All posts tagged bubbles

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.

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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Robin Hanson has been suggesting recently that we’ve been experiencing an AI boom that’s not too different from prior booms.

At the recent Foresight Vision Weekend, he predicted [not exactly – see the comments] a 20% decline in the number of Deepmind employees over the next year (Foresight asked all speakers to make a 1-year prediction).

I want to partly agree and partly disagree.

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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

Most Universal Basic Income (UBI) proposals look a bit implausible, because they want to solve poverty overnight, and rely on questionable hopes for how much taxpayers can be persuaded to support[1].

They also fall short of inspiring my idealistic motives, because they want to solve poverty only within the countries that implement the UBI (i.e. they should be called national basic income proposals). That means even those of us living in relatively successful countries would be gambling on the continued success of the country they happen to live in. I imagine some large upheavals in the next century or so that will create a good deal of uncertainty as to which countries prosper.

Political movements to create national basic income run the risk of being hijacked by political forces that are more short-sighted and less altruistic.

Whereas I’m more interested in preparing for the more distant risks of a large-scale technological unemployment that might accompany a large increase in economic growth.

UBI without taxation?

Manna is a somewhat better attempt. It’s a cryptocurrency with a one account per human rule, and regular distributions of additional (newly created) currency to each account.

It provides incentives to sign up (speaking of which, I get rewards if you sign up via this link). It’s less clear what incentive people have to hold onto their manna[2].

It’s designed so that, given optimistic assumptions, the price of manna will be stable, or maybe increase somewhat. Note that those optimistic assumptions include a significant amount of altruism on the part of many people.

Cryptocurrencies gained popularity in part because they offered a means of trust that was independent of their creator’s trustworthiness.

Manna doesn’t attempt to fully replicate that feature, because they’re not about to fully automate the one-human-one-account rule. They’ve outsourced a good deal of the verification to cell phone companies, but the system will still be vulnerable to fraud unless a good deal of human labor goes into limiting people to one account each.

The obvious outcome is that people stop buying manna, so it becomes worth too little for people to bother signing up.

I suspect most buying so far has been from people who think any cryptocurrency will go up. That’s typical of a bubble.

That may have helped to jumpstart the system, but I’m concerned that it may distract the founders from looking for a long-term solution.

Why use a cryptocurrency?

Some of what’s happening is that crypto enthusiasts expect crypto to solve all problems, and apply crypto to everything without looking for evidence that crypto is helpful to the problem at hand. The cryptocurrency bubble misled some people into thinking that cryptocurrencies created free lunches[3] (manna comes from heaven, right?), and a UBI is a good use for a free lunch.

I recommend instead that you think of manna as primarily a charity, which happens to get some advantage from using a cryptocurrency.

Cryptocurrencies provide fairly cheap ways of transmitting value.

The open source nature of the mechanism makes it relatively easy to verify most aspects of the system.

These may not sound like terribly strong reasons, but it looks to me like much of the difficulty in getting widespread adoption of valuable new charities is that donors won’t devote much effort to evaluating charities. So only the most easily verified charities succeed on their merits, and the rest succeed or fail mainly on their marketing ability.


It seems almost possible that the price of manna could be stable or rise reliably enough to act as a good store of value.

But it won’t happen via the thoughtless greed that drove last year’s cryptocurrency buying frenzy. It requires something along the lines of altruism and/or signaling.

It seems to require the “central bank” to use charitable donations to buy manna when the price of manna declines.

It also requires something unusual about the average person’s attitude toward manna. Would it be enough for people and businesses to accept manna as payment, for reasons that involve status signaling? That doesn’t seem quite enough.

It’s also important to persuade some people to hold the manna for a significant time.


There’s little chance that can be accomplished by making manna look as safe as dollars or yuan. The only possibility that I can imagine working is if holdings of manna provide a good signal of wealth and wealth-related status. Manna seems to be positioned so that it could become a substitute for a fancy car or house as a signal of wealth. With that level of acceptance, it might provide a substitute for bank accounts as a store of value.

Signaling motives might also lead some upper-class people/businesses to use it as medium of exchange.

To work well, manna would probably need to be recognized as a charity, with a reputation that is almost as widely respected as the Red Cross. I.e. it would need to be a fairly standard form of altruism.

The main UBI movement wants to imagine they can solve poverty with one legislative act. Manna uses a more incremental approach, which provides less hope of solving poverty this decade, but maybe a bit more hope of mitigating larger problems from technological unemployment several decades from now.


Manna seems to be run by the first group of people who decided the idea was worth doing. Typically with a new technology, the people who will manage it most responsibly wait a few years before getting involved, so my priors are that I should hesitate before deciding this particular group is good enough.

Manna currently isn’t fair to people who can’t afford a cell phone, but if other aspects of manna succeed, it’s likely that cell phone companies will find a way to get cell phones to essentially everyone, since the manna will pay for the phones. Also, alternatives to cell phones will probably be implemented for manna access.

The high-level rhetoric says any human being is eligible for manna, but a closer look shows that anyone under 18 is treated as only partly qualified – manna accumulates in their name, and they get access to the manna when they come of age. The arbitrariness of this threshold is unsettling. We’ll get situations where people become parents, yet don’t have access to manna. Or maybe that’s not much of a problem because someone else will enable children to borrow, using their manna as collateral?

The problems will become harder if someone needs to figure out what qualifies a human being in an Age of Em, where uploaded minds (human, and maybe bonobo) can be quickly duplicated.

I’m not too clear on how the governing board will be chosen – they say something about voting, which sort of suggests a global democracy. That runs some risk of short-sighted people voting themselves more money now at the cost of a less stable system later. But the alternative governing mechanisms aren’t obviously great either.

I’d have more confidence if manna were focused exclusively on a UBI. But they want to also enable targeted donations, by providing verified age, gender, location, and occupation data, and “verified needy” status indications generated by other charities. Maybe a one or two of those would work out well, but I see some important tension between them and the “NO DISCRIMINATION” slogan on the home page.

The people in charge also want to solve “instability … resulting from too much money being held in too few hands and used for reckless financial speculation” without convincing me they understand what causes instability.

I’d be concerned about macroeconomic risks in the unlikely event that manna’s use became widespread enough that wages were denominated in it. Manna’s creators express Keynesian concerns about aggregate demand, suggesting that the best we could hope for from a manna monetary policy is that it would repeat the Fed’s occasional large mistakes. I’d prefer to aim for something better than that.

Current central banks have enough problems with promoting monetary stability. If they’re replaced by an organization which has a goal that’s more distinct from monetary stability, I expect monetary stability to suffer. I don’t consider it likely that manna will replace existing currencies enough for that to be a big concern, but I find this scenario hard to analyze.

Like most charities, it depends more on support from the wealthy than from the average person. Yet the rhetoric behind Manna seems designed to alienate the wealthy.

Is current People’s Currency Foundation sufficiently trustworthy? Or should someone create a better version?

I don’t know, and I don’t expect to do enough research to figure it out. Maybe OpenPhil can investigate enough?

Is this Effective Altruism?

The near-term benefits of Manna or something similar appear unimpressive compared to GiveDirectly, which targets beneficiaries in a more sophisticated (but less transparent?) way.

But Manna’s simpler criteria make it a bit more scaleable, and make it somewhat easier to gain widespread trust.

The main costs that I foresee involve the attention that is needed to shift people’s from charities such as the Red Cross or their alma mater as the default charity, toward manna. Plus, of course, whatever is lost from the charities who get fewer donations. There’s no shortage of charities that produce less value than a well-run UBI would, but the social pressure that I’m imagining is too blunt an instrument to carefully target the least valuable charities as the things that manna should replace.


I don’t recommend significant purchases of manna or donations to the People’s Currency Foundation now. Current efforts in this area should focus more on evaluating these ideas further, figuring out whether a good enough implementation exists, and if it should be scaled up, then we should focus more on generating widespread agreement that this is a good charity, and not focus much on near-term funding.

I give Manna a 0.5% chance of success, and I see an additional 1% chance that something similar will succeed. By success, I mean reliably providing enough income within 30 years so that at least 10 million of the world’s poorest people can use it to buy 2000 calories per day of food. That probability seems a bit higher than the chance that political action will similarly help the world’s poorest.


[1] – e.g. pointing to tax rates that were tolerated for a while after a world war, without noticing the hints that war played an important role in getting that toleration, and without noting how tax rates affect tax avoidance. See Piketty’s Capital in the Twenty-First Century, figures 13.1 and 14.1, for evidence that tax rates which are higher than current rates haven’t generated more revenues.

[2]Wikipedia says of the original manna: ‘Stored manna “bred worms and stank”‘.

[3] – or maybe the best cryptocurrencies do create free lunches, but people see more free lunches than are actually created. The majority of cryptocurrencies have been just transfers of money from suckers to savvy traders.

Scott Sumner asks whether those of us[1] who talked about a housing bubble are predicting another one now.

Sumner asks “Is it possible that the housing boom was not a bubble?”.

It’s certainly possible to define the word bubble so that it wasn’t. But I take the standard meaning of bubble in this context to mean something like a prediction that prices will be lower a few years after the time of the prediction.

Of course, most such claims aren’t worth the electrons they’re written on, for any market that’s moderately efficient. And we shouldn’t expect the news media to select for competent predictions.

Sumner’s use of the word “bubble” isn’t of much use to me as an investor. If prices look like a bubble for a decade after their peak, that’s a good reason to have sold at the peak, regardless of what happens a decade later.

If I understand Sumner’s definition correctly, he’d say that the 1929 stock market peak looked for 25 years like it might have been a bubble, then in the mid 1950s he would decide that it had been shown not to be a bubble. That seems a bit strange.

Even if I intended to hold an investment for decades, I’d care a fair amount about the option value of selling sooner.


The U.S. is not currently experiencing a housing bubble. I can imagine a small housing bubble developing in a year or two, but I’m reasonably confident that housing prices will be higher 18 months from now than they are today.

Several signs from 2005/2006 that I haven’t seen recently:

I mostly used to attribute the great recession to the foolish leverage of the banking system and homebuyers, who underestimated the risks of a significant decline in housing prices.

I’ve somewhat changed my mind after reading Sumner’s writings, and I now think the Fed had the power to prevent most of the decline in gdp, unless it was constrained by some unannounced limit on the size of its balance sheet. But I still think it’s worth asking why we needed unusual Fed actions. The fluctuations in leverage caused unusual changes in demand for money, and the Fed would have needed to cause unusual changes in the money supply to handle that well. So I think the housing bubble provides a good explanation for the timing of the recession, although that explanation is incomplete without some reference to the limits to either the Fed’s power or the Fed’s competence.

[1] – he’s mainly talking about pundits who blamed the great recession on the housing bubble. I don’t think I ever claimed there was a direct connection between them, but I did imply an indirect connection via banking system problems.

Book review: Warnings: Finding Cassandras to Stop Catastrophes, by Richard A. Clarke and R.P. Eddy.

This book is moderately addictive softcore version of outrage porn. Only small portions of the book attempt to describe how to recognize valuable warnings and ignore the rest. Large parts of the book seem written mainly to tell us which of the people portrayed in the book we should be outraged at, and which we should praise.

Normally I wouldn’t get around to finishing and reviewing a book containing this little information value, but this one was entertaining enough that I couldn’t stop.

The authors show above-average competence at selecting which warnings to investigate, but don’t convince me that they articulated how they accomplished that.

I’ll start with warnings on which I have the most expertise. I’ll focus a majority of my review on their advice for deciding which warnings matter, even though that may give the false impression that much of the book is about such advice.
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I’ve donated/sold more than 80% of my cryptocurrency holdings (Ripple and Bitcoin) over the past two weeks, after holding them without trading for around 4 years.

When I last blogged about Bitcoin, I said I would buy Bitcoin soon. That plan failed because I didn’t manage to convince the appropriate company that I’d documented my identity, so I didn’t find a way to transfer money from a bank to an account from which I could buy Bitcoin. (Difficulties like that were one reason why cryptocurrencies used to be priced too low). I procrastinated for two years, then found a convenient opportunity when MIRI needed to unload some Ripple.

My guess is that the leading cryptocurrencies will be somewhat higher a decade or two from now, but the prospects over the next year or two seem fairly poor compared to the risks.

Much of my expected value for the cryptocurrencies used to come from a 2+% chance of a hundred-fold rise. But a hundred-fold rise from current levels seems a bit less than 1% likely.

I compare cryptocurrency trends mainly to the gold bubble of 1980, since gold is primarily a store of value that pays no income, and is occasionally used as a currency.

I made some money once before by predicting that an unusual market pattern would repeat, with the same seasonal timing. So I’ve been guessing that cryptocurrencies would peak in mid-January. Yes, that’s pretty weak evidence, but weak evidence is all I expect to get.

I’ve also tried to extract some evidence from price trends. That usually provides only a tiny benefit in normal markets, but I suspect I get some value in high-volume inefficient markets (mainly ones where it’s hard to short) by detecting how eager traders are to buy and sell.

I watched the markets nervously in December, thinking that a significant bubble was developing, but seeing signs that any peak was still at least weeks in the future. Then I got nervous enough on January 2 to donate some Ripple to CFAR, even though I still saw signs that the market hadn’t peaked.

By January 5, I stopped seeing signs that the trend was still up, but I waited several days before reacting, hoping for rebounds that ended up being weaker than I expected. I ended up selling at a lower average price than CFAR got for what I donated to them, because dissatisfaction with the lower-than-recent price made me hesitant to sell.

An important lesson to draw from this is to always try to sell financial assets before the peak. Endowment effect is hard to avoid.

P.S. – It’s unclear whether cryptocurrencies are important enough to influence other stores of value. My best guess is that gold would be 5 to 10% higher today if it weren’t for cryptocurrencies. And the recent rise in cryptocurrencies coincides with a rise in expected inflation, but that’s more likely to be a coincidence, than due to people abandoning dollars because they see cryptocurrencies as a better store of value.

Book review: The Midas Paradox: Financial Markets, Government Policy Shocks, and the Great Depression, by Scott B Sumner.

This is mostly a history of the two depressions that hit the U.S. in the 1930s: one international depression lasting from late 1929 to early 1933, due almost entirely to problems with an unstable gold exchange standard; quickly followed by a more U.S.-centered depression that was mainly caused by bad labor market policies.

It also contains some valuable history of macroeconomic thought, doing a fairly good job of explaining the popularity of theories that are designed for special cases (such as monetarism and Keynes’ “general” theory).

I was surprised at how much Sumner makes the other books on this subject that I’ve read seem inadequate.
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[See my previous post for context.]

I started out to research and write a post on why I disagreed with Scott Sumner about NGDP targeting, and discovered an important point of agreement: targeting nominal wages forecasts would probably be better than targeting either NGDP or CPI forecasts.

One drawback to targeting something other than CPI forecasts is that we’ve got good market forecasts of the CPI. It’s certainly possible to create markets to forecast other quantities that the Fed might target, but we don’t have a good way of predicting how much time and money those will require.

Problems with NGDP targets

The main long-term drawback to targeting NGDP (or other measures that incorporate the quantity of economic activity) rather than an inflation-like measure is that it’s quite plausible to have large changes in the trend of increasing economic activity.

We could have a large increase in our growth rate due to a technology change such as uploaded minds (ems). NGDP targeting would create unpleasant deflation in that scenario until the Fed figured out how to adjust to new NGDP targets.

I can also imagine a technology-induced slowdown in economic growth, for example: a switch to open-source hardware for things like food and clothing (3-d printers using open-source designs) could replace lots of transactions with free equivalents. That would mean a decline in NGDP without a decline in living standards. NGDP targeting would respond by creating high inflation. (This scenario seems less likely and less dangerous than the prior scenario).

Basil Halperin has some historical examples where NGDP targeting would have produced similar problems.

Problems with inflation forecasts?

Critics of inflation targeting point to problems associated with oil shocks or with strange ways of calculating housing costs. Those cause many inflation measures to temporarily diverge from what I want the Fed to focus on, which is the problem of sticky wages interacting with weak nominal wages to create unnecessary unemployment.

Those problems with measuring inflation are serious if the Fed uses inflation that has already happened or uses forecasts of inflation that extend only a few months into the future.

Instead, I recommend using multi-year CPI forecasts based on several different time periods (e.g. in the 2 to 10 year range), and possibly forecasts for time periods that start a year or so in the future (this series shows how to infer such forecasts from existing markets). In the rare case where forecasts for different time periods say conflicting things about whether the Fed is too tight or loose, I’d encourage the Fed to use its judgment about which to follow.

The multi-year forecasts have historically shown only small reactions to phenomena such as the large spike in oil prices in mid 2008. I expect that pattern to continue: commodity price spikes happen when markets get evidence of their causes/symptoms (due to market efficiency), not at predictable future times. The multi-year forecasts typically tell us mainly whether the Fed will persistently miss its target.

Won’t using those long-term forecasts enable the Fed to make mistakes that it corrects (or over-corrects) for shorter time periods? Technically yes, but that doesn’t mean the Fed has a practical way to do that. It’s much easier for the Fed to hit its target if demand for money is predictable. Demand for money is more predictable if the value of money is more predictable. That’s one reason why long-term stability of inflation (or of wages or NGDP) implies short-term stability.

It would be a bit safer to target nominal wage rate forecasts rather than CPI forecasts if we had equally good markets forecasting both. But I expect it to be easier to convince the public to trust markets that are heavily traded for other reasons, than it is to get them to trust a brand new market of uncertain liquidity.