300 posts

I started to jot down my morning notes 300 days ago. It was right after Labor Day, when the world is energized and set to blossom. I didn’t know what I would write about, although I set myself some ground rules in the masthead, to limit the endlessly potential subject matter with enough diversity to keep it interesting. The interest was mainly for my own part, to be honest, which is to say, I used the vehicle to take notes, to learn, to force myself to think about the meaning(s) of events and patterns that I saw or lived or read about.

It started brief and barely richer than a tweet in the initial weeks. Like this one here, for instance, The miracle of blocks, from a Boulder hotel room; and this other the next day, The bridge, hanging at the Denver airport. As time went on, and somewhat to my own chagrin, the posts got longer and more verbose; in part, I guess, because I felt encouraged by a growing readership, in part because I got more comfortable with my posting voice, but also, to be fair, because the world became more complicated and amazing into the new year and after.

So, lately, what started as a series of brief morning notes has turned into a daily blog of standard form and length (e.g., Convergence, platforms and new market color, The consequence and its intentions, New verticals and horizontals, The truth, which isn’t linear, The market standard-bearers), examples from just the past ten days or so. And I don’t think I can keep this up.

The time it takes each morning is far longer now than it once was, and, what is much more problematic, I’m falling behind as a result in reading that I used to do during these same early hours. The writing itself, I think, suffers, as the subject of these notes and of my learning starts to get repetitive and stagnant.

In other words, I think, the time has come. 300 posts, including this, is a handy milestone number on which to end. I’ll probably return (I say this to myself) to speculate and write about some favorite subjects (if I had to guess), but perhaps it won’t be daily and it may not be for a while. On the other hand, when it does happen, I will likely have some new material, having caught up by that time with so much reading I would like to do. By then as well, perhaps, the world will also settle into a new normal, which hopefully will be a good thing and provide a new and interesting area of study.

Until then, the posts are all here for the browsing, categorized by subject and pull-down menu reference, each with links to others at the bottom, suggested by the platform based on some tagging reference, I imagine, which makes the bounce-around even more of an adventure. As well, there is a drop-down menu organized by month, which may at some point be another reference, a document of sorts as we progressively evolved from one world to another.

I guess, in ways, this may have been a book. Maybe sometime in the future, and maybe we’re already there, such interactive and dynamic books will be a whole new category. Like fiction, history, biography, business, mystery and etc., but converging all of these and more, like markets do, and other networks.

The market standard-bearers

There is much self-inflicted pain in markets caused by stubborn, antiquated measures, definitions, guideposts, dating back to who-knows-when and still the basis of the segmentation and the analytics, the theories and allocations, which have not much to do with what in actuality goes on out there, in the world where it most matters.

The More Markets Change, the More They Stay the Same, according to The Wall Street Journal, in a profile article that includes the following chart in support of the observation.

I’m sure there are clear demarcation lines somewhere that separate and organize the items in each of the listed pairs, but if the average investor were to take a minute and really think through what if anything these designations mean and what would cause a given stock to be in one and not another, it might take more than a minute to arrive at a dubious non-answer.

To keep things simple by focusing on the biggest of the subjects for this type of exercise, we can look at the grand five public companies that we sort of know as FAA[M]G, or Big Tech, or the Big 5: Apple, Amazon, Facebook, Google, Microsoft, listed alphabetically to avoid subjective bias. Eyeballing the categories again, I think these five could comfortably fit in every single one of every listed pair, except for small – which is itself a clue, I think, that we should dig a little further.

These were at one time small but they no longer are. And the trajectory has come about in record time, and hasn’t budged since the five’s grand arrival.

And now they keep on growing and expanding the area of their shadows, where all the others in this new market move around. In the chart below, the dark blue line down at the bottom stands for the 505 companies in the S&P 500 Index, which includes the five of the superior lines above. Were these to be stripped out, the index obviously would look worse, much worse…

Yahoo Finance

How much worse exactly would depend on the percentage composition of the total that the Big 5 represent. As of June 30, according to Slick Charts, that figure stood at roughly 22%. So, of 505 stocks in the widely accepted benchmark index, five constitute more than one fifth.

It pays, I think, given this circumstance, to look to these Big 5 (which straddle all the standard categories, as mentioned) for particular analysis and profiling. What makes them special? What drives their largeness, value, growth, tech and non-tech, U.S. and all the world, and all of that?

A few years back I shared my views on what I believed (and still do) was the answer, and even though there’s been a lot that’s changed since then, the principle remains: Networks 3.0 – defined by digital dimensions. As I extrapolate from there to have a look at all the others in the referenced big list (i.e., look to the networks and their deep effects), here are some results:

All five of the top 5 comprise 22%, as has been said. Of the remaining 15 in the top 20, eight are similarly characterized (including two global finance institutions) and in the aggregate make up another 8% of the S&P 500. And because it pains me to leave out #21 and #22 on the list, as they’re such obvious examples, this adds another 2% to the total.

Thus, roughly 32% (rounding error excused) or almost one-third of the S&P 500 Index – that which is the standard of all performance measurement in markets – is supported by 15 companies (out of the top 22).

Each of these is different from the others in the grouping, judged by product, service, customer base, technology solution, location, and so on, but each of these is a very large and growing network. It may be about time to recognize this as a new market fact and standard, and draw some new conclusions, research some new metrics, publish new reports, maybe even build a whole new index. It helps, as a start, to be merely cognizant, as apparently the investors and traders implicitly already are.

Related reading: Interpreting the networks (2017).

Convergence, platforms and new market color (cont’d)

The new Stratechery essay on the evolution of Apple computing is a great history lesson in the evolution of digital networks. The same principles and patterns that we associate with other network systems – the forms and value of engagement, the clusters that grow or sometimes dissolve, the community behavior that shapes the network system overall and leads to outcomes that lead to other outcomes as the network profile and its set of links and possibilities perpetually change their shape – are seen in the evolving architecture and resulting marketplace of Apple’s ecosystem.

The End of OS X

An interesting aside in Ben Thompson’s essay is a hat-tip to Paul Graham, commenting on hackers and their interests of the period, whatever these may be, as a leading indicator of the network’s future patterns:

The context of Graham’s comment was his perspective on Apple’s stock value, shaped by network engagement as he saw it. Wittingly or not, the observation was way ahead of its time. I posted something yesterday about this same subject more or less: Convergence, platforms and new market color.

The fate of the big data banks

I remember “disintermediation.” In finance that used to be a thing. The vision and the trend line was predicated on the dismantling of banking institutions that stood between depositor/investor/consumer and borrower/issuer/vendor into various component parts to give each more direct access to the other.

And the result was many funds – hedge, venture, growth equity, assorted debt, and so on – and funds-of-funds, and other forms of go-between through which sources and uses passed. And banks of course were still involved in all of that, plus countless new advisory (gatekeeping) operations to help sort through the tangled mess. And later on the ETFs and index funds that would in theory disintermediate the mutual fund segment. (And who even knows what dark pools really are, apparently these also are disintermediating something.) And as the funds-flow architecture evolved to also disintermediate the system, there is by now a so-called payments category made up of layers like a jigsaw puzzle, where finance and technology converge.

So anyway, that’s how “disintermediation” seems to have unfolded, while the disintermediated banks are now many times larger than they were when this whole thing began. And every layer in the illustrated market network takes a cut for services provided. And every layer grows the shrinking distance between depositor/investor/consumer and borrower/issuer/vendor, the space where there is interference of some kind, for payment that is rendered.

With that by way of history, we enter now a time of break-up and anti-trust motif, directed at new data banks that have emerged. These, too, it seems, are ripe now for their fated disentanglement.

The cheapening of market presence

The winner-take-most statistical power law effect we’ve seen in many emerging business categories is a phenomenon that network scientists have noticed in their natural investigations for some time. It is a trait in certain business models where network effects can reinforce a market presence, sometimes exponentially and to the marginalized exclusion of competitors who are relegated to a long (and narrow) tail, which is dreaded. The Big 5 techs, so-called, are more truly the Big 5 networks (in the broad sense), and it apparently will take some kind of intervention to keep their dominance in check. There are other examples.

An overlooked example in this way of seeing the network power law phenomenon in market presence, is on the funding side of the equation. That is to say, there is a winner-take-most parallel in financial markets, which has as much to do with the nature of the underlying business target as it does with the network nature of the markets themselves. Bubbles form sometimes, concentrations gather, attention focuses or fades, and thus the masses of financial capital shape similar leaderboard formations at all their many levels. The portfolio positions of fund managers tend to overlap, the structure of securities go in and out of fashion, certain institutions amass growing troves, and so on etc. (The wealth gap that is growing, perhaps, is also part of the event and its network effect drivers.)

And just as the individual products, messages or links that pass through the Big 5 networks (and others) tend to commoditization by sheer undifferentiated volume in these network concentrations, it’s possible to see financial flows and products the same way. That is to say, the financial category and its varied funding elements that accumulate, are contributing to the cheapening of these, if you will. And the return opportunity fades.

In this context, some news items from the financial press the other day, which, like everything described herein, is a participant in the gatherings.

Progress and the clusters

The formations and movements of the clusters is the pattern recognition that ultimately matters. It’s referred to as momentum by some, strategy by others, depending on one’s technical or fundamental bias. In the first case, the criss-cross lines of history are extended out, subjectively, until it’s noticed that the line is broken. In the second case, the exercise is in principle the same, but with a more attentive look at underlying drivers and a proactive push. No matter, the clusters form and move, and thus the markets.

The “markets” in the aggregate are the network graph manifestation. Equities are just one part, with debt and all the other asset classes, and all the non-financial forms, such as the shopping mall and Amazon dot com, which in turn tie to supply and value chains back to financial categories.

The economy is reflected in markets, they say, and the reverse is also true. Underneath it all, the clusters grow or shrink or change their shape and nature of their links to other clusters that are very rarely static. The change has its effect in ways that aren’t easy to predict, because the system is multivariate and dynamic.

Nevertheless, it is inherent in our nature (and important) that we try. A bubble only happens if and when it pops. And sometimes even then, it bounces back. It isn’t final, though possibly transformed to something else. That is the pattern, that is progress.

Morgan Housel

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.

WSJ

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…

BI

… 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.

TechCrunch

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.

Fear and missing

The fear of missing out prevails. In an era of accelerating change and visibility – that is to say, of quick and massive opportunities (and sometimes gains), widely and immediately publicized (and oftentimes exaggerated) – it isn’t an improbable outcome. Among many.

The phenomenon has been so common in the past decade, more or less, to even get acronym’d by popular culture – FOMO – a mark of status and abundant use, when printed characters must keep up with breathless and persistent messaging, so no one misses out.

The power law manifestations in competitive dynamics where some winners take the most, are rooted somewhere not too far from FOMO, on a certain level. The market bubbles that emerge may be more obvious examples, although the network graphs and clusters are not so different from the first case, I don’t think.

Sometimes these bubbles burst, sometimes they don’t, and then it’s arguable that they were even bubbles. The speed however is the thing that is important. It signals to the next big wave, which starts out small, that missing out could be an issue. A missed gain is almost like a loss, and maybe even worse, if others made it.

The underlying basics aren’t of particular importance. It may even be that there aren’t any, or that the ones that are, are not thought through for lasting impact. Perhaps that doesn’t matter much, because the impact is inherent in the value or the bubble that gets formed. By fear and by the missing.

When the economy reopens, this may ignite the spark that leads to a recovery, which may be faster, sharper than if purely based on need.

Interpreting the networks

The social media hubbub over facts and checking, voices and editors, freedom and control, the public and the private gain, is a hubbub over network principles.

Economically, socially, technologically, politically, artistically, educationally, and in many other ways that overlap and interrelate, the explosive social media emergence of the past decade has been transformative. The speed with which this happened and its global scale have been unprecedented in all the listed ways.

Outside of certain market trades, niche publications and entrepreneurial segments, there hasn’t been much of a discussion at the mainstream level on the meanings and results of it, the qualities that shape the different outcomes, or outcomes that shape certain qualities, the nature of the different platforms at their root, and the defining principles.

What is now starting as a hubbub may lead to needed progress in a more formalized and structured understanding. That is the opportunity. Below are some excerpts from a longer post that went up on a different medium a while ago, which starts to play around with some such matters. The full thing is here.

Interpreting the networks

Distribution and hierarchy

  • In a networked information economy Power Law distributions emerge. This can be seen in the category dominance of leaders, followed by a long tail of smaller competitors behind (“winner-take-most” phenomenon), and it is sometimes also seen within the networks themselves as certain nodes and clusters gain in presence. Sometimes the loudest or most popular voices in the social web control discussion, certain apps in the app store rise up in the ranks, the top search results attract the most attention… these examples are all from the distributed multi-directional network types. The edited one-directional networks, like broadcast operations, are much more obviously hierarchical.
  • The tendency of networks towards hierarchy, by design or evolution, is a quality that in important ways resembles product distinctions previously described. In the extreme case, where a network’s flow is purely one-directional, this runs the disruption risks and profit pressures of a service offering, at the expense of much more valuable community. In a highly commoditized and competitive environment, networks seek to resist such outcomes.
  • Historically, the longest lasting networks in commerce have been multi-directional and distributed, where the operator’s purpose is to optimize the quality of distribution. Looking back past the current examples of digital search and marketplaces and others, examples include telecommunications systems that survived (but for regulatory intervention) since their first emergence and financial exchanges (that may have gotten into trouble from the concentrations that occurred). On the other hand, publishers of all forms (video, audio, print) have had rougher going.
  • This distinction of distributed versus hierarchical, and various points of nuance between the extremes, is shaping value formation within the network category in its current digitized form. Netflix, despite its global growth and dominant position, must compete with Hulu and HBO on the basis of its unique content. The competition is expensive, and the value of these properties, even the best of them, is nowhere near the value of the decentralized Big 5. There is no cord cutting, not really, only new digital cords.