Investing

Mancur Olson’s The Rise and Decline of Nations tells us that in stable times special interest groups tend to slowly create increasingly rigid agreements to cement their income streams. Major wars, and other cataclysms of that size, occasionally sweep away those rigidities, creating conditions under which faster economic growth is possible.

COVID has been much less cataclysmic than what Olson talks about. Yet I see hints that the recent pandemic has had effects that weakly resemble war. I see stronger evidence that the pandemic was a useful trigger for overcoming the effects status quo bias. I’m writing this post to help clarify my thoughts about how significant these effects will be, and how they’ll affect stock markets.

Is the stock market’s impressive performance partly due to expectations that the pandemic caused a lasting increase in profits?

I’ll guess that it explains one quarter of the stock market’s rise. A fair amount of that guess reflects my intuitions about how much can’t be explained by other factors. That approach is at least as error-prone as estimating individual pandemic effects. So please interpret this post as mostly groping around in the dark.

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Book review: Shut Out: How a Housing Shortage Caused the Great Recession and Crippled Our Economy, by Kevin Erdmann.

Why did the US have an unusually bad recession in 2008, followed by years of disappointing growth?

Many influential people attribute it to the 2004-2006 housing bubble, and the ensuing subprime mortgage crisis, with an implication that people bought too many houses. Erdmann says: no, the main problems were due to obstacles which prevented the building and buying of houses.

He mainly argues against two competing narratives that are popular among economists:

  • increased availability of credit fueled a buying binge among people who had trouble affording homes.
  • there was a general and unusual increase in the demand for homes.

Reframing the Housing Bubble

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It’s been a decade since I blogged about the benefits of avoiding news.

In that time I mostly followed the advice I gave. I kicked my addiction to The Daily Show in late 2016 after it switched from ridiculing Trump to portraying him as scary (probably part of a general trend for the show to be less funny). I got more free time, and only missed the news a little bit.

Then the pandemic hit.

I suddenly needed lots of new information. Corporate earnings releases were too slow.

Wikipedia, Our World in Data, Metaculus, and some newly created COVID-specific web sites partly filled that gap. But I still needed more, and I mostly didn’t manage to find anything that was faster or more informative than the news media storyteller industry.

That at least correlated with higher than normal stress. I suspect that paying attention to the storytellers partly caused the stress.

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Lots of people have been asking recently why the stock market appears unconnected with the economy.

There are several factors that contribute to that impression.

First, stock market indexes are imperfect measures of the whole stock market. Well-known indexes such as the S&P500 are higher than pre-pandemic, but the average stock is down something like 10% over the same time period. The difference is due to some well-known stocks such as Apple and Amazon, which have unusually large weights in the S&P500.

See this Colby Davis post for some relevant charts, and for some good arguments against buying large growth stocks today.

Stock markets react to the foreseeable future, whereas the daily news, and most politicians, prefer to focus attention on the recent past. People who focus on the recent past see a US that’s barely able to decide whether to fight COVID-19, whereas the market sees vaccines and/or good treatments enabling business to return to normal within a year.

Stock markets don’t try to reflect the costs associated with death, chronic fatigue, domestic violence, etc. Too many people want the market to be either a perfect indicator of how well we’re doing, or to dismiss it as worthless. Sorry, but imperfect indicators are all we have.

Plenty of influential people have been exaggerating the harm caused by the pandemic, in order to manipulate the average person into taking the pandemic seriously. As far as I can tell, this backfired, and contributed to the anti-mask backlash. It also contributed to stocks being underpriced in the spring, so parts of the stock market rebound have simply been reactions to the growing evidence that most large companies are recovering.

The vaccine news has been persistently good, except for the opposition from big pharma and their friends at the FDA to making vaccines available as soon as possible.

Another modest factor is that many companies dramatically reduced their capital expenditure plans starting around March and April. That will reduce production capacities for the next year or two, thus making shortages of goods a bit more common than usual. This should prop up profit margins. But I haven’t noticed much connection between the most relevant industries and rising stock prices.

Why is there such a large divergence between the S&P500 and the average stock?

Investors have developed a somewhat unusual degree of preference for well-known companies whose long-term growth prospects seem safe.

I guessed last year that this would be a rerun of the Nifty Fifty. I still see important similarities in investor attitudes, but I see enough divergences in patterns of stock prices that I’m guessing we’ll get something in between the broad, gradual peak of the Nifty Fifty and a standard bubble (i.e. with a well-defined peak followed by a clear reversal within months).

Remember that high volatility is somewhat correlated with being in a bubble. We’ve recently seen Zoom Video Communications rise 40% in one day, and Salesforce rise 26%, in response to good earnings reports. That’s a $50 billion one-day gain for Salesforce. It reminds me of the volatility in PetroChina in 2007 (PetroChina has declined 87% since then). There was also that $173 billion rise in Apple after it’s latest earnings report, but that was a mere 10.5% rise.

Some of the divergence is due to small retailers losing business to Amazon, and to small restaurant chains losing business to fast food chains.

The bubble is a bit broader than just tech stocks – Home Depot and Chipotle are well above their pre-pandemic levels, by much larger amounts than can be explained by any near-term changes in their profits.

Incumbent politicians have been trying to buy votes by shoveling money to influential companies and people. There’s been some speculation that that’s biased toward large companies. It seems likely that large companies are better able to take advantage of those deals, because they’re more likely to employ someone with expertise at dealing with the government than is, say, a barbershop.

But I don’t see how that explains more than 1% of the stock market divergence. Stocks like Apple and Tesla have risen much more than can be explained by any change in this year’s profits. Any sane explanation of those soaring stocks has to involve increased optimism about profits that they’ll be making 5 to 10 years from now.

Large companies have better access to banks. Large companies typically have someone who is an expert at dealing with banks, and they have the accounting competence to make it easy for banks to figure out how much they can safely lend to the company. In contrast, a family-owned business will be slower to figure out how to borrow money, and therefore is more likely to go out of business due to unusual problems such as a pandemic. That might explain a fair amount of the divergence between the S&P500 and what you hear by word of mouth, but it explains little of the divergence between the S&P500 and the publicly traded companies that are too small for the S&P500.

I’ve only done a little selling recently, and I’ve been mostly avoiding large companies for many years. I’m guessing that Thursday’s tech stock crash wasn’t the end of the bubble. Bubbles tend to continue expanding until the average investor gets tired of hearing pundits say that we’re in a bubble. That suggests the peak is at least a month away, and I could imagine it being more than a year away.

Stock markets have a long history of being abnormally risky in September and October. Out of 10 months in which the S&P500 ended at least 15% lower than when it started, 3 were in October. Out of 31 months in which it ended at least 10% lower, 12 were in September or October.

I used to guess that this was due to the onset of seasonal affective disorder. That explanation was a bit unsatisfying, because SAD seems likely to be predictable enough that the effects could be mostly smoothed out by smart investors.

After looking at the 1957 pandemic and its possible effect on the stock market, I wondered whether infectious diseases was a better explanation.

I did a crude analysis of the correlations between flu deaths and stock market changes. I didn’t manage to get as good a dataset as I’d hoped for, and ended up settling for the monthly US data for selected seasons (12 in the period 1941-1976) in table 1 of Trends in Recorded Influenza Mortality: United States, 1900–2004.

I looked at correlations between monthly increases in flu deaths per 100,000 people and the monthly change in the S&P500. I was able to find a large effect, but it disappeared when I left out the 1943-1944 season (which was by far the worst season in that time period, yet wasn’t labeled as a pandemic).

Either there’s no effect in that time period, I don’t have detailed enough data, or the effects precede deaths by enough that the death data aren’t helpful.

I was mostly thinking that diseases might have affected the market via effects on investors moods or liquidity preferences, so I wasn’t assuming there would be much discussion of the topic. The paper The Unprecedented Stock Market Reaction to COVID-19 investigated whether newspapers mentioned the topic, and concluded:

In the period before 24 February 2020 – spanning 120 years and more than 1,100 jumps – contemporary journalistic accounts attributed not a single daily stock market jump to infectious disease outbreaks or policy responses to such outbreaks. Perhaps surprisingly, even the Spanish Flu fails to register in next-day journalistic explanations for large daily stock market moves.

So, after a fair amount of research, I still don’t have good evidence about what’s causing the September / October volatility.

P.S. For some strange reason, January is an unusually safe month, with no declines of more than 9% in the S&P 500.

P.P.S. VIX futures are saying that the S&P500’s volatility around late October will be 3.6 points higher the average of August and December volatilities. That compares to an average of 0.86 points higher (and a maximum of 2.1) over the prior 11 years in which VIX futures have been available (all of these numbers come from prices near July 20 of the relevant year).

So the markets expect something unusual this October. Something more surprising than they expected during the prior two presidential election years. Does anyone know whether this risk is due to weather-related pandemic risk or due to political risk?

New infections have been declining at an almost adequate pace (10% per week?) in most parts of the US, and probably the rest of the developed world.

The overall reported new cases look more discouraging, for two reasons.

One reason is the increase in testing. I estimate that two months ago, a bit less than 10% of new infections were being confirmed by tests, and I estimate that now it’s above 20%, maybe getting close to 25%. That means that if the new infection rate were unchanged, we’d be seeing a roughly 10% per week increase in reported cases.

Nearly all parts of the country have done a good deal better than that.

I estimate the change in new infections since the early April peak by multiplying the early April confirmed daily cases by 10 or 12, and the June ones by 4 or 5, and I get a current rate that’s about 1/4 to 1/3 of the peak.

The bad news is that there are some heavily populated areas for which the trend doesn’t look very good over the past few weeks. When the rate of new infections remains constant in some areas, but declines at exponential rates in others, the exponential declines stop affecting the total numbers before too long. E.g. much of California has suppressed the pandemic, but a few cities, such as Los Angeles and Oakland, are enough to keep the state’s total count of new infections steady.

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Long-term investors should stay away from most bonds for the foreseeable future.

Last summer, Colby Davis explained why portfolio managers might want to buy bonds that yield 2%. At the time, I was suspicious, but it felt premature to argue against it.

Since then, yields on 30-year government bonds have dropped to 1.44%. That means bond prices went up. His advice worked well as a hedge against pandemics.

Inflation expectations have dropped along with those yields.

30-year TIPS have an expected yield of -0.045%.

That implies expected CPI inflation of less than 1.5% over the next 30 years, and that, adjusted for inflation as measured by the CPI, investors who buy 30-year government bonds now should expect to lose wealth if they hold to maturity.

So why are investors buying bonds at these prices?

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In this post, I make some conjectures about U.S. economic growth over the next year or two.

Many people expect a depression, due to the current high unemployment numbers. But depressions aren’t caused by unemployment – that’s a symptom, with little predictive power.

The main cause of poor economic growth has been an inability to alter wages so that the supply of and demand for labor are in balance. That typically means deflation, or a large, unexpected decline in the inflation rate, combined with sticky wages.

So I’ll mostly focus on guessing whether we’ll have inflation or deflation.

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The stock market crash of the past two weeks looks like an over-reaction to COVID-19.

Is COVID-19 really the reason for the crash? I can’t find any other news that would explain the timing and which stocks were hit hardest.

Here’s a sample of some of the harder hit stocks, all travel-related (Friday’s close compared to the highest close in February):

  • -37% Hertz (HTZ)
  • -36% Avis (CAR)
  • -29% World Fuel Services Corp (INT)
  • -24% Carnival (cruise line) (CCL)
  • -22% Delta Air Lines (DAL)
  • (compare to the S&P 500: -12.4%)

It is, of course, possible that the market was in a mild bubble in early February, and the virus merely triggered a return to sanity. There were enough high-priced stocks that I’ll guess that’s explains a little of what happened. Hertz and Avis are maybe high-risk stocks due to the risks associated with the upcoming transition to robocars. But the others that I listed did not at all fit my stereotype of overpriced stocks.

And the stocks that I had been thinking were overpriced, in industries that don’t look to be especially hurt by the virus, declined roughly in line with the market.

Outside of travel-related stocks, it mostly looks like a general shift in preferences to more cash, and away from stock. I.e. a general increase in risk aversion.

The gold market is confused as to which direction a pandemic should move it. I agree. I’m confused as to how gold should react.

What scenario could explain the decline? Maybe a two month shutdown of 90+% of U.S. air travel? A multi-year reduction in travel of 10%? It would take something like that for the market reaction to make much sense. Yet I’d bet at roughly 10:1 odds against any one of those scenarios happening.

Metaculus is currently predicting 195k COVID-19 deaths this year.

Metaculus forecast trends ought to look a good deal like random walks, yet the charts I see there look more like exponential growth.

Metaculus is likely to be a more objective source of information than the news media storyteller industry or social media. But it’s likely more susceptible to selection effects and hype than are markets that have lots of money at stake. (Metaculus has token prizes, structured in a way that may encourage more extreme bets than a regular market would).

None of this implies much about where other reactions to the virus are sensible. There’s a much different asymmetry between getting sick versus being paranoid than there is between losing money due to a pandemic versus losing money due to selling on a false alarm.

I’ve got about a month’s supply of food, but that’s my normal preparation for a variety of disasters. I have no special insights about whether the current risks justify staying home.

P.S. Chinese stocks are supporting the view that the situation in China has improved over the past month.

There are a number of investment ideas that pop up about once per generation, work well for years, and then investors get reminded of why they’re not so good, and they get ignored for long enough that the average investor doesn’t remember that the idea has been tried.

The idea I’m remembering this month is known by the phrase Nifty Fifty, meaning that there were about 50 stocks that were considered safe investments, whose reliable growth enabled investors to ignore standard valuation measures such as price/earnings ratios, dividend yields, and price to book value.

The spirit behind the Nifty Fifty was characterized by this line from a cryonaut in Woody Allen’s Sleeper (1973): “I bought Polaroid at seven, it’s probably up millions by now!”.

There was nothing particularly wrong with the belief that those were good companies. The main mistakes were to believe that their earnings would grow forever, and/or that growing earnings would imply growing stock prices, no matter how high the current stock price is.

I’ve seen a number of stocks recently that seem to fit this pattern, with Amazon and Salesforce mostly clearly fitting the stereotype. I also ran into one person a few months ago who believed that Amazon was a good investment because it’s a reliable source of 15+% growth. I also visited Salesforce Park last month, and the wealth that it radiated weakly suggests the kind of overconfidence that’s associated with an overpriced stock market.

I took a stab at quantifying my intuitions, and came up with a list of 50 companies (shown below) based on data from SI Pro as of 2019-09-20, filtered by these criteria:

  • pe_ey1 > 30 (price more that 30 times next year’s forecast earnings)
  • mktcap > 5000 (market capitalization more than $5 billion)
  • prp_2yh > 75 (price more than 75% of its 2 year high)
  • rsales_g5f > 50 (5 year sales growth above the median stock in the database)
  • sales_y1 < 0.33333*mktcap (market capitalization more than 3 times last year’s sales)
  • yield < 3 (dividend yield less than 3%)
  • pbvps > 5 (price more than 5 times book value)
  • epsdc_y2 > 0 (it earned money the year before last)

I did a half-assed search over the past 20 years, and it looks like there were more companies meeting these criteria in the dot com bubble (my data for that period isn’t fully comparable), but during 2005-2015 there were generally less than a dozen companies meeting these criteria.

The companies on this list aren’t as widely known as I’d expected, which weakens the stereotype a bit, but otherwise they fit the Nifty Fifty pattern of the market seeming confident that their earnings will grow something like 20% per year for the next decade.

There were some other companies that arguably belonged on the list, but which the filter excluded mainly due to their forward price/earnings ratio being less than 30: BABA (Alibaba Group Holding Ltd), FB (Facebook), and GOOGL (Alphabet). Maybe I should have used a threshold less than 30, or maybe I should take their price/earnings ratio as evidence that the market is evaluating them sensibly.

This looks like a stock market bubble, but a significantly less dramatic one than the dot com bubble. The market is doing a decent job of distinguishing good companies from bad ones (much more so than in the dot com era), and is merely getting a bit overconfident about how long the good ones will be able to maintain their relative quality.

How much longer will these stocks rise? I’m guessing until the next major bear market. No, I’m sorry, I don’t have any prediction for when that bear market will occur or what will trigger it. It will likely be triggered by something that’s not specific to the new nifty fifty.

I’m currently short EQIX. I expect to short more of these stocks someday, but probably not this year.

ticker company pe_ey1 mktcap sales_y1 yield pbvps
AMT American Tower Corp 52 100520 7440.1 1.7 18.21
AMZN Amazon.com, Inc. 54 901016 232887 0 16.67
ANSS ANSYS, Inc. 31.8 18422.3 1293.6 0 6.46
AZPN Aspen Technology, Inc. 30.5 8820.8 598.3 0 22.2
BFAM Bright Horizons Family Solutio 37.2 9181.8 1903.2 0 10.21
CMG Chipotle Mexican Grill, Inc. 48 23067.9 4865 0 15.04
CRM salesforce.com, inc. 50.1 134707 13282 0 7.02
CSGP CoStar Group Inc 49.3 21878.4 1191.8 0 6.74
DASTY Dassault Systemes SE (ADR) 32.9 37683.3 3839 1 7.05
DXCM DexCom, Inc. 110.3 14132.9 1031.6 0 20.44
EQIX Equinix Inc 70.2 48264.7 5071.7 1.7 5.46
ETSY Etsy Inc 61.7 7115.6 603.7 0 16.42
EW Edwards Lifesciences Corp 36.7 44736.3 3722.8 0 13.06
FICO Fair Isaac Corporation 36.5 9275.5 1032.5 0 33.71
FIVE Five Below Inc 33.6 7152.1 1559.6 0 10.86
FTNT Fortinet Inc 31.6 13409.2 1801.2 0 11.93
GDDY Godaddy Inc 67.2 11976.7 2660.1 0 12.41
GWRE Guidewire Software Inc 70.3 8835.9 652.8 0 5.84
HEI Heico Corp 49.3 15277.3 1777.7 0.1 10.58
HUBS HubSpot Inc 94.6 6877.4 513 0 10.93
IAC IAC/InterActiveCorp 38.3 19642.5 4262.9 0 6.51
IDXX IDEXX Laboratories, Inc. 49.3 23570.6 2213.2 0 138.03
ILMN Illumina, Inc. 44.3 44864.4 3333 0 10.5
INTU Intuit Inc. 31.6 70225.1 6784 0.8 18.67
INXN InterXion Holding NV 106.8 5995.1 620.2 0 7.95
ISRG Intuitive Surgical, Inc. 38.8 61020.9 3724.2 0 8.44
LULU Lululemon Athletica inc. 33.7 25222.7 3288.3 0 16.36
MA Mastercard Inc 30.1 276768 14950 0.5 55.23
MASI Masimo Corporation 41.8 8078.9 858.3 0 7.8
MDSO Medidata Solutions Inc 43.4 5734.1 635.7 0 8.35
MELI Mercadolibre Inc 285.4 27306.2 1439.7 0 12.59
MKTX MarketAxess Holdings Inc. 56.7 12941.1 435.6 0.6 18.93
MPWR Monolithic Power Systems, Inc. 31.5 6761.2 582.4 1 9.44
MTCH Match Group Inc 38.4 22264.7 1729.9 0 105.51
OLED Universal Display Corporation 45.5 8622.8 247.4 0.2 11.36
PAYC Paycom Software Inc 51.3 12812.8 566.3 0 28.6
PCTY Paylocity Holding Corp 47.6 5150.5 467.6 0 17.01
PEGA Pegasystems Inc. 167.2 5686.4 891.6 0.2 10.14
PEN Penumbra Inc 134 5142.8 444.9 0 11.3
RMD ResMed Inc. 30.6 19181.5 2606.6 1.2 9.33
RNG RingCentral Inc 139.4 11062.4 673.6 0 30.93
ROL Rollins, Inc. 43.6 11383.4 1821.6 1.2 15.04
RP RealPage Inc 31.3 6084.5 869.5 0 5.3
TAL TAL Education Group (ADR) 39.4 21326.2 2563 0 8.45
TECH BIO-TECHNE Corp 34.6 7483.8 714 0.6 6.52
TREX Trex Company Inc 30.2 5074.2 684.3 0 13.05
TYL Tyler Technologies, Inc. 43.5 10004.5 935.3 0 6.98
VEEV Veeva Systems Inc 62 21366.2 862.2 0 15.27
VRSK Verisk Analytics, Inc. 32.3 25948.4 2395.1 0.6 11.73
ZAYO Zayo Group Holdings Inc 42.5 7997.8 2578 0 5.95