The Limits to Trusting the Robots

October 20, 2017 Leave a 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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Summary of My Post-CPI Tweets (Oct 2017)

October 13, 2017 Leave a comment

Below is a summary of my post-CPI tweets. You can (and should!) follow me @inflation_guyPV or sign up for email updates to my occasional articles here. Investors with interests in this area be sure to stop by Enduring Investments or Enduring Intellectual Properties. Plus…buy my book about money and inflation. The title of the book is What’s Wrong with Money? The Biggest Bubble of All; order from Amazon here or get it a little cheaper on our site here.

  • Friday the 13th and a heavy data day. What could go wrong?
  • 10y breakevens at local highs of 1.90% – but that’s the biggest spread over core CPI in several years.
  • …yet we still have 10y TIPS 50bps to fair at this level of interest rates.
  • Economist expectations are for 0.21% on core and 1.78% y/y. Interesting given how low it has been recently.
  • I don’t usually look at headline but the y/y number is forecast to jump to 2.3% from 1.9%. That will get some attention.
  • I think the market forecasts are about right for core, but there’s a wide range of upside risks. Autos are due to catch up, e.g.
  • But that’s why the forecasts make sense. 0.15% for trend plus 0.05% for expected value of risks.
  • …in turn, that means the point forecasts are not the most likely prints. They’re in between the most likely prints.
  • Core +0.13%, 1.69% y/y.
  • Breakdown will be interesting. Housing broad category went to 2.79% y/y from 2.91%. Medical Care fell to 1.56% from 1.81%.
  • Used cars/trucks went to -3.7% vs -3.8% y/y, so that rebound is still ahead of us. Surveys of car prices are up a lot, just not in BLS yet.
  • pulling in the breakdown now…core services 2.6% from 2.5%, but core goods deflation deepens to -1.0% from -0.9%.
  • Core goods deflation, however, ought soon to be rising again after the lagged effect of the dollar’s decline passes in.
  • In Housing, Primary Rents plunged to 3.78% from 3.88%. That’s huge. OER dropped to 3.18% from 3.27%. Also huge. There’s your story.
  • Core ex-housing rose to 0.58% vs 0.52% y/y, so there’s more going on here but the housing. Wow.
  • A few months ago we had y/y OER fall by more, but that was when OER was overextended.
  • Here is primary rents y/y. I guess this isn’t DRAMATIC – just quite contrary to my own expectations for a continuation of the rebound.

  • In Medical Care, Medicinal Drugs fell to 1.01% from 2.51%. Wow! But Professional Services and Hospital Services accelerated slightly.
  • Here’s CPI for pharma. Think we’ve discussed this before – likely compositional in nature, more generics thanks to worse insurance.

  • Professional services (doctors) bounced;not significant. Also somewhat compositional as old doctors quit rather than take ins. headaches.

  • College Tuition 2.08% vs 1.89%. Have I mentioned the new S&P Target Tuition Inflation Index recently? 🙂
  • Just b/c …who can get enough of wireless telecom services? Bounced, mostly base effect of course. Bottom line was that dip was a 1-off.

  • New cars also still deflating, BTW. -1.0% vs -0.68%. Obviously this will change with Houston buying loads of new cars.
  • Speaking of Houston: core CPI in Houston y/y ended June: 1.31%. For y/y ended Aug: 1.90%. But that’s actually before Harvey.
  • In Miami, 2.01% vs. 2.26% (June vs August). Have to wait a bit to get October numbers – they’ll come out in Dec.
  • Bottom line on the storms is that we haven’t seen the impact yet on CPI. Still to come.
  • My early estimate of Median CPI is 0.20%, bringing y/y up to 2.17% from 2.15%.
  • Housing and Medical Care still keeping pressure on core.

  • Interestingly, these other categories, including Food, and Energy too, all saw acceleration this month (except for other).

  • distribution of changes getting more spread out…

  • Percentage of basket over 3% hasn’t changed much, ergo median didn’t change much.

  • Does this change the Fed’s calculus? I don’t think so, especially with wages accelerating. Still waiting for one-offs to unwind.
  • The doves will argue that the unwind of a one-off is itself a one-off and we should therefore look thru and see 0.12-0.14 as the trend.
  • They’re unlikely to carry the day in Dec, even if the data don’t bounce higher. But if core stays weak the mkt will unwind the 3 in 2018.
  • 10y breakevens -3bps since the number. Market had seemed a little long but this is still too low for breakevens.
  • Four pieces. Piece 1: Food & Energy

  • Piece 2: core goods. Won’t go down forever with the dollar well off its highs.

  • Core services less ROS. A bounce. Sustainable? We’ll have to see.

  • Piece 4, Rent of Shelter. Seemingly ignoring continued rise in home prices. Back to model but weaker than I expected.

  • Last chart. here is the argument: do we cheer the weak consumer inflation or worry about higher wages?

  • Yes, wages follow inflation rather than lead…but the Fed doesn’t believe that.

Thanks to everyone who followed my new “premium” (but cheap) channel. I wrote on Wednesday about the reason for changing my Tweet storm; in a nutshell, it’s because research is starting to be priced a la carte at the major dealers and hopefully this means that quality but off-Street analysis might finally be competing on an even footing rather than competing with “free.” If you think there’s value in what I do, I’d appreciate a follow. If not…well, if the market tells me that what I’m producing isn’t worth anything, then I’ll stop producing it of course!

But in the meantime, here is the story of CPI this month. A continuing regression of rents and OER to model levels held core down to recent-trend levels. But there are many one-off and temporary effects that are due to be reversed, and relationships that suggest certain components are due to catch up to underlying realities. For example, here is the picture of Used Cars and Trucks CPI, compared to the Manheim Used Vehicle Value Index 4 months prior.

According to the relationship between these series over the last decade, CPI for Used Cars and Trucks should be growing about 5% faster than it is presently, and rise another 3-4% in the next few months. New and Used Motor Vehicles inflation is about 8% of core CPI, so this effect alone could add 0.7% to core CPI! Or, put another way, right now core CPI is about 0.4% lower than it would be if the CPI was measuring the actual price of vehicles the same way that Manheim does it. That’s a big number when the entire core CPI is only 1.7%.

The continued, and actually extended weakness in core goods is also due to reverse. I don’t mean that core goods inflation will go from -1% to +3% but only to 0.5%. But that 150bp acceleration, in one-quarter of the core CPI, would also raise core CPI by 40bps or so. To be sure, there is some double-counting since a third of core commodities is new and used vehicles, but that merely reinforces the message.

So, too, are the effects in medical. Volatility in those series should persist, which means that since they are at a low ebb there’s a better bet that the next volatile swing is to higher prices.

All of which is to say that the hawks on the Federal Reserve Board actually have it right, in a sense. Prices are headed higher, and inflation is accelerating. It would be a truly shocking development if core inflation one year from now was unchanged from the current level. Indeed, I think there is a better chance that core inflation is above 2.7% than below 1.7%. On another level, the hawks aren’t quite right though. By hiking rates before draining excess reserves, the Fed risks kicking off the vicious cycle I have mentioned before: higher rates cause higher money velocity, which causes higher inflation, which causes higher rates etc. Without control of reserves at the margin, the Fed cannot control money supply growth and so the normal offset to rising monetary velocity in a tightening cycle, slowing money growth, comes down to chance. Either way, the Fed is very likely to tighten in December, but beyond that it probably matters more who ends up in the Chairman’s seat than anything economic data.

The Changing Face of Free Stuff

October 11, 2017 5 comments

Today’s article isn’t about inflation, or the bond market, or the Federal Reserve. It is more of a meta-article: an article about articles or, more precisely, research.

I started my career as a technical and quantitative analyst back when we were still doing point-and-figure charting on large sheets of graph paper tacked to the wall. After coming to Wall Street in the early 1990s, I went to JP Morgan in 1994 as a futures researcher. Subsequently, I became the lead US fixed-income researcher at Bankers Trust before gradually parlaying my research skills into a trading position at Barclays.[1]

In those years, and really until now, compensation of researchers was pretty reasonable. While few researchers – especially in fixed-income – earn seven-figure compensation packages, they still earn an awfully nice living and get to go home at night and not worry about whether their short options position is blowing up in Japan while they sleep. Researchers in general don’t need to wake up at 2am to talk to Hong Kong and delta-hedge the book.

However, there is a downside to being a researcher and that is that historically there hasn’t been a very good connection between the quality of the research (and the eyeballs it commands) and the bonus at the end of the year. On Wall Street, if you don’t have a P&L attached to your name then you don’t have much ammunition when it comes to the bonus discussion. If you can point to a trade that you recommended, the sales force sold, and the trading desk profited from (as well as, hopefully, the clients…since if the clients don’t profit they don’t listen to your next recommendation), and you can compute how much money you made the desk; or if you can claim responsibility for a bond tip that happened as a customer reward for help you gave them on some other matter; or you are a “star” analyst who is the “axe” on some company or market and clients clearly give the firm business so as to have access to you (this is more likely to be the case at a small shop that would otherwise not get such business), then you’re in good shape. But the vast majority of analysts have nothing to say when they sit down with management to discuss their bonuses, because the research bonus pool is essentially a gift from Sales & Trading and not an allocation from their own profits.

Enter the second chapter of the “Markets in Financial Instruments Directive,” aka MiFID II, a product of the European Securities and Markets Authority (ESMA).

I don’t claim to understand everything, or even very much, about MiFID II. I’ve spent a lot of time talking to people who understand more, but no one is really sure what the ultimate impact of MiFID II is going to be, just like no one was sure how bad Dodd-Frank would be for the financial markets. But I want to focus here on the impact of MiFID II on the provision of sell-side and, more to the point, independent research.

Part of MiFID II essentially requires broker-dealers (in Europe, but practically speaking it’s hard to ring fence a global B/D’s activities and clients to just one jurisdiction) to separate the fees for execution and for research. Previously, research – including access to research analysts, for good clients – was provided free to clients in almost all cases. The European regulator, observing that this meant that research must be an ancillary benefit to clients paid for by dealers from their trading profits, reasoned that bid/offer spreads must be wider than they would be if dealers didn’t have to bear this invisible charge.

It is a risible argument, even if it must technically be true. But no trader ever, I am sure, adjusted his bid/offer spread wider to cover the cost of research being provided. Traders think of the bid/offer as being a price for liquidity, period. So I would be shocked if the effort to split these charges resulted in (as is intended) lower trading costs for clients.

Anyway, the bottom line is that now if clients want to get research from their dealers they need to explicitly pay for it, and disclose to the clients what the client is being charged for the research. (We have vaguely similar rules here regarding how ‘soft dollars’ must be used and disclosed, but research that is “free” is not subject to that measurement and reporting.) And so dealers have been announcing what they will charge for research starting on January 1, 2018.

So here’s the interesting side-effect on independent research. Previously, it was virtually impossible for quality independent research providers to make a living. There are a very few who have succeeded at this – Bianco research, Medley, etc – but those numbers are small and those folks have been having a more difficult time of it in recent years. It’s really hard to compete with “free” research coming from the sell side. And so – to bring this home – people like me have had to give away content, hoping to someday recoup the cost of writing and researching by attracting more clients to other lines of business or to a paid research product. Honestly, I’ve tried ten different ways and haven’t figured it out, and I’m the only person I’m aware of with deep domain knowledge in inflation that’s putting out commentary or research.

MiFID II may change that. If buy-side institutions no longer get research for free from the Street, they may be more discerning about what they spend money on. Why pay dealer X for research that used to be free – and was worth about what you paid for it – when independent researcher Y is charging $100 for research that is twice as good? Buy side firms have been wrestling with this question, and there have also arisen several platforms for research providers to hawk their wares – Alpha Exchange, ERI-C, and RSRCHXchange, just to name three. In fact, my company is posting our research on those platforms as well, and in January we will see if anyone is willing to pay for it.

Here is where we make it really personal.

I never wanted to be a ‘blogger.’ I get value from the process of writing my thoughts down, and I get value from feedback from readers. Lots of value. But it takes a ton of time, and it’s hard to justify the time and effort to the fellow stakeholders in my company if there is no revenue attached, ever. And so over the years I have stopped allowing platforms to publish my articles (such as Seeking Alpha) if they weren’t willing to allow me to mention my company, for example; I have also gone from publishing daily (as I did for years) to once or twice per week.

I intend to continue to produce these articles, and distribute them freely on my blog (https://mikeashton.wordpress.com ), on Investing.com, Harvest, and TalkMarkets as well as other places where it is picked up from time to time. And I hope you like them. But my CPI-day tweets, and some other occasional content, will be moving to a new channel. You can go to PremoSocial and subscribe to get access to that “premium content” for only $10 per month. Here is the link.

You can help make sure that this column remains free, by subscribing to that channel. If you think my out-of-the-box viewpoint on markets and especially inflation is valuable, please consider signing up. If the response is very good, it may even justify my spending more time on the research-for-public-consumption (as opposed to R&D) part of the business, and writing more frequent articles. I am eager to see what the response is. Surely my work is worth more than zero. Anyway, I hope so.

Thanks in advance!

[1] I don’t recommend that path for any new graduate starting off on Wall Street. It is quite hard to get from the research desk to a risk-taking role and I got lucky.

The Mystery of Why There’s A Mystery

October 10, 2017 Leave a comment

We have an interesting week ahead, at least for an inflation guy.

Of course, the CPI statistics (released this Friday) are always interesting but with all of the chatter about the “mystery” of inflation, it should draw more than the usual level of attention. That’s especially true since the mystery will cease to be a mystery fairly soon as even flawed indicators of inflation’s central tendency, such as the core CPI, turn back higher. This is not particularly good news for many pundits, who have declared the mystery to be solved with some explanation that implies inflation will stay low.

  • “Amazon effect”
  • Globalization
  • “competition”
  • Etc

The first of these I have addressed previously back in June (“The Internet Has Not Killed, and Will Not Kill, Inflation”). The second is a real effect, but it is a real effect whose effect peaked in the early 1990s and has been waning since then. I wrote something in our quarterly in Q4 last year, which is partly summarized here.

The “competition” objection is a weird one. It seems to posit that competition was pretty lame until recently, which is pretty strange. One argument along these lines is in this article by Steve Wunsch, who considers the increase in airline fees “stark evidence of a deflationary spiral in those ticket prices caused by antitrust-induced competition.” This is odd, since airlines were deregulated in 1978 and have in recent years become less competitive if anything with the mergers of Delta/Northwest in 2009, United/Continental in 2010, Southwest/AirTran in 2011, and US Airways/American Airlines in 2013. A flaccid antitrust response from the Justice Department has allowed quasi-monopolies to develop in some travel hubs, which has tended to push fares higher rather than lower. The chart below shows the relationship between Jet Fuel prices and the CPI for airfares (both seasonally adjusted) for the 20 years ended in 2014, along with the most-recent point from last month.

The highly-explanatory R-squared of 0.81 suggests that there is not much wiggle room in airline pricing. Airfares are, as you would expect under a competitive industry, roughly cost-plus with the main source of variance being jet fuel prices. This is true even though we would expect that spread to vary over time. As Mr. Wunsch would argue, the highly competitive nature of the industry is holding down the non-commodity price pressures in airfares.

The only problem is that if you extend this graph to include the last three years, the R-squared drops about 10 points:

In case it isn’t clear from that chart, the last three years have seen airfares increasingly above what we would expect from the level of jet fuel prices. The next chart makes that clear I hope by plotting the residual (and 12-month moving average to smooth out seasonal issues such as one that evidently happened last month) between the actual CPI-airfare and the level that would be predicted from the 1994-2014 relationship. As you can see, prices have been higher, and increasingly so, than we would have thought, until this last month or two – and I wouldn’t grab a lot of comfort from that yet.

Not only is this not “stark evidence of a deflationary spiral in those ticket prices caused by antitrust-induced competition,” it seems to be stark evidence of inflation in ticket prices caused by a reduction in competition thanks to airline mergers.

In reading these many articles, it always is somewhat striking to me: everybody thinks their answer is “the” answer to the mystery. But most of these authors really don’t sufficiently understand how inflation works, and what the data is showing. This is apparent to those who do understand these nuances, as an author might discuss (as the one mentioned above did) an “aberration” in cell phone inflation as if the experts are stupid for expecting inflation when cell phone services only go down. The author clearly misunderstands what the “aberration” referred to even is; in this case the aberration was an enormous one-month collapse in prices that had never been seen and has not been repeated since. (For those who are curious about the aberration, and why it occurred, and why it is likely a methodology issue rather than sign of spiraling deflation in wireless services you can see my discussion of it here.)

The mystery is simple – the Fed’s models don’t work, and don’t take into account the fact that lower interest rates cause lower money velocity. They rely on a Phillips Curve effect that they think is broken because they don’t understand that the Phillips Curve relates wages and unemployment, not consumer prices and unemployment. They focus on a flawed measure like PCE rather than on something like Median CPI which, coincidentally, is a lot higher and suggests more price pressures. The mystery isn’t why inflation isn’t rising yet – the mystery is why they think there’s a mystery.

Gold and TIPS – Related or Not?

September 27, 2017 4 comments

Because I spend so much time digging into inflation data and learning about how inflation works (and how securities and markets work, in different inflation regimes), I am always delighted when I come across something new, especially something simple and new that I could have previously stumbled on, but didn’t.

Recently, a friend sent me a link to an article by Scott Grannis (aka Calafia Beach Pundit). I occasionally read Scott’s stuff, and find it to be good quality. I’m not writing this article to either criticize or support most of his column, but rather to point to one particular chart he ran that amazed me. Specifically, he showed the 5-year TIPS yield against the nominal price of gold. Here is his chart:

He also showed the price of gold versus TIPS on a longer-term basis. I’ve replicated that here, although I’ve deflated gold by the CPI since the longer the time frame, the less the nominal price of gold will resemble its real price. It’s still basically the same picture:

This is an amazing chart, even allowing for the divergence in the 2000s (which some people would call prima facie evidence that the Fed eased too much back then). And it just tickles me because I’ve never noticed the correlation at all, and yet it’s really quite good. But here’s the really amazing part: there is no immediately obvious reason these two series should be related at all.

One of them is a price index. In Scott’s version, which isn’t adjusted for inflation, it should march upward to the right forever as long as the general price level continues to rise. Obviously, real yields will not march ever lower forever. When we adjust for the general level of prices, the real price of gold should, like real yields, oscillate (since the long-term real return to gold is approximately zero) so we have removed the tendency for nominal prices (unlike yields) to have a natural drift. But even in real terms, apples-to-apples, it’s an astonishing chart. What this chart seems to say is that when expected growth is poor, gold is worth more and when expected growth is strong, gold is less valuable. But that seems a bit crazy to me.

Okay, one possible interpretation is this: when expected returns from other asset classes such as stocks and bonds and inflation-linked bonds are low, then the expected return from gold should also be low, which means its price should be high. That makes sense, although it is hard to find many gold investors who think as I do that the expected forward-looking real return to gold right now is negative. Heck, I wrote about that last month (see “The Gold Price is Not ‘Too Low’”). It makes some sense, though. But the implication is that as inflation rises, and yields – both real and nominal – rise, then gold prices should fall. I think you’d discover it difficult to find an investor in gold who would think the gold price should fall if inflation picks up!

Where you would think to see more of a relationship is in inflation expectations versus gold. When inflation expectations are high, you’d think you would see gold prices high and vice-versa. But that chart has really nothing suggestive at all, possibly since inflation expectations have really been fairly grounded for the last twenty years. Gold prices, however, have not!

So going back to the original Grannis chart, I am still very suspicious. Fortunately, some time ago we developed a very long history of real interest rates, using a more advanced approach than had previously been applied (you can see the long-term series in this article). That series is derived, rather than observed as the TIPS series is, but it’s probably pretty close to where TIPS yields might have traded had they existed during that period. And when we look at real gold prices versus 5y TIPS yields…

…we get a pretty disappointing chart. What I see is that in the 1970s and early 1980s, high gold prices were associated with high real yields; in the 2000s and 2010s, a high gold price was associated with low real yields.

So, this is a bit of a bummer in one sense but a relief in another sense. That initial chart suggested some very weird dynamics happening between real yields, inflation expectations, and the price of a real commodity. I think this latter chart indicates that the relationship we saw was not some fundamental previously-undiscovered truth – sadly, I guess – but rather something more prosaic: an illustration of how the relative values of all assets tend to move more or less together. TIPS are expensive. Bonds are expensive. Stocks are expensive. Gold is expensive. Unfortunately, I don’t think that tells us a lot that we didn’t already know (although I have strong opinions about the relative ordering of the richness/cheapness of those asset classes).

Categories: Commodities, Gold, TIPS

Targeting Tuition as a Long Run Goal

September 21, 2017 2 comments

A few months ago, in a couple of articles entitled “The Bias in Investor Perceptions” and “What’s Wrong With the Long Run?”, I started to lay out the case for individuals and family offices to approach the investment challenge like a well-run pension fund or endowment would. Most well-run pensions and endowments these days are run in a “liability-driven” manner, which means that instead of maximizing the performance of the fund’s assets, subject to the risk of those assets – classic “mean variance optimization” based on “Modern Portfolio Theory” – the manager aims to maximize the funded status of the plan subject to the variance in the funded status. That is, the manager recognizes that having assets which mimic the behavior of the liabilities is valuable and worth at least some sacrifice in expected return. Many such portfolios, especially when they are fully funded, have two “buckets” for assets, one that is designated as the “liability immunizing” portfolio and one that is designated the “return-seeking” portfolio.

The reason this is a valuable mode of thought for an individual or family office is that it tends to force a focus on the long run, since the “liabilities” in question (such as retirement, college education, bequests, etc) tend to be long-term in nature. But there are a couple of challenges.

One such challenge is to get the client to focus on that long run, rather than on the brokerage statement that shows up in the mail every month and is always one mouse-click away. And that’s what I discussed/lamented on in those prior two articles.

The other challenge is that, unlike a pension fund or endowment, an individual has a kaleidoscope of different liabilities that behave differently from each other. Some of these, like saving for retirement, can be approximated by general consumer price inflation (CPI). But some, like saving for college or saving for future health care costs, behave in their own unique ways. And so the conundrum for many years has been “sure, personal Liability-Driven-Investing makes sense, but what assets do I hold against those liabilities?”

This has driven calls for “goal-appropriate financial instruments,” led by people like Arun Muralidhar (who specifically used that term in “Goals Based Investing, the KISS Principle, and the Case for New Financial Instruments”) and Robert Shiller, who muses on making “previously untradable risks tradable” in Finance and the Good Society, and has a history of innovative enterprises to attempt the same.

What I am excited about is a step forward in creating these instruments…one that my company Enduring Intellectual Properties has had a key role in. Last week, S&P Dow Jones Indices announced the launch of the “S&P Target Tuition Inflation Index,” which is designed to reflect inflation of college tuition and fees over long-term periods. The index was designed by S&P on the basis of a method that we developed a very long time ago but could never figure out how to commercialize. It involves liquid securities, and so can easily be made into investible products such as mutual funds, ETFs, UITs, and other structured products that individual investors can buy. The chart below shows the index, alongside CPI for College Tuition and Fees (NSA).

As with any liquid markets-based index compared to a periodic economic indicator, the tracking error on a day to day basis is not necessarily good. But it is also not terribly relevant – how your fund does next week should not affect how you feel about your college fund! The strategy is built on an understanding of what the main drivers of college tuition are, and these turn out to be fairly simple (unlike is the case with, say, Medical Care). Because the main drivers of college tuition inflation are the same as the drivers of the index, the errors tend to be “mean-reverting,” meaning that the longer you hold the index the closer (in annualized terms) you tend to be to the target.

Investing in a product linked to this index will not be a substitute for saving money in the first place. But, having saved, investing in such a product should help to reduce the risk that the money saved for college suddenly evaporates, as it did for many parents in 2000-2002 and 2007-2009.

I am ecstatic that we were able to team up with S&P to create such an important index – one that will help investors save in a goal-driven way, with their eyes turned to the future rather than to the latest wiggle in the markets.

Money and Credit Growth Update

September 19, 2017 Leave a comment

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It has been a challenging few years to be a monetarist. That isn’t because monetarist predictions have failed, but rather because monetarists have had to spend a lot of time explaining why money velocity has been declining (the answer is: low interest rates) and why “printing money” hasn’t led to runaway inflation (the answer is: inert reserves don’t count, but M2 money growth has been growing between 5%-8% for the last 5 years and that would be too fast for stable prices if velocity was stable).

Money velocity declines when interest rates decline because the demand for real cash balances increases when the opportunity cost of those cash balances is low. That is, if interest rates are at 10%, then you won’t leave cash sitting around idle; it becomes a hot-potato and either gets reinvested in term loans or other assets, or spent. On the other hand if term interest rates are at 0%, then what’s the hurry? The chart below (source: Bloomberg) shows the simple relationship since the early 1990s between 5-year Treasury rates and M2 velocity. This is not a mystery – it has been a critical part of monetarist theory since the 1970s.

You can see that there is a modest conundrum, since interest rates bottomed a couple of years ago but money velocity has continued to sag. I don’t see this as a major mystery; it makes sense to me that there could be some nonlinearities in this relationship near and below the 0% level that we just don’t have enough data to resolve. These nonlinearities have certainly made forecasting more difficult and led generally to forecasts that were modestly too high compared with actual inflation outturns. Again, there’s no mystery about why the forecast misses – the mystery is why money velocity has remained low while interest rates have bounced (we believe economic policy uncertainty has led people to hold somewhat higher real cash balances than they otherwise would, but that’s just a hypothesis). At some point, higher interest rates will snap money velocity back as it gets too ‘expensive’ to leave cash balances sitting around. But this hasn’t happened yet.

Meanwhile, money growth has been slowing. It is still rising faster than 5% per annum, which means that if money velocity was stable and potential GDP growth is 2.5% then we would see the GDP Deflator rising at 2.5%. So money growth is still a bit too fast, unless money velocity is going to decline forever. But it is better at 5% than at 8%, to be sure.

Credit growth has also been slowing, as the chart below (source: Federal Reserve) shows.

Now, regardless of what you read credit growth has essentially no relation to money velocity. Obviously, credit growth has been fairly rapid – as money velocity continued to sag – and is now slowing – as money velocity has continued to sag. It is moderately better connected to M2 growth, so it tends to reinforce the notion that money growth is slowing somewhat, but people who are saying that velocity will continue to slow because banks are slowing loan growth need to explain why rapid growth didn’t lead to velocity acceleration. One-way relationships in economics are pretty rare.

I doubt very seriously that M2 growth is about to drop off a cliff. The Fed’s rate hikes and any balance sheet reduction is not going to affect money supply growth while bank reserves are still “abundant,” to use the Fed’s phrase. Banks are neither capital nor reserve-constrained at the moment, so a decline in credit growth is either coming from the supply side as banks voluntarily reduce loan growth perhaps because credit quality is diminishing, or it is demand side as borrowers are not seeing the growth opportunities that require financing. Money growth is still, and always, something to keep an eye on. But, just as changes in velocity dominated changes in money growth when velocity was falling, velocity changes will dominate changes in money growth when (if?) money velocity starts to rise. As the first chart above shows, velocity when interest rates were “normal” was around 1.8 or higher. I invite you to go to the calculator on the Enduring Investments website and play around using a starting money velocity of 1.43 to see what sort of money supply contraction is required to keep inflation low, if velocity returns to 1.80 over some period of time.

And then, realize that M2 has not declined on a y/y basis as far back as the Fed has records on FRED (about 1960). It seems unlikely to do so now. This leaves few low-inflation exit paths as long as money velocity isn’t permanently dead.

I think the decline in credit growth has implications, but they are mainly implications for growth and not for inflation. Along with the weakness that is starting to be seen in some other areas of the economy (e.g. autos, until the hurricanes caused some “forced replacement”), I think this could be seen as a harbinger of a potential recession in 2018.

Categories: Causes of Inflation Tags: ,
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