Investing

Book review: Capital in the Twenty-First Century, by Thomas Piketty.

Capital in the Twenty-First Century is decent at history, mediocre at economics, unimpressive at forecasting, and gives policy advice that is thoughtfully adapted to his somewhat controversial goals. His goals involve a rather different set of priorities than I endorse, but the book mostly doesn’t try to persuade us to adopt his goals, so I won’t say much here about why I have different priorities.

That qualifies as a good deal less dumbed-down-for-popularity than I expected from a bestseller.

Even when he makes mistakes, he is often sufficiently thoughtful and clear to be somewhat entertaining.

Piketty provides a comprehensive view of changes in financial inequality since the start of the industrial revolution.

Piketty’s main story is that we’ve experienced moderately steady increases in inequality, as long as conditions remained somewhat normal. There was a big break in that trend associated with WW1, WW2, and to lesser extents the Great Depression and baby boom. Those equalizing forces (mainly decreases in wealth) seem unlikely to repeat. We’re back on a trend of increasing inequality, with no end in sight.

Continue Reading

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.

2.

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.
Continue Reading

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.

This post is about the combined effects of cheap solar energy, batteries, and robocars.

Peak oil is coming soon, and will be at least as important as peak whale oil; probably more like peak horse.

First I noticed a good article on the future of fossil fuels by Colby Davis. Then I noticed a report on robocars by Rethinkx, which has some fairly strong arguments that Colby underestimates the speed of change. In particular, Colby describes “reasonable assumptions” as implying “Electric vehicles would make up a third of the market by 2035 and half by 2040”, whereas RethinkX convinced me to expect a 2035 market share of more like 99%.

tl;dr: electric robocars run by Uber-like companies will be cheap enough that you’ll have trouble giving away a car bought today. Uber’s prices will be less than your obsolete car’s costs of fuel, maintainance, and insurance.

As I was writing this post, a Chinese official talked about banning gas-based cars “in the near future” (timing not yet decided). If only I had bought shares in a lithium mining company before that news.

energy costs

Solar costs have dropped at a Moore’s law-like rate. See Swanson’s law.
Continue Reading

Book review: Superforecasting: The Art and Science of Prediction, by Philip E. Tetlock and Dan Gardner.

This book reports on the Good Judgment Project (GJP).

Much of the book recycles old ideas: 40% of the book is a rerun of Thinking Fast and Slow, 15% of the book repeats Wisdom of Crowds, and 15% of the book rehashes How to Measure Anything. Those three books were good enough that it’s very hard to improve on them. Superforecasting nearly matches their quality, but most people ought to read those three books instead. (Anyone who still wants more after reading them will get decent value out of reading the last 4 or 5 chapters of Superforecasting).

The book’s style is very readable, using an almost Gladwell-like style (a large contrast to Tetlock’s previous, more scholarly book), at a moderate cost in substance. It contains memorable phrases, such as “a fox with the bulging eyes of a dragonfly” (to describe looking at the world through many perspectives).

Continue Reading

The stock market reaction to the election was quite strange.

From the first debate through Tuesday, S&P 500 futures showed modest signs of believing that Trump was worse for the market than Clinton. This Wolfers and Zitzewitz study shows some of the relevant evidence.

On Tuesday evening, I followed the futures market and the prediction markets moderately closely, and it looked like there was a very clear correlation between those two markets, strongly suggesting the S&P 500 would be 6 to 8 percent lower under Trump than under Clinton. This correlation did not surprise me.

This morning, the S&P 500 prices said the market had been just kidding last night, and that Trump is neutral or slightly good for the market.

Part of this discrepancy is presumably due to the difference between regular trading hours and after hours trading. The clearest evidence for market dislike of Trump came from after hours trading, when the most sophisticated traders are off-duty. I’ve been vaguely aware that after hours markets are less efficiently priced. But this appears to involve at least a few hundred million dollars of potential profit, which somewhat stretches the limit of how inefficient the markets could plausibly be.

I see one report of Carl Icahn claiming

I thought it was absurd that the market, the S&P was down 100 points on Trump getting elected … but I couldn’t put more than about a billion dollars to work

I’m unclear what constrained him, but it sure looked like the market could have absorbed plenty more buying while I was watching (up to 10pm PST), so I’ll guess he was more constrained by something related to him being at a party.

But even if the best U.S. traders were too distracted to make the markets efficient, that leaves me puzzled about asian markets, which were down almost as much as the U.S. market during the middle of the asian day.

So it’s hard to avoid the conclusion that the market either made a big irrational move, or was reacting to news whose importance I can’t recognize.

I don’t have a strong opinion on which of the market reactions was correct. My intuition says that a market decline of anywhere from 1% to 5% would have been sensible, and I’ve made a few trades reflecting that opinion. I expect that market reactions to news tend to get more rational over time, so I’m now giving a fair amount of weight to the possibility that Trump won’t affect stocks much.

Why do people knowingly follow bad investment strategies?

I won’t ask (in this post) about why people hold foolish beliefs about investment strategies. I’ll focus on people who intend to follow a decent strategy, and fail. I’ll illustrate this with a stereotype from a behavioral economist (Procrastination in Preparing for Retirement):[1]

For instance, one of the authors has kept an average of over $20,000 in his checking account over the last 10 years, despite earning an average of less than 1% interest on this account and having easy access to very liquid alternative investments earning much more.

A more mundane example is a person who holds most of their wealth in stock of a single company, for reasons of historical accident (they acquired it via employee stock options or inheritance), but admits to preferring a more diversified portfolio.

An example from my life is that, until this year, I often borrowed money from Schwab to buy stock, when I could have borrowed at lower rates in my Interactive Brokers account to do the same thing. (Partly due to habits that I developed while carelessly unaware of the difference in rates; partly due to a number of trivial inconveniences).

Behavioral economists are somewhat correct to attribute such mistakes to questionable time discounting. But I see more patterns than such a model can explain (e.g. people procrastinate more over some decisions (whether to make a “boring” trade) than others (whether to read news about investments)).[2]

Instead, I use CFAR-style models that focus on conflicting motives of different agents within our minds.

Continue Reading

NGDP targeting has been gaining popularity recently. But targeting market-based inflation forecasts will be about as good under most conditions [1], and we have good markets that forecast the U.S. inflation rate [2].

Those forecasts have a track record that starts in 2003. The track record seems quite consistent with my impressions about when the Fed should have adopted a more inflationary policy (to promote growth and to get inflation expectations up to 2% [3]) and when it should have adopted a less inflationary policy (to avoid fueling the housing bubble). It’s probably a bit controversial to say that the Fed should have had a less inflationary policy from February through July or August of 2008. But my impression (from reading the stock market) is that NGDP futures would have said roughly the same thing. The inflation forecasts sent a clear signal starting in very early September 2008 that Fed policy was too tight, and that’s about when other forms of hindsight switch from muddled to saying clearly that Fed policy was dangerously tight.

Why do I mention this now? The inflation forecast dropped below 1 percent two weeks ago for the first time since May 2008. So the Fed’s stated policies conflict with what a more reputable source of information says the Fed will accomplish. This looks like what we’d see if the Fed was in the process of causing a mild recession to prevent an imaginary increase in inflation.

What does the Fed think it’s doing?

  • It might be relying on interest rates to estimate what it’s policies will produce. Interest rates this low after 6.5 years of economic expansion resemble historical examples of loose monetary policy more than they resemble the stereotype of tight monetary policy [4].
  • The Fed could be following a version of the Taylor Rule. Given standard guesses about the output gap and equilibrium real interest rate [5], the Taylor Rule says interest rates ought to be rising now. The Taylor Rule has usually been at least as good as actual Fed policy at targeting inflation indirectly through targeting interest rates. But that doesn’t explain why the Fed targets interest rates when that conflicts with targeting market forecasts of inflation.
  • The Fed could be influenced by status quo bias: interest rates and unemployment are familiar types of evidence to use, whereas unbiased inflation forecasts are slightly novel.
  • Could the Fed be reacting to money supply growth? Not in any obvious way: the monetary base stopped growing about two years ago, M1 and MZM growth are slowing slightly, and M2 accelerated recently (but only after much of the Fed’s tightening).

Scott Sumner’s rants against reasoning from interest rates explain why the Fed ought to be embarrassed to use interest rates to figure out whether Fed policy is loose or tight.

Yet some institutional incentives encourage the Fed to target interest rates rather than predicted inflation. It feels like an appropriate use of high-status labor to set interest rates once every few weeks based on new discussion of expert wisdom. Switching to more or less mechanical responses to routine bond price changes would undercut much of the reason for believing that the Fed’s leaders are doing high-status work.

The news media storytellers would have trouble finding entertaining ways of reporting adjustments that consisted of small hourly responses to bond market changes. Whereas decisions made a few times per year are uncommon enough to be genuinely newsworthy. And meetings where hawks struggle against doves fit our instinctive stereotype for important news better than following a rule does. So I see little hope that storytellers will want to abandon their focus on interest rates. Do the Fed governors follow the storytellers closely enough that the storytellers’ attention strongly affects the Fed’s attention? Would we be better off if we could ban the Fed from seeing any source of daily stories?

Do any other interest groups prefer stable interest rates over stable inflation rates? I expect a wide range of preferences among Wall Street firms, but I’m unaware which preferences are dominant there.

Consumers presumably prefer that their banks, credit cards, etc have predictable interest rates. But I’m skeptical that the Fed feels much pressure to satisfy those preferences.

We need to fight those pressures by laughing at people who claim that the Fed is easing when markets predict below-target inflation (as in the fall of 2008) or that the Fed is tightening when markets predict above-target inflation (e.g. much of 2004).

P.S. – The risk-reward ratio for the stock market today is much worse than normal. I’m not as bearish as I was in October 2008, but I’ve positioned myself much more cautiously than normal.

Notes:

[1] – They appear to produce nearly identical advice under most conditions that the U.S. has experienced recently.

I expect inflation targeting to be modestly safer than NGDP targeting. I may get around to explaining my reasons for that in a separate post.

[2] – The link above gives daily forecasts of the 5 year CPI inflation rate. See here for some longer time periods.

The markets used to calculate these forecasts have enough liquidity that it would be hard for critics to claim that they could be manipulated by entities less powerful than the Fed. I expect some critics to claim that anyway.

[3] – I’m accepting the standard assumption that 2% inflation is desirable, in order to keep this post simple. Figuring out the optimal inflation rate is too hard for me to tackle any time soon. A predictable inflation rate is clearly desirable, which creates some benefits to following a standard that many experts agree on.

[4] – providing that you don’t pay much attention to Japan since 1990.

[5] – guesses which are error-prone and, if a more direct way of targeting inflation is feasible, unnecessary. The conflict between the markets’ inflation forecast and the Taylor Rule’s implication that near-zero interest rates would cause inflation to rise suggests that we should doubt those guesses. I’m pretty sure that equilibrium interest rates are lower than the standard assumptions. I don’t know what to believe about the output gap.