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The Limits to Trusting the Robots

October 20, 2017 1 comment

After another day on Thursday of stocks starting to look mildly tired – but only mildly – only to rally back to a new closing high, it hardly seems unusual any more. I have to keep pinching myself, reminding myself that this is historically abnormal. Actually, very abnormal. If the S&P 500 Total Return Index ends this month with a gain, it will be the second time in history that has happened. The other time was in 1936, as stocks bounced back from a deep bear market (at the end of those 12 months, in March 1936, stocks were still 54% off the 1929 highs). A rally this month would also mean that stocks have gained for 19 out of the last 20 months, the longest streak with just one miss since…1936 again.

But we aren’t rebounding from ‘oversold.’ This seems to be a different situation.

What is going on is confounding the wise and the foolish alike. Every dip is bought; the measures of market constancy (noted above, for example) are at all-time highs and the measures of market volatility such as the VIX are at all-time lows. It is de rigeur at this point to sneer “what could go wrong?” and you may assume I have indeed so sneered. But I also am curious about whether there is some kind of feedback loop at work that could cause this to go on far longer than it “should.”

To be sure, it shouldn’t. By many measures, equities are at or near all time measures of richness. The ones that are not at all-time highs are still in the top decile. Buying equities (or for that matter, bonds) at these levels ought to be a recipe for a capitalistic disaster. And yet, value guys are getting carried out left and right.

Does the elimination (with extreme prejudice) of value traders have any implications?

There has been lots of research about market composition: models, for example, that examine how “noise” and “signal” traders come together to create markets that exhibit the sorts of characteristics that normal markets do. Studies of what proportion of “speculators” you need, compared to “hedgers,” to make markets efficient or to cause them to have bubbles form.

So my question is, what if the combination of “buy the dip” micro-time-frame value guys, combine with the “risk parity” guys, represents a stable system?

Suppose equity volatility starts to rise. Then the risk-parity guys will start to sell equities, which will push prices lower and tend to push volatility higher. But then the short-term value guys step in to ‘buy the dip.’ To be clear, these are not traditional value investors, but rather more like the “speculators” in the hedger/speculator formulation of the market. These are people who buy something that has gone down, because it has gone down and is therefore cheaper, as opposed to the people who sell something that has gone down, because the fact that it has gone down means that it is more likely to go down further. In options-land, the folks buying the dip are pursuing a short-volatility strategy while the folks selling are pursuing a long-volatility strategy.[1]

Once the market has been stabilized by the buy-the-dip folks, who might be for example hedging a long options position (say, volatility arbitrage guys who are long actual options and short the VIX), then volatility starts to decline again, bringing the risk-parity guys back into equities and, along with the indexed long-only money that is seeking beta regardless of price, pushing the market higher. Whereupon the buy-the-dip guys get out with their scalped profit but leaving prices higher, and volatility lower, than it started (this last condition is necessary because otherwise it ends up being a zero-sum game. If prices keep going higher and implied volatility lower, it need not be zero-sum, which means both sides are being rewarded, which means that we would see more and more risk-parity guys – which we do – and more and more delta-hedging-buy-the-dip guys – which we do).

Obviously this sort of thing happens. My question though is, what if these different activities tend to offset in a convergent rather than divergent way, so that the system is stable? If this is what is happening then traditional value has no meaning, and equities can ascend arbitrary heights of valuation and implied volatility can decline arbitrarily low.

Options traders see this sort of stability in micro all the time. If there is lots of open interest in options around, say, the 110 strike on the bond contract, and the Street (or, more generally, the sophisticated and leveraged delta-hedgers) is long those options, then what tends to happen is that if the bond contract happens to be near 110 when expiry nears it will often oscillate around that strike in ever-declining swings. If I am long 110 straddles and the market rallies to 110-04, suddenly because of my gamma position I find myself long the market since my calls are in the money and my puts are not. If I sell my delta at 110-04, then I have locked in a small profit that helps to offset the large time decay that is going to make my options lose all of their remaining time value in a short while.[2] So, if the active traders are all long options at this strike, what happens is that when the bond goes to 110-04, all of the active folks sell to try and scalp their time decay, pushing the bond back down. When it goes to 99-28, they all buy. Then, the next time up, the bond gets to 110-03 and the folks who missed delta-hedging the last time say “okay, this time I will get this hedge off” and sell, so the oscillation is smaller. Sometimes it gets really hard to have any chance of covering time decay at all because this process results in the market stabilizing right at 110-00 right up until expiration. And that stabilization happens because of the traders hedging long-volatility positions in a low-volatility environment.

But for the options trader, that process has an end – options expiration. In the market process I am describing where risk-parity flows are being offset by buy-the-dip traders…is there an end, or can that process continue ad infinitum or at least, “much longer than you think it can?”

Spoiler alert: it already has continued much longer than I thought it could.

There is, however, a limit. These oscillations have to reach some de minimus level or it isn’t worth it to the buy-the-dip guys to buy the dip, and it isn’t worth reallocation of risk-parity strategies. This level is much lower now than it has been in the past, thanks to the spread of automated trading systems (i.e., robots) that make the delta-hedging process (or its analog in this system) so efficient that it requires less actual volatility to be profitable. But there is a limit. And the limit is reach two ways, in fact, because the minimum oscillation needed is a function of the capital to be deployed in the hedging process. I can hedge a 1-lot with a 2 penny oscillation in a stock. But I can’t get in and out of a million shares that way. So, as the amount of capital deployed in these strategies goes up, it actually raises the potential floor for volatility, below which these strategies aren’t profitable (at least in the long run). However, there could still be an equilibrium in which the capital deployed in these strategies, the volatility, and the market drift are all balanced, and that equilibrium could well be at still-lower volatility and still-higher market prices and still-larger allocations to risk-parity etc.

It seems like a good question to ask, the day after the 30th anniversary of the first time that the robots went crazy, “how does this stable system break down?” And, as a related question, “is the system self-stabilizing when perturbed, or does it de-stabilize?”

Some systems are self-stabilizing with small perturbations and destabilizing with larger perturbations. Think of a marble rolling around in a bowl. A small push up the side of the bowl will result in the marble eventually returning to the bottom of the bowl; a large push will result in the marble leaving the bowl entirely. I think we are in that sort of system. We have seen mild events, such as the shock of Brexit or Trump’s electoral victory, result in mild volatility that eventually dampened and left stocks at a higher level. I wonder if, as more money is employed in risk parity, the same size perturbation might eventually be divergent – as volatility rises, risk parity sells, and if the amount of dip-buyers is too small relative to the risk parity sellers, then the dip-buyers don’t stabilize the rout and eventually become sellers themselves.

If that’s the secret…if it’s the ratio of risk-parity money to dip-buyer money that matters in order to keep this a stable, symbiotic relationship, then there are two ways that the system can lose stability.

The first is that risk parity strategies can attract too much money. Risk parity is a liquidity-consumer, as they tend to be sellers when volatility is rising and buyers when volatility is falling. Moreover, they tend to be sellers of all assets when correlations are rising, and buyers of all assets when correlations are falling. And while total risk-parity fund flows are hard to track, there is little doubt that money is flowing to these strategies. For example one such fund, the Columbia Adaptive Risk Allocation Fund (CRAZX), has seen fairly dramatic increases in total assets over the last year or so (see chart, source Bloomberg. Hat tip to Peter Tchir whose Forbes article in May suggested this metric).

The second way that ratio can lose stability is that the money allocated to buy-the-dip strategies declines. This is even harder to track, but I suspect it is related to two things: the frequency and size of reasonable dips to buy, and the value of buying the dip (if you buy the dip, and the market keeps going down, then you probably don’t think you did well). Here are two charts, with the data sourced from Bloomberg (Enduring Intellectual Properties calculations).

The former chart suggests that dip-buyers may be getting bored as there are fewer dips to buy (90% of the time over the last 180 days, the S&P 500 has been within 2% of its high). The latter chart suggests that the return to buying the dip has been low recently, but in general has been reasonably stable. This is essentially a measure of realized volatility. In principle, though, forward expectations about the range should be highly correlated to current implied volatility so the low level of the VIX implies that buying the dip shouldn’t give a large return to the upside. So in this last chart, I am trying to combine these two items into one index to give an overall view of the attractiveness of dip buying. This is the VIX, minus the 10th percentile of dips to buy.

I don’t know if this number by itself means a whole lot, but it does seem generally correct: the combination of fewer dips and lower volatility means dip-buying should become less popular.

But if dip-buying becomes less popular, and risk-parity implies more selling on dips…well, that is how you can get instability.

[1] This is not inconsistent with how risk parity is described in this excellent paper by Artemis Capital Management (h/t JN) – risk parity itself is a short volatility strategy; to hedge the delta of a risk parity strategy you sell when markets are going down and buy when markets are going up, replicating a synthetic long volatility position to offset.

[2] If this is making your eyes glaze over, skip ahead. It’s hard to explain this dynamic briefly unless I assume some level of options knowledge in the reader. But I know many of my readers don’t have that requisite knowledge. For those who do, I think this may resonate however so I’m plunging forward.

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Bitcoin Versus Tesla

July 18, 2017 3 comments

Last night, over drinks – a detail that will gain more salience when I describe the discussion – several friends and I were talking about lots of market-related items (as well as, of course, many non-market items).

The topics were as diverse as bitcoin, New Jersey Transit, and Tesla. However…and here’s where the drinks may have played a role…we also explored intersections of the elements of this set. For example, one of our party pointed out that fifteen Teslas would produce about the same power as a diesel locomotive, but at a fraction of the price. Given the recent record of New Jersey Transit’s locomotive fleet (among other problems), perhaps this is worth considering. Not only that, going to work in a train pulled by 15 Teslas would be much more stylish.[1]

A more interesting connection is between Bitcoin and Tesla.

In my book, I reflect at length about the significance of having money which is backed by something concrete (no matter what that is) compared to something backed only by faith – faith that other people will accept our money as a medium of exchange, in exchange for goods or services at rates reasonably predictable and not terribly volatile. Inflation is caused by too much money in the system; hyperinflation is what happens when a currency loses its anchor of confidence and people lose faith that these things will be true in the future. I talk a bit about how high rates of inflation, by eroding confidence, can lead to hyperinflation – but that’s only true of fiat currencies. If money is backed by something tangible, whether it is a precious metal or a bushel of rice, there are limits to how much it can depreciate in real terms and hyperinflation is difficult to come by in these circumstances.

In this context, consider Bitcoin or any of its crypto-currency brethren. Bitcoin is not backed by anything; indeed, it is backed by even less than the “classic” fiat currencies that issuing governments at least promise to accept in payment of citizen obligations to the government. This is not a critique – it simply is. Evidently, the inflation issue is not currently a problem with Bitcoin…as the chart below (source: Bloomberg) suggests, everything in the world is deflating in Bitcoin-equivalents.

But the fact remains that if something were to happen – such as the MtGox scandal a few years ago, at the left side of that chart – that affected people’s confidence that someone else would take Bitcoin in payment, then the value of Bitcoin could (and did) drop precipitously. At the extreme, Bitcoin could go to zero if no one was willing to accept it in exchange – for example, if for some reason it became impossible to confirm that the contents of your Bitcoin wallet was really yours.[2] There is no one you can turn to who is guaranteed to give you something real in exchange.

Now, no one thinks of Tesla as a currency. But, actually, equity securities representing ownership in Tesla could be considered a form of currency – you can exchange them for other items of value, although the usual way is to exchange them for dollars which can then be used to buy other items of value. I am not sure I would call  its price in exchange reasonably stable…but it’s certainly more stable than Bitcoin. Here’s the salient commonality, however: at the current price, representing a 11x price-to-book ratio, 6x price to sales ratio, and undefinable price to free cash flow (-$9.74/share free cash flow) or earnings, on a stock with negative net margins, ROA, ROE, and ROC, the price of Tesla is almost entirely faith-based. It is based on a quasi-religious belief by the equity owners that the CEO will manage to produce cars at a positive margin and maintain a large market share, which it will be able to maintain even once large auto manufacturers start to compete.

Far be it from me to question whether investors’ faith will prove well- or ill-founded. I will leave that to my friend @markbspiegel. I don’t own Tesla and have no plans to be long it or short it. My point, though, is that it is remarkably like Bitcoin in that it is backed primarily by faith and, as with any faith-based currency, is entirely based on that faith remaining unshaken. For the implications of having that faith shaken, see Enron in 2001 (chart below, source Bloomberg).

Interestingly, in the battle of Bitcoin versus Tesla it is the former that is winning. A share of Tesla in 2015 was worth 1 Bitcoin. Today, that share is only worth 0.14 Bitcoins (see chart, showing the ratio of Tesla to Bitcoin).[3]

All of which goes mainly to show – be careful when you go out for drinks with quant finance friends!

[1] We thought perhaps Elon Musk is just being coy, playing the long game before he springs this brilliant idea on the public. But today another friend of mine pointed out that it isn’t just the power you’re paying for but the sustainability of that power, and he estimated that 15 Teslas could only pull the train for about 8 miles. Oh well.

[2] “Preposterous!” shout the supporters of Bitcoin. Relax, I’m not saying this is something that will or could happen. It’s not a prediction. It’s merely a thought experiment.

[3] This is a ridiculous chart and it means nothing. But it’s fun. You should see what it looks like if you go back farther. In 2010, one share of Tesla was worth 300 Bitcoins!

Categories: Analogy, Bitcoin, Silly

Horse Racing and Value Investing

June 28, 2017 2 comments

Momentum and value investing are two classes of strategies that, historically, alternate ascendancy in terms of which strategy is dominating the other. They are largely opposite strategies: a momentum investor buys a security because it has gone higher (because prices aren’t really a random walk, something which has gone up in price is more likely to continue to go up in price) while a value investor buys a security because it has gone lower (since the lower the buying price, the better the return on a security).

You can imagine the two strategies in the context of horse racing. The “momentum” strategy would be represented by betting on the “favorite,” the horse with the best odds to win as determined by the prior betting. (Some people think the track sets the odds on the horses, but that’s not the case. The payouts are based on the proportion of the entire betting pool allocated to bets on a particular horse, less the track’s vig. So, a horse with “good odds of winning” is simply the horse that has the most money bet on it to win.) That’s pretty close to exactly what a momentum investor in stocks is doing, right? A “value” investor, in the context of horse racing, is the person who bets on the long shots because they have big payoffs when they hit (and the bettor believes, obviously, that these unloved horses are irrationally disliked because most people like betting on favorites and winning frequent, small amounts instead of winning infrequent, large amounts.)

So at the track, sometimes the favorites win and sometimes the long shots win, and there are people in each camp that will tell you their strategy is the better one in the long run. I don’t know that there have been many studies of whether “value” or “momentum” investing in horse racing is the better strategy, but there have been numerous such studies in finance. Both value and momentum have been shown to improve investing strategies, with better risk-adjusted returns than simply buying and holding a capitalization-weighted basket of securities. They tend to have “seasons,” by which I mean long periods when one or the other of these strategies tends to be dominant. But it is very unlikely that either of these strategies could ever be the winner over the long run.

To see why, think of the horse track. Suppose everyone noticed that the favorites were winning, and so more and more money came in on the favorites. What would happen then is that the payoffs on the favorite would get worse and worse, and the payoff on the long shots would get better and better. Eventually, it would be very hard to make money betting the favorites unless they always won. On the other hand, if lots of money were to come in on the long shots, they wouldn’t be long shots for long. So neither strategy can dominate forever.

The same is true in finance. If everyone is betting on the previous winners, then eventually the “losers” become easy money, and vice-versa. The chart below (which is imperfect for a reason I’ll mention in a moment) illustrates the give-and-take. It shows the Russell 1000 “growth” index (RLG, in white) and the Russell 1000 “value” index (RLV, in orange). The source of the chart is Bloomberg.

You can see clearly how “growth” (which has similarities to momentum) outperformed in the Y2k bubble, depressing the heck out of value investors. But then value beat growth for a while, until the next bubble in 2007. The ensuing bear market crushed both strategies.

One caveat here is that the composition of the “growth” and “value” indices doesn’t change every day, and isn’t based on momentum, so that at the peak in 2007 a lot of stocks in the “value” index were not truly value stocks. But you get the general point.

The second, and more important caveat, applies to the years since 2009. This chart would lead one to believe that both value and growth stocks are doing equally well. And they are, given this definition of growth and value. But what this chart really means is that the distinction of “growth” and “value” are now less important than the single factor “momentum.” Whether you have a growth stock with momentum, or a value stock with momentum, is less important than if you compare performance to something else that does not have momentum.

We can illustrate this concept by calculating portfolios that are built to maximize momentum or value for a given risk constraint, and comparing the performance of the portfolios. I’ve done this for a bunch of different types of portfolios (different commodities, equities only, broad investor stock/bond/cash/commodity portfolios, etc) and they all look something like this chart, which shows the total returns of these two competing portfolios:

What I’m doing here is for the security universe in question, I’m calculating for each security a “momentum” score that is simply the year-on-year percentage change in price, and a simple “value” score that is the inverse of the four-year price change.[1] Then I optimize two portfolios, one which maximizes the value score and one which maximizes the momentum score, and then track that portfolio’s performance for the following month (whereupon the portfolios are reconstructed). If there was no memory to the momentum or value processes, these lines would wander around 100…a high momentum score would not increase next month’s performance, e.g.. But, evidently, it does and it has. Over the last three years, for this security universe, the “momentum” portfolio outperformed the “value” portfolios 78% of the time by a cumulative 50%. And this happens for every universe of securities I test. Even within commodities, which are universally hated, the high-momentum commodities are hated less.

Note that this is at the same time that in the first chart above the “growth” and “value” stocks have been performing about the same. This just means that the dispersion between growth and value has been narrow, which is another way that volatility is low.

As a value investor, this situation has been tortuous, and has led me to change the way we do certain things to keep from being purely value all the time. But as I said before, the situation cannot remain this way forever. Every computer is chasing every other computer, for now. But at some point, one of the computers will decide it’s time to lean the other way, and the first ones that do so will be the winners while the other computers start to chase momentum lower.

That might not be as fun for investors as the recent period has been, unless you’re the one who was getting paid on the nag at 200-1 odds.

[1] In this I am taking a cue from Asness, Moskowitz, and Pedersen, “Value and Momentum Everywhere,” Journal of Finance Vol LXVIII, #3, June 2013.

Pre-Existing Conditions and Fire Insurance

When it comes to health care, I continue to be amazed at the utter nonsense that gets tossed about when the discussion comes to insuring pre-existing conditions. The problem seems to be that no one who understands insurance has anything to say about health care legislation, because the question of why you may not want to guarantee issuance of insurance at a given rate no matter what pre-existing conditions the patient has is really not hard to understand. Consider this little vignette:

Caller: Hi, I’d like to buy some home insurance, please.

Agent: Sure, I’d be happy to help with that.

Caller: Does the insurance cover loss from fire?

Agent: Of course. That’s just one of many coverages you get with our insurance. Can you tell me a little bit about your house?

Caller: It’s three bedrooms, two baths. Worth about $300,000. What will the insurance cost me?

Agent: It depends on a few more pieces of information I have to gather from you, but about <pause> $800 per year.

Caller: That sounds great. Sign me up. Do you need my credit card?

Agent (laughing): Just a moment, sir! I need to get more information to give you an accurate quote. Can you tell me about the condition of your home?

Caller: You mean, right now?

Agent: Um…yes.

Caller: It’s on fire.

Agent: Your house is on fire?

Caller: Yep. Can we speed this up a bit?

Agent: Sir, we can’t insure your house against fire if it’s already on fire!

Caller: Why not? Just because it’s a condition that existed prior to my call?

Agent: Well, yes.

Caller: That’s outrageous! I demand you issue me insurance!

Agent (after conferring with management): Sir, it turns out we can offer you insurance on your home…

Caller: See? I knew you could be reasonable.

Agent: …for $350,000.

See, here’s the thing. Insurance is based on the principle of distributing money in a pool of similar risks from insureds who don’t experience the insurable event to those who do experience the insurable event. If someone enters the pool who has already had the insurable event, it’s simply a transfer – there’s no insurance. Person A needs $100,000 in surgeries, and gets an insurance policy that costs $1,000. Where does the rest of the money come from? It doesn’t come from the insurance company, and I think perhaps people don’t understand that point (and Republicans are truly abysmal at explaining it). The rest of the money comes from other insureds. Consider this situation: rather than get private insurance, you and twenty of your fraternity brothers from college – all about the same age and health – decide to form your own mutual insurance network. Everyone agrees that if anyone gets sick, the whole group will pitch in equally to pay the medical bills of the sick person. Now, suppose one person says “can we take my mom in as well? She has early-onset dementia and was just diagnosed with lung cancer. She’d be glad to join the group and pay an equal share, because fair is fair!” Do you think it is fair that mom pays the same amount?

The insurance company makes money if the money they pay out is less than the money they take in, but they also stand to lose if they underwrite the risks poorly and pay out more than they take in. And insurance companies don’t systematically rip people off by underwriting policies super-conservatively. In fact, the evidence seems to be that insurance companies rather frequently fall prey to pressures to move more product, and underwrite policies too aggressively.

The social-justice question can be separated from the health care insurance question. If you feel that everyone should have their medical bills covered, no matter what, then create a federal umbrella program for high-risk insureds and pay for that program with taxpayer funds. That’s explicit: let the cost of health insurance cover the actual cost of health insurance, which involves conditions the risk pool doesn’t have yet, and represent the welfare or charity – because that’s what it is, of course, when others pick up the expense of those unable to pay – as exactly that. After all, the federal government offers flood insurance to landowners who can’t get insurance at a “reasonable price” because the land floods all the time; that is a similar welfare situation in which taxpayers have decided they are willing to foot the bill because it’s a social good that people live or build on the flood plain. (I’m not sure why, but that’s the import of the federal flood insurance program). So there’s precedent for the government taking over pools that are too risky for private markets.

Again, this isn’t rocket science and it isn’t hard to explain. Why doesn’t someone get on television and explain it? How about a commercial using my script?

Categories: ACA, Analogy, Good One, Insurance, Rant

Do Shortages Cause Lower Prices?

September 19, 2016 3 comments

This is a quick post this morning because it is rainy and I am grumpy and feel like complaining.

Over the weekend I saw a post from a major market news website. I don’t want to name the website, because what they wrote was embarrassingly obtuse. I wouldn’t like it if someone cited my blog when I write something obtuse, so I won’t link to theirs. Consider it professional courtesy.

Here is what they wrote: “The global bond selloff was blamed largely on fears the European Central Bank and the Bank of Japan will eventually run out of bonds to buy.”

At this point, time yourself to see how long it takes you to figure out what’s wrong with that sentence. Score yourself with this table:

1 second or less: Congratulations! You have excellent common sense.

2-30 seconds: You have good common sense but maybe spend too much time around markets.

31-2 minutes: You are smart enough to figure this out, but you watch too much financial TV.

Over 2 minutes: You can be a Wall Street economist!

“I don’t see anything wrong” : You can write for the blog in question.

I could give an answer key, but in the interest of ranting let me present instead an analogy:

In a certain town there is a grocery store, whose proprietor sells apples for 50 cents. One day, a man walks in, flags down the proprietor, and says, “Hello kind sir. I see you have apples for sale. I would like to buy your apples. You see, I have bought all of the apples in this state, and in the surrounding state. I have bought every apple in this town. In fact, I have bought almost all of this year’s harvest. So, I’d like to buy your apples because I have money to buy apples and you have the only apples left.”

The proprietor responds, “Great! I will sell them to you for a nickel each!”

Because, you see, since the apple buyer has just about run out of apples to buy, the price of apples should fall. Right? Well, that’s exactly the point the blog made about bonds: because investors fear the ECB and BOJ will eventually run out of bonds to buy, bond prices fell. If there are really investors out there who think that when the supply of something declines, its price will fall…please introduce me to them, because I’d like to trade with them.

The fact that global central banks continue to buy bonds is the single, best reason to think that yields may not rise. In normal times, bond yields would be rising right now to reflect the fact that inflation is rising, just about everywhere we measure inflation (maybe not in Japan – core inflation in Japan was rising thanks to more-rapid money growth, but when the BOJ lowered rates into negative territory it lowered money velocity and may have squashed the recent rise). But if central banks are buying every bond they can, then prices are more likely to stay high and yields low – even in places like the US where the central bank is not currently buying bonds, because a paucity of Japanese and European bonds tends to increase the demand for US bonds. The risk to the bulls is actually that central banks stop buying bonds.

Maybe that is the weird reasoning that the blog in question was employing: once there are no bonds, central banks will have to stop buying them. And when the central banks stop buying bonds, their prices should fall. Ergo, when there are no bonds to buy the prices should fall. Sure, that makes sense!

Twits and Brits

June 27, 2016 1 comment

I want to talk today about some of the really important pieces of information that circulated this weekend. First, I am certain that everyone is familiar with the following chart, which made the rounds after the Brexit vote. It shows an enormous surge in the search term “What is the EU” after the Brexit vote was completed:

noaxisThis chart, or something very much like it, was all over the place. Oh, wait! I just realized that I forgot to put the axes on the chart! Here it is with a few more relevant pieces of information – incidentally the same information that was left off the original chart. It turns out that it wasn’t the chart I thought it was. Sorry about that…they looked the same.

waxis

(For the record, after an extended period of indolence, on Thursday I went for a run; on Friday I went for a run before putting on any other shoes first; on Saturday I went for a run and then later put on different shoes to go to a cocktail party.)

Is it too much to ask that people seeking to insult the British voters at least put some effort into their attempt? Ignore for a moment the simple fact that we don’t know who was searching this – it might well have been the people who voted to Remain, after all – and so the story line that the people who voted Leave were just morons gets no support from this chart. It also turns out that this was the second-most-searched term only for one small time segment: early in the morning after the vote. By 5am it was eclipsed by questions about the weather. Oh my – it seems the Britons also don’t know what weather is! Also, as the Telegraph’s skeptical story (linked above) points out, the raw number of people asking the question was only on the order of 1,000 – it was just a massive increase since it hadn’t been previously asked very much. This is where not having axes matters…it turns out this is a non-story, and nonsense.

Another piece of nonsense I want to point out is more general. I have seen several Twitter polls and other polls in something like this form:

Q: What effect do you think that Brexit will have on the global economy?

a) Deeply contractionary

b) Moderately contractionary

c) Somewhat contractionary

d) Expansionary

Now this is nonsense because the actual result not only has nothing to do with opinion, it’s not even clear why we would care about people’s opinion in this case (unless we are trying to show how pervasive the negative news stories are, or something). Polls work comparatively well when there is not a lot of information inequality – for example, when each person is asked about his or her own vote. But the poll above is analogous to this poll:

I submit that only me, and my valet, have the information sought by this poll; all other respondents have zero information. Therefore…what’s the value of the poll? Unless I or my valet are respondents, precisely zero; if we are, then the value is inverse to the number of other respondents diluting the response of the people who know.

Similarly, there is likely some information asymmetry among respondents to the poll about the effect of Brexit on the global economy. I would respectfully suggest that most people who are responding are saying what they have heard, or what they fear, or what they hope, while some people – macroeconomists, for example – might have actual models. To be sure, those models are probably only slightly better than the fearful and hopeful assumptions put into them, but the point is that this poll is nonsense in the same way that polling people about what they expect inflation next year to be is nonsense. The vast majority of respondents have no way to evaluate the question in a structured way, so what you are capturing is no more and no less than what people are worried about, which is itself just a reflection of what they’re seeing and hearing…for example, on Twitter.

(For what it’s worth, I think that thanks to the weakening of sterling Brexit is likely to be mildly stimulative to the UK economy, as well as somewhat inflationary, and slightly contractionary and disinflationary to the rest of the world. But the question about global effects is a trick question. Obviously, global production and consumption are unlikely to change much in real terms just due to the arrangement of trade flows. More friction in the system to the extent that Europe puts up significant trade barriers against the UK – something I don’t view as terribly likely – will lower global output slightly and raise global prices.)

These flash polls and Google trends data are part and parcel of the Twitterization of discourse. They have in common the fact that they can be snapshot and draw eyeballs and clicks, whether or not there is any content to the observations. In these cases, and in many others, there isn’t.

Here’s a thought: why don’t we wait a few months, or better yet a few years, before we judge the impact of Brexit? Sometimes, having actual data is even better than a Twitter poll.

Categories: Analogy, Europe, Good One, Rant, UK

The Most Crowded Trade

Wise investors hate crowded trades. Good, high-alpha trades tend to be out-of-consensus and uncomfortable. Bad trades tend to be ones that everyone wants to talk about at the cocktail party. Think “Internet bubble.” That doesn’t mean that you can’t make money going along with a consensus trade, at least for a while; what it means is that exiting from a consensus trade can be very difficult if you wait too long, because you have a bunch of people wanting to go the same direction as you.

So what is the most crowded trade? In my mind, it has got to be the bet that inflation will remain low and stable for the foreseeable future.

This is a very crowded trade almost by default. If you want to be long momentum stocks and short value stocks, and no one else is doing it, then it can get crowded but this takes some time to happen. Other investors must elect to put on the factor risk the same way as you do.

But the inflation trade doesn’t work that way. When you are born, you are not born with equity risk. But you are born with inflation exposure. Virtually everyone has inflation risk naturally, unless they actively work to reduce their inflation exposure. So, from the day of your birth, you have a default bet on against inflation. If there is no inflation, you’ll do better than if there is inflation.

It’s a consequence of living in a nominal world. And the popularity of this bet at the moment is a consequence of having “won” that bet for more than three decades. Think for a minute. When you find someone who thinks that inflation is headed higher – and let’s cull from our sample all the nut-jobs who think hyperinflation is imminent – what is “higher” to them? When I tell people that our forecast is for 3% median inflation by year-end, they look at me like I’m from Mars, like three percent is so unfathomably exotic that they can’t imagine it. Because, for the most part, they can’t.

This month marks a full twenty years since the last time that year/year core inflation exceeded 3%. Sophomores in college right now have never seen 3% core inflation. (Median inflation has gotten somewhat higher, up to 3.34% in 2007, but hasn’t been higher than that since 1992). So truly, for many US investors 3% inflation is exotic, and 4% inflation is virtually hyperinflation as far as they are concerned.

So this is a very crowded trade. And this crowded trade is expressed in numerous ways:

  • Bonds of course do very poorly in inflationary outcomes. Floating rate bonds do slightly better. Inflation-linked bonds do the best. And inflation-linked bonds, while richer now than they were, are still vastly preferable to nominal bonds in a real risk sense and still quite cheap in an expected-return sense.
  • Equities do poorly in inflationary times. While earnings tend to keep up with inflation, the P/E multiple is usually at a maximum when inflation is between 1% and 2% and tends to decline – severely – when inflation moves out of the butter zone.
  • While Social Security has a cost-of-living adjustment, very few private pensions do. Some annuities have “inflation adjustment” features, but with very few exceptions these are fixed escalators and not sensitive to inflation at all. There really aren’t any inflation-linked annuities to speak of.
  • What about the structure of our workforce? Unions tend to be stronger in inflationary periods because it is during these times that their power (as monopolists in the local labor market) to keep wages moving up with the cost of living is deemed more valuable by potential union members. The chart below is from a presentation I made several years ago.

unionization

There are many other examples; most of the ways we express this trade are unconscious since we are so accustomed to living with low inflation that we don’t give our default choice – to face down the possibility of inflation while hedgeless – a second thought. This is, without a doubt, the most crowded trade. And why should investors care? Investors should care for the same reason you want to avoid all crowded trades: when it is time to exit the trade – which in this case means buying commodities, buying inflation-linked bonds, buying other real assets, selling nominal bonds and equities, pressuring futures markets to offer hedging tools (such as CPI futures), borrowing at low fixed rates for long tenors, and so on – investors may find that it is very hard to do at levels they once considered a God-given right. Or in the sizes they want.

Some readers may note that this is the “Most Crowded Trade,” while I just wrote a book about the “Biggest Bubble of All.” Why don’t I just call the “inflation stability trade” the “biggest bubble?” The difference is in emphasis. A crowded trade can be crowded even if it isn’t a bubble (although a bubble also tends to be crowded), and it is no less problematic for not being a bubble. The fact that it is a crowded trade just means that the door to escape is smaller than the crowd that may need to pass through it. In this case, the crowd consists of almost everyone on the planet, aside from the tiny cadre of people who have hedged to some meaningful degree. But it is possible that the trade never has a forced-unwind, a panicky run for the exits. It is possible, although I deem it unlikely, that inflation may stay low and stable forever. And, if it does, then the crowded nature of the trade is no issue. But the trade is indeed crowded.

In the 1970s, investors could be forgiven for not hedging their natural “I was born this way” inflation exposure. There weren’t many ways to do so. One could buy gold, but when the client asked what else the investment manager had done to immunize their outcomes against inflation he could shrug and say “what else could I do?” But this isn’t the case any longer. Investors who want to hedge explicitly against the risk they have implicitly been betting on all along have many options to do so. And, in a low-return world, they don’t even have to give up much in the way of opportunity cost to do so. For now.

So if the crowded trade unwinds…what will managers tell their clients this time?

Categories: Analogy, Investing
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