stock market crash

All posts tagged stock market crash

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.

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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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.

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.

Book review: Fragile by Design: The Political Origins of Banking Crises and Scarce Credit, by Charles W. Calomiris, and Stephen H. Haber.

This book start out with some fairly dull theory, then switches to specific histories of banking in several countries with moderately interesting claims about how differences in which interest groups acquired power influenced the stability of banks.

For much of U.S. history, banks were mostly constrained to a single location, due to farmers who feared banks with many branches would shift their lending elsewhere when local crop failures made local farms risky to loan to. Yet comparing to Canada, where seemingly small political differences led to banks with many branches, it seems clear that U.S. banks were more fragile because of those restrictions, and less competition in the U.S. left consumers with less desirable interest rates.

By the 1980s, improved communications eroded farmers’ ability to tie banks to one locale, so political opposition to multi-branch banks vanished, resulting in a big merger spree. The biggest problem with this merger spree was that the regulators who approved the mergers asked for more loans to risky low-income borrowers. As a result, banks (plus Fannie Mae and Freddie Mac) felt compelled to lower their standards for all borrowers (the book doesn’t explain what problems they would have faced if they had used different standards for loans the regulators pressured them to make).

These stories provide a clear and plausible explanation of why the U.S. has a pattern of banking crises that Canada and a few other well-run countries have almost entirely avoided over the past two centuries. But they suggest the U.S. banking crises should have been more unique among mature democracies than was actually the case.

The authors are overly dismissive of problems that don’t fit their narrative. Commenting on the failure of Citibank, Lehman, AIG, etc to sell more equity in early 2008, they say “Why go to the markets to raise new capital when you are confident that the government is going to bail you out?”. It seems likely bankers would have gotten better terms from the market as long as they didn’t wait until the worst part of the crisis. I’m pretty sure they gave little thought to bailouts, and relied instead on overly complacent expectations for housing prices.

The book has a number of asides that seem as important as their main points, such as claims that Britain’s greater ability to borrow money led to its military power, and its increased need for military manpower drove its expansion of the franchise.

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.

One simple way to prevent fluctuations like those of last Thursday would be for stock exchanges to prohibit orders to buy or sell at the market.

That wouldn’t mean prohibiting orders that act a lot like market orders. People could still be allowed to place an order to sell at a limit of a penny. But having an explicit limit price would discourage people from entering orders that under rare conditions end up being executed at a price 99 percent lower than expected.

It wouldn’t even require that people take the time to type in a limit price. Systems could be designed to have a pseudo-market order that behaves a lot like existing market orders, but which has a default limit price that is, say, 5 percent worse than the last reported price.

However, it’s not obvious to me that those of us who didn’t sell at ridiculously low prices should want any changes in the system. Moderate amounts of money were transferred mainly from people who mistakenly thought they were sophisticated traders to people who actually were. People who are aware that they are amateurs rarely react fast enough to declines to have done anything before prices recovered. The decline looked like it was primarily the result of stop-loss strategies, and it’s hard to implement those without at least superficially imitating an expert investor.

Many people seem to be reacting to the recent stock market crash the way they wish they had to the 1987 crash, and a smaller number are comparing it to 1929.
The unusual resemblance to the crash of 1937 makes me expect something in between those two scenarios.

  • The 1937 crash was caused in part by a sudden increase in caution by banks after the Fed significantly increased their reserve requirement. Banks played no interesting role in the 1929 or 1987 crashes.
  • The 1929 and 1987 crashes followed stock market peaks in August, versus March and the prior October for the 1937 and 2008 crashes.
  • The 1937 and 2008 crashes both came eight years after one of history’s largest stock market bubbles.
  • The 1929 and 1987 crashes followed an increase in the discount rate to 6 percent. The 1937 and 2008 crashes followed decreases in the discount rate to 1 and 2.25 percent.

All four crashes happened mainly in October and their behavior in that month provides little reason for distinguishing them.
If the 1937 crash is a good model for what to expect in our near future, many investors who are currently following the lesson they learned from the 1987 crash will discover in early 2009 that the unexpectedly severe recession casts doubt on the belief that crashes create good buying opportunities. How many of them will stick to their buy and hold commitment then (when I expect it will be a good idea)?
When the extent of the recession becomes disturbing, remember Brad DeLong’s perspective:

Is 2008 Our 1929? No. It is not. The most important reason it is not is that Bernanke and Paulson are both focused like laser beams on not making the same mistakes as were made in 1929….
They want to make their own, original, mistakes..

(HT James Hamilton).

For more than 2 months, Treasury Inflation-Indexed Notes maturing within 2 years have been selling at prices that apparently mean their yields are negative (e.g. see here and here). This isn’t the first time people have apparently paid a government to hold their money, but I can’t think of a previous case where yields reached -1 percent.
What can cause such a perverse situation? An expectation that the CPI would overstate inflation by as much as 1 percent would mean appearances are misleading and investors do expect to make money on those notes. I could make a case for that by focusing on the way that the CPI’s reliance on rents to measure housing costs hides the effects of dropping home prices. But most evidence about people’s inflation expectations (e.g. the University of Michigan Inflation Expectation report) say they expect more inflation than what can be inferred from the Treasury Inflation-Indexed Notes about expected CPI change.
So I’m inclined to conclude that we’re seeing investors paying abnormally large amounts in order to get liquidity, and probably plan to redeploy those assets somewhere else within a few months. If we see a big financial crisis soon, that strategy may pay off. But having people prepare for financial crises tends to reduce their magnitude, so I’m skeptical and am short t-bond futures.