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).

New verticals and horizontals

As is by now well known, the economic age we’re in isn’t defined by its tech/mobility/cloud/data/AI/robots/connectivity, at least not in terms of isolated pieces, but by the aggregation of these things and others to form a simpler and more comprehensive designation: the digitally networked age. For proof, one only has to look to market leadership for guidance, those which have deepened, widened, grown – consistently and dominant – for all of the past decade.

Accepting this to be the case, and going with the age’s stated definition, the lens through which we may assess strategic actions, splits or combinations is similarly one of network rules, parameters and vision. We can look at forms of product distribution, the processing of information, fund flows, and other basic elements of modern economics, as network forms that all evolve and dynamically flow to change the living body of the network’s interlinked topology. It is a continuous, self-energizing phenomenon – always on its way, never arrived – the way that any living body is characterized by the same.

In the case of enterprise expansions or retreats, defenses of attacks, friendships and enmities, the underlying network fundamentals map out a vertical and horizontal structure that is much like the verticals and horizontals of any other time: the former is a build or takedown of the integrated stack, the latter is a widening or narrowing of scope.

An offering that supplements the core is in this illustration vertical, and one that enters a new field is horizontal. What makes these movements more complex and interesting now than in the past (now in the digitally networked age), is the positioning of the competing networks relative to one another: a dance of sorts, a play that tests the limits and the balances of power on the stage.

With the above as a translator application – there are others – to make sense of enterprise directions, here are selected headlines from the recent news…

The consequence and its intentions

The line that separates intended and unintended consequences is only as clear as the intentions and the consequences are. Both forms of clarity ought to ideally be satisfied for the cause-effect of actions and reactions to flow as though in controlled lab conditions. But there is no lab per se in economics, it’s all an open field of influence and noise that makes the separating line in question rigorously delicate.

There are plenty of intentions, goodness knows – some clear, many approximately so, and some just vague and loose enough to be distorted – the lot of them could probably be plotted on a chart that would describe a bell-curve, where the horizontal axis runs the clarity continuum. The same type of statistical representation could probably be drawn for consequence, and in both cases the little subsets that are close enough to clarity may or may not overlap with one another in the underlying data set.

Which is to say, the ideal case of perfect clarity – in both intention and desired outcome – is theoretically, and very likely, minuscule. The vast majority, the dominant activity by far, is thus a matter of degree, a question only of how unclear or how far from perfection is the particular case, as measured by the combined consequence and its original intention.

The market is a voting mechanism, it is said, that bases its decisions on perceptions shaped by much of the above. Whether the market is right or wrong – and it is strictly speaking almost always wrong, as evidenced by perpetual price movement – is additionally complicated by the interconnection between its individual subjects: companies, industries, financial instruments, trends, themes and etc..

The degree of uncertainty, the magnitude of imperfection as contemplated in the (un)intended consequence environment described, is the degree of risk, on one hand, and optionality, on the other. Many refer to the latter as opportunity, but the choice of words can be deceptive – diminishing, as it does, the element of chance in the equation.

At the levels down below the market and the big economy – the micro levels of the enterprise, technology, product, customer base, social group, and individual – which are all influenced by and also shape the macro picture, the described elements are more or less the same. There is an important difference though, I believe, in that the macro set tends to be more aware of these things than the micro set tends to be. This is an added element of risk (and all of its assorted flip-sides) because the macro is almost always a diversified portfolio, while the micro almost never is.

Economic data

As if it isn’t enough that Economics as a discipline is all tangled up and circular, always as if deeper in the hole it has itself created. As if that isn’t enough to bring out the mystery and excitement of this sort-of-art and sort-of-science but really neither one. In addition, there is the shaky ground of the very information that is underlying, on which models are constructed and which adds to the adventure in unbounded ways.

I’ve wondered about the data behind employment trends before, and I keep wondering about it. While the updates keep updating, the gap that puzzles me remains. Maybe the puzzle is my own, I’m sure the specialists have it all figured out and reconciled. I’m sure it’s as precise as algebra, and only subject to interpretation. Which is where I stumble.

Here goes my mental block again…

Exhibit A
Exhibit B

If you add up the big bars in Exhibit A (initial weekly claims) and compare the ballpark figure to the latest total in Exhibit B (continuing claims), you may conclude that more than half of those who filed initial claims in the past months have returned to work. All while the noted new-claim bars each week stay elevated and stubborn, unprecedentedly almost.

First off, the two results seem somehow contradictory, and secondly, they don’t quite reconcile to common sense. If the shutting down of a giant economy can lead to the loss of more than 40 million jobs at once, and then with upkeep, how (when?) has that shock reversed concurrently to the tune of half?

No doubt, there is an economic explanation. Perhaps it’s rooted in the “seasonal adjustment” noted in the fine print of the graphs, perhaps it’s in the difference between the data sources, some based on agency statistics and others on surveys of some kind? (Do people still respond to those? Like Nielsen television ratings back when there wasn’t a digital connection?) Perhaps. Or maybe it’s all really as accurate as a clock. That seems like the most likely possibility, in light of market scrutiny at every single moment.

But either way, perhaps it doesn’t matter. If the vocabulary and the grammar are accepted, the language is the language that is and should be used. It’s important for there to be a way to tell the time and be in sync for our appointments, as much as we may secretly question the schedule.

Mixing up the signals

In anticipation of what might be coming up if certain trends continue…

… it is now suggested that the banks should save…

… which may offset the signal of low rates on market calculations…

… because no rate is low enough when funds stop flowing, or high enough when savers need to save.

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.

Convergence, platforms and new market color

The categories on which we continue to insist make little sense and getting littler with time. We still insist on calling them consumer, industrial, financial, telecom and so on. We also call one isolated category tech, as though the notion can be isolated still, like it was (arguably) before becoming universally adopted.

We need such guideposts to stay organized and clear in our perspective(s), but there comes a point where the method turns against us on account of unreality…

WSJ

… because, when everything is tech, and when so-called Big Tech is by extension into everything, the lines of demarcation get all blurry and confused, the reference points to which we are accustomed become faded, the competitive landscape turns into a tangled web… gradually, gradually, and then of a sudden.

It’s gotten to the point, perhaps, where rather than evaluating stocks and assets on a standard model that narrowly compares each to others in its increasingly artificial category, we recognize now that Big Tech (a misnomer, really, these are the Big Platforms) is now the standard by which others can be universally assessed.

The exercise may not be formulaically financial, necessarily, as much as strategically diagnostic, though these things tend to be connected. The Big Platforms, to begin with, are made of multiple dimensions, network entanglements, and effects. These, once a certain depth is reached, become too deep to fail, (unless by legislated disentangling, as is now apparently considered with much effort and confusion).

Secondly – a broader, more impactful aspect of all this from an economic vantage point – is the theme of industry convergence that these platform companies represent. Media, finance, healthcare, commerce, transportation, even manufacture, are all represented here, and other categories also that are transformationally underway (e.g., robotics, virtual reality, symbiotics).

We once went through a major phase, some decades back, of big conglomeration. It was the time when synergy became a common term and when some big conglomerates became the standard-bearers. After a while the trend reversed and there were spinoffs and divestments and restructurings, and the word synergy went out of style as much of its luster faded.

This time is different. It really is. The fundamentals are inherently created now, and the strategic expansions referenced are following their natural progression. As much as software is eating the world, the new analysis and study is network science.

In the footsteps of giants

Sometimes, such as now, when the market’s watchers seem entranced by day traders and their daily whims, it’s fun, behind the scenes, to add another layer to the picture, imagining a silent smiling figure among the watchers, pressing a button here and there, infrequently and almost casually, which causes everything at once to scramble and change course. Like an elephant or some such giant walking slow and heavy through a jungle, oblivious to specimens that scurry down below, the frenzy of each giant step that’s taken.

It isn’t fair for either the big or little specimens to think about such things (for one’s amusement), because it isn’t altogether like that in the real life of the market or the jungle, but when we watch things from afar we simplify. For fun or not. And in this case the walking influential giant, for fun, embodies the investment funds’ limited partners. The limiteds, in parlance.

This ultimately is the money source that calls the shots, if only indirectly. It can move funding and commitments from here to there; it can deposit big amounts or take these out; it can go the private or the public route, equity or debt, early- or late-stage, alternative or what have you. And sometimes, if it wants, it takes from one pocket and transfers to another, all casually like – as mentioned, the cartoon is for amusement – and even when that happens all the market watchers and the traders and what have you, scramble.

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Who’s writing the first checks
“On Wall Street, the rich aren’t easy to rob.”