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).

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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.

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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.


[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.

I was quite surprised by a paper (The Surprising Alpha From Malkiel’s Monkey and Upside-Down Strategies [PDF] by Robert D. Arnott, Jason Hsu, Vitali Kalesnik, and Phil Tindall) about “inverted” or upside-down[*] versions of some good-looking strategies for better-than-market-cap weighting of index funds.

They show that the inverse of low volatility and fundamental weighting strategies do about as well as or outperform the original strategies. Low volatility index funds still have better Sharpe ratios (risk-adjusted returns) than their inverses.

Their explanation is that most deviations from weighting by market capitalization will benefit from the size effect (small caps outperform large caps), and will also have some tendency to benefit from value effects. Weighting by market capitalization causes an index to have lots of Exxon and Apple stock. Fundamental weighting replaces some of that Apple stock with small companies. Weighting by anything that has little connection to company size (such as volatility) reduces the Exxon and Apple holdings by more than an order of magnitude. Both of those shifts exploit the benefits of investing in small-cap stocks.

Fundamental weighting outperforms most strategies. But inverting those weights adds slightly more than 1% per year to those already good returns. The only way that makes sense to me is if an inverse of market-cap weighting would also outperform fundamental weighting, by investing mostly in the smallest stocks.

They also show you can beat market-capitalization weighted indices by choosing stocks at random (i.e. simulating monkeys throwing darts at the list of companies). This highlights the perversity of weighting by market-caps, as the monkeys can’t beat the simple alternative of investing equal dollar amounts in each company.

This increases my respect for the size effect. I’ve reduced my respect for the benefits of low volatility investments, although the reduced risk they produce is still worth something. That hasn’t much changed my advice for investing in existing etf’s, but it does alter what I hope for in etf’s that will become available in the future.

[*] – They examine two different inverses:

  1. Taking the reciprocal of each stock’s original weight
  2. Taking the max(weight) and subtracting each stock’s original weight

In each case the resulting weights are then normalized to add to 1.

In his talk last week, Robin Hanson mentioned an apparently suboptimal level of charitable donations to for-profit companies.

My impression is that some of the money raised on Kickstarter and Indiegogo is motivated by charity.

Venture capitalists occasionally bias their investments towards more “worthy” causes.

I wonder whether there’s also some charitable component to people accepting lower salaries in order to work at jobs that sound like they produce positive externalities.

Charity for profitable companies isn’t likely to become a popular concept anytime soon, but that doesn’t keep subsets of it from becoming acceptable if framed differently.

The CFTC is suing Intrade for apparently allowing U.S. residents to trade contracts on gold, unemployment rates and a few others that it had agreed to prevent U.S. residents from trading. The CFTC is apparently not commenting on whether Intrade’s political contracts violate any laws.

U.S. traders will need to close our accounts.

The email I got says

In the near future we’ll announce plans for a new exchange model that will allow legal participation from all jurisdictions – including the US.

(no statement about whether it will involve real money, which suggests that it won’t).

I had already been considering closing my account because of the hassle of figuring out my Intrade income for tax purposes.

Book review: The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t by Nate Silver.

This is a well-written book about the challenges associated with making predictions. But nearly all the ideas in it were ones I was already familiar with.

I agree with nearly everything the book says. But I’ll mention two small disagreements.

He claims that 0 and 100 percent are probabilities. Many Bayesians dispute that. He has a logically consistent interpretation and doesn’t claim it’s ever sane to believe something with probability 0 or 100 percent, so I’m not sure the difference matters, but rejecting the idea that those can represent probabilities seems at least like a simpler way of avoiding mistakes.

When pointing out the weak correlation between calorie consumption and obesity, he says he doesn’t know of an “obesity skeptics” community that would be comparable to the global warming skeptics. In fact there are people (e.g. Dave Asprey) who deny that excess calories cause obesity (with better tests than the global warming skeptics).

It would make sense to read this book instead of alternatives such as Moneyball and Tetlock’s Expert Political Judgment, but if you’ve been reading books in this area already this one won’t seem important.

Book review: Manias, Panics and Crashes: A History of Financial Crises 6th ed., by Charles P. Kindleberger and Robert Aliber.

The book starts with a good overview of how a typical bubble develops and bursts. But I found the rest of the book poorly organized. I often wondered whether the book was reporting a particular historical fact as an example of some broad pattern – if not, why weren’t they organized in something closer to chronological order? It has lots of information that is potentially valuable, but not organized into a useful story or set of references.