value – prior to this it was trading at a significant premium.

This could be because the price of gold, at least as measured in US dollars, has declined from a high of about US$1,950 during the election to US$1,800 today and suddenly gold is no longer in vogue. It is difficult to prescribe what causes price decreases in gold, but given its perception of a “when everything goes to hell” metal, my guess is that the fallout of the presidential election is alleviating to those that went into gold.

Another solution espoused by monetary doomsday proponents is the purchase of cryptocurrencies.

Here is my current theory of how things will end up.

You’re going to continue hearing more and more about Bitcoin until the last dollar has been sucked up into this global Ponzi vacuum – it’s up about US$1,000/coin today. The price is going to continue to rise because of forced buying (ETFs) and rampant speculation (easy access through financial apps that can be loaded on anybody’s smartphone). You’re going to hear your friends, neighbours, etc., get into the action, and you will be aggravated to hear about fortunes made because they bought half a bitcoin and it went up ten-fold in a month, while you are just sitting on your boring shares of Fortis and Enbridge, clipping quarterly dividend coupons at a hundred times less magnitude.

The disparity in performance going to drive a lot of people insane. Literally insane. Seeing your friend pull up to your doorstep in a Lambo (“Look! I sold some bitcoin!”) while you’ve just made an extra value meal in dividends fuels a lot of psychological resentment. After finishing drag racing on the freeway in your friend’s Lambo, picking up your Big Mac and fries at the McDonalds drive-through with your dividend cheque, you both will then go home and buy some more bitcoins.

All I can suggest to keep your sanity is to go to the library (assuming your local branch hasn’t been shut down by the COVID scourge) and get some history reference books on what happened during the Dutch tulip bulb mania. This is the closest analogy I can think of to the current situation. One difference between the 17th century and today’s era is that in today’s era, things move much, much faster, including Lambos vs. horse carriages. This includes price movement and capital mobility. The Tulip Bulb mania took about 3 years to form, and the crescendo went over about four months of trading. With bitcoin, I would not be shocked that the initial collapse will be a price drop of over 50% in a 1 week period. It will be massively disruptive.

You will also hear at the same time after this price collapse a bunch of people saying this is the greatest chance to get in of all times.

Most people in finance have some knowledge of the Tulip Bulb Mania. However, many less people (including Wikipedia) have a historical knowledge of another great pyramid scheme which brought down the country of Albania in 1997. This made for a very fascinating study although there were few references to it in English. Another difference is that Albania wasn’t exactly a rich country at that time, so the absolute amount of capital sucked into this scheme was relatively limited by comparison, while Bitcoin has a nearly global audience.

History is repeating again, right before your very eyes! What a time to be living.

How do we begin to model this?

Unlike Tulip Bulbs, which trade in discrete quantities, Bitcoin is divisible in units of 100 millionths of a bitcoin, which means anybody will be able to get into the game – with Tulip Bulbs, the purchasing power of one bulb at its peak was massive, which limited the ability for people to get in (they had to put up margin collateral). With bitcoin, anybody with a cell phone and a bank account can get in.

There are about 18.6 million bitcoin outstanding at present, with a good chunk of this (at the onset of creation) apparently not used, and with people losing coins here and there. At US$19,000/coin, the market capitalization of the entire bitcoin set is US$350 billion. I think you can now make a good argument this could go a lot larger before the bottom falls out on this one. I initially thought the market cap of bitcoin would be roughly restricted to the largest cap companies trading on the public exchanges (currently, this would be Apple at around $2 trillion) but for a true mania, shouldn’t it go higher? There’s clearly room to head up to $100k/coin. The question is – how much cash will this suck up before demand stops?

Kind of makes my earlier predictions half a decade ago of a $10k ceiling to be pretty ridiculous, but then again, I never knew Bitcoin would be the vessel of the next tulip mania. Times really haven’t changed.

Diversification and risk

Textbooks in finance are written about the benefits of diversification and how to achieve your portfolio objectives. If you can find two assets that you estimate have the same expected return, in theory it makes sense to split your portfolio 50/50 among them to reduce the risk to achieve the expected value. Implicit behind this is that the returns achieved by these assets are not correlated. For instance, if your two assets are CNR and CP, if Canada goes bust, your diversification is not going to help. But if your two assets are CP and some boring and stable power generation utility out in India, chances are that the returns from the two assets are likely to be much less correlated. Computer algorithms can sort out all of these historical correlations and give you a pretty good idea of the mathematical risk, just from historical trading data.

Then we get into the business of asset allocation. Traditionally, equities and government bonds are inversely correlated to each other, and it has been a layer of portfolio protection when equities rise, you sell a little bit and buy (relative to before, lower priced) treasuries and vice versa.

However, it all goes haywire when traditional correlations do not manifest themselves.

One example is the usage of gold as a “world is going to hell” hedge and also a hedge against inflationary monetary policy decisions. In panicked market conditions, gold is just as susceptible as other asset classes for being liquidated.

Another example is the market for unsecured debt (e.g. TSX debentures or any other corporate bond that trades publicly in a reasonably liquid manner) – although many of these companies are sure-guarantees to pay out at maturity, the value of their debt trades down in market panic conditions.

Finally, another example is the usage of Bitcoin. Since there is limited historical data, there is a considerably higher element of human intuition that goes behind what the true risk profile of this asset is.

When traditional correlations break, it forces portfolio managers to either stay the course (assuming it will regress to some sort of ‘mean’), or to adjust the asset allocation to reflect the new reality with the correlations between various assets. In general, my gut feel is that markets are moving ‘faster’ than they were before, which will make institutional managers that much more challenged to adjust their models to reflect market reality.