The RH traders and the Treasury

The diverging positions of RH traders and bankruptcy financiers, in the end, is a difference in outlook: the distinction between, say, the letters V and L. The former signifies a sharp and expeditious economic bounce after an artificial short-lived stoppage that did nothing to the business fundamentals; the latter is a slower drift, where the asset value remains permanently damaged.

It is conceivable that if the broader funding market were to see the future the same way the RH traders seem to, at least implicitly, the bankruptcy scenario – its valuation exercise, its ranks and splits, perhaps even its timing – would be different. In this scenario, perhaps, the scope of the proceeding would be more mechanical in nature than financial; in other words, a short bridge to protect the company for some missed near-term payments. Until the rapid rebound that’s in this scenario expected.

In essence, the described position is similar to federal stimulus initiatives enacted at the outset of the economic lockdown. The PPP loan structure, for instance, intended to preserve small business payrolls with a short-term bridge to the V-recovery’s other side, the unemployment benefit boost set to expire a few months after implementation, the 90-day tax extension to mid-July, are all predicated on a quick economic bounce and return to “normalcy”.

In this sense, the RH traders and the Treasury department are more or less the same, although the latter holds more weight (because sophistication). In truth there is no way to really know, at least not yet, whether the V or L, or other shapes and letters that are kicked around, will be upcoming reality. But where the RH traders might reverse their bets at any time with ease and at a relatively small potential loss, all things considered, the federal institutions may not be as nimble or inconsequential.

So far at least, both seem well set and almost stubborn in their opening positions. Let’s hope that they are right, for our collective sakes and theirs.

In the world of guesses

It’s in a way convenient to point to Hertz day traders and lol, or smh if your mood tends to the reflective. The phenomenon of a bankrupt company’s common stock surging in value, out of nowhere and for no good reason, is unheard of. Clearly, it is said, a company is in bankruptcy to begin with because it can’t support financial obligations, and thus the value of these ranking liabilities is written down, while the deeply subordinated equity layer is left worthless. If there is any worth at all for common stock, it’s some tiny option value; and tiny for good reason, it is said, because it’s only in the mind of hopeful and imaginative gamblers. When that value surges, the gamblers have lost their collective mind. Or, so it goes.

The reflectives and the laughers are, from a financially educated and market knowledgable point of view, correct. Especially when history is taken in consideration. But, just for kicks (in keeping with the subject), it’s interesting to think about a world where the event makes sense. What if, in such a world, minds haven’t been lost, option value hasn’t been distorted, financial obligations don’t get written down, the market is as it ever was, and there is nothing strange about Herz or its day traders? A wonderful and fascinating world: admittedly, a speculative fiction, per the masthead.

In this world, all value is predicated on financial outlook, a perspective of the future that gets discounted to time present; and, since perspectives vary, the market clears at some point of common ground. There is give and take, there is supply and demand, but, in this world it’s recognized and factored into calculations that, really and if one is being honest, it’s all a guess, no matter how educated.

In this same world, when the estimated value of the asset dips below its corresponding liabilities, this is an indication that the collective market guess has caused it to be so. Just as a short-term dip in earnings (or even a continuing multi-year series of financial losses) may not matter to the long-term value of a stock because the market guesses a bright future, so in bankruptcy the market guesses a future less bright, and takes corrective action. In this world, the difference between the first and second case is merely one of the accepted guess and the degree of its acceptance.

Sometimes, additionally, there are in this world cases of circularity. The more the commonly accepted guess prevails, the more it becomes self-fulfilling. They call it reflexivity in this world, where there are countless instances of market guesses driving capital access (in either direction), which in turn contributes to the guess’s plausibility.

Finally, it sometimes happens in this world that very large disturbances of questionable precedent will cause the markets to guess wildly. The turbulence, in such a world, serves to increase option value, as possibilities get magnified when almost anything is possible. Sometimes letters get assigned to various shapes of future outcome – V, U, L, W, M, and even K, it is said – the growing alphabet of which only draws attention to the assortment in the rich bouquet of guesses and their almost equal probability.

It would seem absurd, in such a world, although it has been known to happen, for one group to treat another with righteous indignation about the nature of its guess…

All things considered, that would seem even more absurd than the guess itself, and its multitude of consequences…

Security, conservation, defense

It’s in a way symbolic that the proposed Uber acquisition of Grubhub has left its target to Just Eat Takeaway instead. If Uber stands for the conveniently mobile and spontaneous ways of an outgoing urban environment, the meal delivery businesses of both Grubhub and its new strategic partner stand for something more reluctant and withdrawn.


The segment’s other dominant competitor, DoorDash, is in the meanwhile securing a market vote of confidence of its own… which is also symbolic.

The Information

While much of the crystal ball viewership is homing in on remoteness as the new wave (including the symbolic market moves described)… remote learning, remote work, remote health, and so on…


… perhaps there is a bigger and more interesting theme in the making, something to do with security, conservation, and defense at a more general level. It’s in any case a theme worth watching.


Competing spirals

It’s probably too soon to tell, but maybe we’re about to enter a deflationary spiral. The low and falling costs and pricing of the digitizing world had for a long time contributed to the pressure – a driver of stubbornly low inflation overall – even as certain categories in certain parts have seemed like outliers to the trend at certain times. A spiral, though, is something different.

In this, spending and investment get defensively pulled back, causing demand to fall and thus also prices, which leads businesses and consumers to wait in anticipation of further declines and to hoard cash in the meanwhile. In a falling price/demand environment, the buying power of money increases over time. You wait for the next sale, you wait for the free trial, you wait for the higher yield and in the meantime… you buy stocks?

Perhaps, and if liquidity permits (a big if) sure and why not. If cash gets piled up on the sidelines waiting for consumption, maybe there’s a case that one can reasonably make to chase the return potential. How much worse than zero can it be? The answer, in theory, is “a lot”, but if everyone at once piles in to form a counter-spiral up the other way?

WSJ Investors Get Ready for the Fed to Cap Rates

For now, perhaps, this may be what is happening already. And if the trend persists, there may be two competing spirals up ahead, both of which cash enabled… until the cash runs out, for some perhaps, because you can’t live on apps and stocks alone. But cash doesn’t run out at once for everyone. It’s only transferred, bridged, sometimes it’s assembled. There is no end to cash, not in the aggregate, and no end to imagination.

Strangers in a strange land

Maybe it’s a question of language. To communicate and transact, it’s a necessary exchange, a bridge even if between opposing viewpoints. And maybe the language of finance, rooted in earnings and cash and growth prospects and etc. and so on, is an arbitrary construct like any other.

Why not, for instance, evaluate an investment based on the number of squirrels climbing around the second nearest tree to where you are right now? No matter where you are, there is a second nearest tree, and if there are no squirrels, that’s only a factor in the calculation that the market builds a consensus around. If that’s the language that the market understands, is that not the definitive language and the basis of the valuation that matters? Who are we to judge if we don’t speak the language?

Here’s an example of a headline that is rooted in a different tongue, a culture where it’s been established since forever that common stockholders get wiped out in a bankruptcy restructuring, because the value of the asset and the cash flow on which this is based doesn’t support the asset’s financial obligations, and on the basis of this ingrained notion the words and phrases spill, the values are set, and the markets flow…


… until the language as though in a reset or a passage through a wormhole changes, and suddenly the headline observation makes no sense. What “massive risks”? Have you not seen the second nearest tree? It’s overwhelmed with squirrels, look, it’s in the data.

This question of language, I think, underlies the general distinction between fundamental and technical analysis. The fundamental practitioners tend to be language purists, if you will, with vocabulary, grammar and diction like Victorians at tea time. The technical analysts, on the other hand, with their charts and patterns and chaos drawn out like a map, are akin to machine learners that get trained to understand the sentences and unstructured data sets, hopefully.

When the two groups agree, that is not even fortunate, despite the harmony that might ensue, because there is limited opportunity then. There is no gap.

The opportunity arises when the language changes… especially for those who grok its meanings before others do.

This very rarely lasts, we think (we hope), until we finally relent and readapt. And right then, at that precise moment, the language again changes.

The pocket and the tech

Some of the best finance reading of 2019 was the S-1 filings for the year’s class of IPOs. It’s nice to see the 2020 editions start to surface, and just as there seemed to be a theme across the 2019 publications, so also 2020 seems to have a subject of its own, thus far.

If 2019 was the year of consumer marketplaces – Uber, Lyft, Peloton, Pinterest – this year’s product seems to go in the direction of tech-enabled resellers. (I am thinking about Lemonade and Vroom in particular, which have attracted some attention.)

There are some common elements and there are distinctions between the two categories. Stripping the business models down to their basic elements – data network effects and user network effects, which go together – I feel like where the marketplace scenario depends on the former in support of the latter, the reseller model does it in reverse. If the edge in the marketplace model is the community of buyers and sellers that is formed and the efficiency of the transaction that results, the edge in the reseller model is the efficiency of customer acquisition and the economic offload of the product to an incumbent vendor. If the marketplace model and its network effects result in a winner-takes-most competitive landscape determined by a naturally growing presence on both sides, the reseller model is perpetually competitive and dependent on continuous efficiency improvements.

Perhaps a good analogy to illustrate the difference is the telecom segment of the ’90s. The network infrastructure, which had taken decades and many dollars to build, was increasingly overlaid by certain CLECs, DSLs, ISPs, and other forms of resale where the underlying lines were used (with owner’s approval) to market to end-users more efficiently than the incumbent did, or to enhance the incumbent’s reach through what was effectively outsourced marketing. The economics were split based on contracts that defined the term and financial responsibilities of each, among other things, and in many of these cases the telecom was essentially rented out by the marketing organization. In a sense.

There is a risk that comes with that, for either side. For the deep-pocket incumbent, it’s that the marketer becomes the magnet and consumer-facing brand that over time may take over. For the marketer, it’s that the deep-pocket incumbent may at any time pull the plug. It’s a delicate balance in what is almost a frenemy equation, each side dependent on the other and thus distrustful with a warm smile on its face; each motivated to increase its self-reliance, as the efficiency of the incumbent and the capital access of the upstart both improve.

I’m thinking about these things as I read about the reinsurance model and its financial risks and benefits to the data-driven tech-enabled insurance startup…

Form S-1

… and the “asset-light” strategy of the used car operation.

Form S-1

It’s a race, just like before, to see which of the sides prevails, the deep and capital intensive pocket that might catch up with the tech, or the deep and data intensive tech that might start pocketing the capital.

A far-away view

Societies, geographies, industries, economies, and markets are complex network layers that interconnect to form a multidimensional structure on a global scale, infinitely more complex than its component layers. While each layer is dynamically shaped by micro-behavior at the individual node and cluster level, collectively all the layers macro-influence each other. The resulting global structure, in turn, has its impact on the pieces.

Historically, the difference was one of space and time, perhaps, where distances and limitations in both made for weaker ties within the mesh than is now the case. The change over the centuries has been observed by many to reflect an accelerating rhythm and impact of events, continuously amplified by the acceleration and the shortening of distances, which are inter-related.

If there is an analogy in all of this to a complex living organism, the complexity increases with the tools and remedies and side-effects. A shock is going to have consequences that are proportional to the shock, but with difficult to predict proportions.

The reopening of a major economy, in this light, is as mysterious as its closing.


Supported by data

One must be careful with statistics. One never knows what they are apt to say. Sometimes they say so many different things, it makes one’s head spin all around, trying to make sense of charts and tables and the endless data. I pity the robots and AIs, they really have their work cut out, it’s liable to make them crazy.

Here’s where I stumble on some reconciliation challenges, for instance. The fault is mine, no doubt, I haven’t seen the underlying calcs and metrics. And so I’m flying blind, or at least blurry eyed, like many of us far above the ground on autopilot.

Now, if my math is right, the big bars of this table add up to roughly 42 million (not counting the little bars immediately prior, which maybe didn’t find a job just as the big bars started)…


… so you would think that most of them, all things these days considered, have not been able to return to work so very swiftly, with the economy just barely out of lockdown, if at all. And then we have the following, which tells a different story still…


… which may imply that roughly half of 42+ million filers didn’t yet get approved by the system? It’s been a short time after all, and these things aren’t automatic. But even so, how is the dip from 25 to 21 explained while all the new claims bars remain so big and positive? I don’t know, maybe it’s the “seasonal adjustment”? Because it’s summertime, when the living is easy?

And then comes yesterday’s big headline, which sends another signal still… at the headline level at least, and, for purposes of zig-zagged pattern recognition in this post, especially the second little line with reference to millions…


Well alright then, there is a rise of 2.5, a corresponding change of 4 – to 21 from 25 – which differs from the 42 and counting… Again, it’s me, I know, I’m mindful of my limitations, I’m only as good as the headlines and the news reports (and probably much less), but honestly, it’s not for lack of trying.

Sometimes I even sift through all the details down below, here goes…

It looks like “goods producing” is the biggest beneficiary…
It looks like “construction” is the biggest item within “goods”…
And within “services” it seems that “leisure and hospitality” saw the biggest bounce (from an enormous trough, for what it’s worth)…

The problem though with all of the percentage charts is that these relate only to themselves, and so the detail is to some extent illusive; we still don’t know the impact of each sub-component on the total of the tens of millions… before digging further still, as some economists have tried.


I don’t know, I just don’t know… but take some solace in the notion that the market does. We’re in a bull market! Clearly.

Jason Zweig on market haves and have-nots, supported by data.