A new study has provided evidence that a healthy lifestyle can reverse aging, as measured by epigenetic age: Reversal of Epigenetic Age with Diet and Lifestyle in a Pilot Randomized Clinical Trial. This is the second study to show that epigenetic age can be reversed in humans (here’s a reminder to read the first).

They used the Horvath DNAmAge clock.

After a mere 8 weeks of a healthy lifestyle, the subjects’ DNAmAge was 3.23 years younger than the controls (and 1.96 years younger than the pre-trial DNAmAge of the treatment group).

The lifestyle interventions weren’t labeled as paleo, but they closely resemble the lifestyles that are recommended by Chris Kresser, Steven R. Gundry, and Dale Bredesen. The diet comes about as close as the diet of a typical paleo enthusiast to avoiding foods that have been available for less than 10,000 years. The recommended foods that I consider the least paleo are “coconut, olive, flaxseed and pumpkin seed oil”. The diet is more plant-based than the stereotypical paleo diet, but it’s well within the normal range of hunter-gatherer diets.

The study has a bunch of the usual limitations, such as a small sample size (18 people in the treatment group). There are also reasons for mild concerns about conflicts of interest, as some of the researchers work as functional medicine physicians, so their careers are mildly dependent on the popularity of the lifestyle approach being studied. As far as I can tell, that is likely to cause a level of bias that is rather ordinary for nutrition-related research. Oh, and the instructions are listed as “Patent pending”, but it’s unclear why they would meet the novelty requirements for a patent.

My main doubt comes from the difficulty of figuring out whether DNAmAge measures causes of age-related health problems, or whether it’s just measuring symptoms. I’m slightly more than 50% confident that epigenetic changes have some causal influence on aging.

This kind of trial raises questions about how well patients follow the instructions – most would find it difficult to “Avoid added sugar/candy, dairy, grains, legumes/beans”. The paper describes how they checked on patient compliance, but I didn’t see any data indicating what they found about compliance. So there’s some risk that they were especially lucky about getting patients to follow their instructions, and maybe future studies of this nature will show much weaker results due to poor compliance.

Lastly, it’s a bit odd that the control group appeared to age 1.27 years in 8 weeks. Maybe they were depressed about not getting any treatment? (This isn’t the kind of study where blinding is feasible). More likely it was just noise, but that’s a reminder that the small sample size provides lots of opportunity for luck to dominate the results. Even if we assume perfect measurement, there’s plenty of room for variation in lifestyles. Uncontrolled lifestyle changes, such as someone getting fired, could mess with the results enough to matter.

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.

I’ve been brainstorming about what might happen with this year’s election. Here’s one of the more interesting (but not likely) scenarios that I’ve imagined:

Most parts of the US are experiencing their second or third wave of the pandemic. Two of the more heavily funded vaccine trials have just been declared to be failures. No US or European company expects to have a vaccine ready for FDA approval before December. Prediction markets say Trump’s chances of re-election have dropped to 20%.

China announces on October 27 that Sinopharm Group has a COVID-19 vaccine that meets China’s safety and effectiveness standards, and can deliver about 1 million doses by November 2.

China offers to allocate half of this initial batch of vaccines to the US, on the grounds that the US is a relatively needy country, and Donald Trump is currently a close friend of China.

Why, I hear you wonder, would China treat Trump as a friend?

China is strong enough that the government can afford to tolerate Trump’s annoying trade wars, and they maybe even see some benefit from reducing China’s somewhat excessive dependence on the US. It’s important to keep in mind that democracy is one of the larger threats to the Beijing regime (h/t scholars-stage). 2020 has proven to be a good year to mount a campaign to demonstrate that socialism with Chinese characteristics is superior to US-style democracy. I’ll leave as an exercise for my readers to figure out how many ways the idea of democracy could be discredited by a Trump re-election.

Why would a Chinese company be faster than US/European companies at producing a vaccine? My initial guess was differences in regulatory red tape would favor China, but my attempt to find evidence for such a pattern turned up nothing. My current guess is that differences between countries in who volunteers for a vaccine trial will have important effects on how quickly the control groups get infected. Trials in some countries may attract only people who are sufficiently risk-averse that the control groups are slower than expected at getting infected. Please don’t assume that I have any useful expertise here; I’m mostly just guessing.

I also wondered whether willingness to do human challenge trials would determine who verifies their vaccine first. I have vague intuitions that China is more likely than other countries to try that, but I haven’t found evidence to confirm those intuitions.

How would voters react to this scenario? My best guess is that the election would be surprisingly close, but Trump would still lose.

The stock market would rise due to the vaccine benefits. There would be no good way to infer the market’s opinion about the election until the results are announced. I’m still confused as to how this scenario should affect my investment strategies.

P.S. – China and Sinopharm aren’t willing to predict when they’ll able to submit the forms needed for FDA approval, and ask that the US consider the approval of China’s NMPA to be good enough evidence of the vaccine’s safety and effectiveness. How does the FDA react?

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?

Book review: Lifespan: Why We Age – and Why We Don’t Have To, by David A. Sinclair.

A decade ago, the belief that aging could be cured was just barely starting to get attention from mainstream science, and the main arguments for a cure came from people with somewhat marginal formal credentials.

Now we have a book by an author who’s a co-chief editor of the scientific journal Aging. He’s the cofounder of 14 biotech companies (i.e. probably more than he’s had enough time to work for full time, so I’m guessing some companies are listing him as a cofounder more for prestige than for full-time work). He’s even respected enough by some supplement companies that they use his name, even after he sends them cease and desist letters.

I’m glad that Sinclair published a book that says aging can be cured, since there’s still a shortage of eminent scientists who are willing to take that position.

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Book review: Black Death at the Golden Gate: The Race to Save America from the Bubonic Plague, by David K. Randall.

Imagine a story about an epidemic that reached San Francisco, after devastating parts of China. A few cases are detected, there’s uncertainty about how long it’s been spreading undetected, and a small number of worried public health officials try to mobilize the city to stop an imminent explosion of disease. Nobody knows how fast it’s spreading, and experts only have weak guesses about the mechanism of transmission. News media and politicians react by trying to suppress those nasty rumors which threaten the city’s economy.

Sounds too familiar?

The story is about a bubonic plague outbreak that started in 1900. It happens shortly after the dawn of the Great Sanitary Awakening, when the germ theory of disease is fairly controversial. A few experts in the new-fangled field of bacteriology have advanced the radical new claim that rats have some sort of connection to the spread of the plague, and one has proposed that the connection involves fleas transmitting the infection through bites. But the evidence isn’t yet strong enough to widely displace the standard hypothesis that the disease is caused by filth.

There was a vaccine for the bubonic plague, which maybe helped a bit. It was only 50% effective, the benefits lasted about 6 months, and the side effects sound like cruel and unusual punishment. It was controversial and often resisted, much like the compulsory smallpox vaccinations of the time.

Yet the plague didn’t seem to know that it was supposed to grow at exponential rates. That left an eerie sense of mystery about how the plague could linger for years, with people continuing to disagree about whether it existed.

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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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