Since taking a break from my daily notes in this space about a year ago, I’ve published a handful of longer pieces on Medium; and for some of you who used to follow me here, I thought you might be interested in these. The most recent one is copied below and the link for all the others is this. Maybe one day I will return to the daily exercise, and until then I hope you will stay well and check in on occasion.

Ten network value lessons from the digitized economy

Networks are having a moment, or rather, they’ve been having it for quite some time, long before the big contagion and the flattening of curves, but the moment is expanding. Stephen Wolfram is working on a new physics model that would explain the universe in terms of network evolution and lead to the long-sought Unified Theory in the field. Niall Ferguson published a book that presents modern history as a series of network events, governed by network behavior and attributes. It is generally recognized in financial markets (themselves dense network structures) that the modern economy was borne of the InterNET (emphasis added). Most currently, cryptocurrencies — a revolutionary but natural extension from all that — are inherently network structures.

And yet there has been very little in the areas of finance and economics — in the mainstream at least, really nothing — to seek to bridge the analysis of value and strategy with what would seem an important counterpart in network science. If science is in this case too strong a word, network theory would be a good enough place to start. While the footprint of commercial networks has been growing to the point where regulators are even taking note, the resulting arguments don’t seem rooted in any network concepts or their context, which renders the debate — at a minimum — incomplete.

Perhaps the financial conventions that we still resort to, predicated on old-economy metrics and trends, are adequate enough. It is nevertheless non-trivial and now also opportune to try to understand the network asset on its terms. What follows are high-level notes, almost a preface, in support of an investment thesis that may be backtested with promising results. This is only a summary, purposefully light on supporting detail and examples that could one day turn it into someone’s massive book. But the interested reader should be able to consider cases, circumstances and criteria from one’s own observations that will fit the mold.


1. In an economy dominated by technology advancement and the digitization of virtually all things, there is a diminishing distinction between companies in the so-called “technology” segment and all the others. On the supposition that a time will soon arrive when the distinction will have altogether vanished, the more important difference is between companies that offer product or service solutions with and those without network effects.

2. The latter are in a state of constant need to upgrade, update, reinvent, ride cycles up and down, and reduce pricing on their offering, or else become disrupted or commoditized in a competitive environment that is moving ever faster. The former — businesses with network value — are better able to withstand attack and well positioned to drive down the costs of growth, because the network mesh is both a base and self-perpetuating driver.

3. But not all networks are the same, in fact they’re mostly very different from each other. At the highest level, these include marketplaces, exchanges, communication systems, platforms, artificial intelligence and other connected data tools — to name some of the principal categories — which may also combine several of the listed fields. And by the same token, network effects — defined as the improvement of network experience or value with the addition of new sources of engagement — are also different among the varied types. These can be broadly classified as user or data network effects — the first a matter of popularity and the second a matter of depth — which may also for some networks work in combination.

4. At levels below the very high, there are more nuanced distinctions that define the nature of the asset, often relative along a continuum, rather than binary or absolute. Examples of such qualities include the centralized, decentralized, and distributed topologies; the single-, bi-, and multi-directional data flows; and the single and manyfold layers of the network, which often co-exist and may in fact be linked, internally or externally to the individual business unit. There are also differences of strength between the ties that link the nodes together, and there are differences in size and numbers of the clusters that ensue.

5. These things and others shape the network profile, which in turn shapes its value and potential. Distributed networks, for instance, all other things being equal, may be more valuable than the centralized variety at the opposite extreme, because the single center-point of the former is a vulnerability to its whole. But all other things are not equal, and thus the network whole is best to understand without such oversimplification. Perhaps the one true constant in the general assessment of all sorts is the value of engagement, an attribute that’s always worthy, regardless of the other qualities described.

6. The so-called FAANG contingent — a less than ideal grouping as each of the five constituents is a different type of network from the others — is a highly visible sampling of the digital network asset class. Because they’re big and public and have evolved in more or less transparent ways, they make good subjects for more general analysis that can be carried over to the less developed cases. The fastest growing (if not already dominant) forces in many if not all the major industry segments — transport, finance, commerce, education, health, security, most recently biotech and manufacture — are additional examples.

7. In all the branches and the realms, it is difficult to the extreme to build a network from ground up. Unlike a product or a service that is designed, produced, and introduced into the market — successfully or not — a network is a complicated being, almost biological in nature, and subject to improbable conditions to take root. And when it does — a miracle in ways, which follows an inflection point that’s hard to manufacture — the network must be nurtured like an organism. The influences and the outcomes (which is to say, the behavior of nodes and clusters) aren’t always easy to anticipate, and there further comes a time at which the growth will asymptotically stall. When this occurs, new use cases or network offerings may provide a lift, but it isn’t always known during such times if the desired effect will materialize. Conversely, a robust and growing network can create great optionality, which may among other things enable an expansion into contiguous network areas.

8. Despite the frequent overlaps of categories — for instance, in finance and commerce, in information and entertainment, messaging and transactions — it has been observed that where user network effects are a core network driver, the resultant entities tend to be unique. Think, Instagram, LinkedIn, Twitter, YouTube, in the social realm, despite the basic similarity ingrained in messaging. It’s also been observed that as new categories form, the landscape tends to winner-take-most or even winner-take-all (power law) competitive effects. The same is true of the behavior within the network, as big clusters tend to become bigger and even dominant at times. (The influencer economy is a result of such network patterns.) What all of this describes is a tendency to centralization, even among the decentralized, that the subject networks may seek to mitigate.

9. Financially, the network’s most attractive features are profitability (after the inflection point) and predictability (as network effects take form). In combination with the winner-take-most advantage previously described and the high-gross-margin nature of the software business in the digital economy, the cash flow of the operation can be superior to almost any other business type. In cases where this is not so, it is advisable to wonder why. Perhaps the subject isn’t quite the network that we might assume it is, while, on the other hand, it’s also true that there are companies that unsuspectedly reveal themselves as such.

10. As certain network platforms have grown and reinvested cash over the years, the concern has recently arisen that these have taken on monopolistic forms which have to be controlled. Should there be a breakup of some kind (which wouldn’t be a first, e.g., Ma Bell), it may be worth remembering the nature of the living organism. Plants can continue to grow after a branch or two have been sliced off, and even branches may evolve into a tree or two once they’re replanted. After a while, we may be back to where we started, or someplace very different and strange, because the consequence of change in complex systems is often unintended.


One way perhaps to summarize all the above and draw a financial conclusion in terms that match traditions and accepted standards, is this:

In the digitized economy, networks and network effects are capital, and seeking to develop these is a capital investment; technology advancements and disruptions are important, but on their own are an expense.

In the long term, however, network effects may also turn negative and spiral down, while the technology expense can in the short term create value.

Related reading:

Clusters of decentralized influence (2021)

Linear perception, exponential change, and the new value (2021)

Reinterpreting the networks (2020)

Markets and the year(s) ahead: Post-digital edition (2018)

Interpreting the networks (2017)

Networks 3.0: Defined by digital dimensions (2016)

Aesthetics and returns

“The number of true theorems is, I believe, infinite. And the number of definitions that one can make is infinite. All these things are out there, but on the other hand, you don’t know this, there’s no book of all these things, because there’s an infinite number of possible theorems and definitions. The key in doing mathematics is to find a good definition, a definition that will get you somewhere, that will unify perhaps other things, and so on, that’s a creative act. It’s a creative act to find something interesting in an infinite field, in an infinite collection of things. It’s out there, but you have to find it, and have good taste… in finding something that will really go somewhere.”

“The word beauty permeates mathematics. There’s an aesthetic to it, and that’s why we use that word.”

From this, the segue into finance is the concept of compound interest, the “eighth wonder of the world” according to another mathematician.

“Our research goes on all the time,” he says, before the cigarette gets lit.

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.

Remote work, entertainment, supermarkets
Institutional Investor
Who’s writing the first checks
“On Wall Street, the rich aren’t easy to rob.”

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.

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…

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.

What looks large from a distance *

The investment thesis to support the market’s apparent disconnection from [everything], according to some, is that on the basis of a long-term forecast model, the current year and maybe next will hardly show up. The following from Matt Levine summarizes the idea:


It all comes back to the same financial principle. Regardless of the valuation methodology – earnings multiple, revenue multiple, cash flow multiple, some multiple of an accounting fabrication, etc. – these translate to, imply, or are directly underpinned by a financial forecast. This forecast yields a present value calculation in which the terminal or future value – a shortcut for what future markets will bear in perpetuity – makes up the vast majority of the result.

Quote extracted from the same article

The issue has always been the same, only now even more so… The market thinks it’s “very forward-looking.” But it isn’t:

If we would backtest the idea 30, 50, 100 years ago on the timeline, we’d be likely to find that the subject company no longer exists, or if it does it isn’t the same company that traders bought or sold back when, or maybe it’s now a subsidiary that bears little operating semblance to the original asset.

In other words, the valuation model and all that it implies, is predicated on a forecast in which we might assume some growth or shrinkage, in which the first year or two probably don’t materially matter, as has been pointed out, but in which we are almost certain to be wrong about the nature of the asset in the future to begin with. It isn’t a question of how big or how small it will become, but what actually will it be? In perpetuity… which is a very, very long time.

The discount rate that reduces the guess back to present value, arguably, can take care of the conundrum. But not really:

First off, the terminal value in the model tends to be so disproportionately large (a multiple that magnifies the projection’s final year, by which time the operation has been typically shown to grow), that even on a discounted basis its impact on the overall is massive; and secondly, these days, the discount rate is more than likely low (ref., the risk-free T-yield curve).

Perhaps a more correct approach in what is mainly an academic exercise – because the market’s voice and judgment are what ultimately matter – is to substitute some long-dated option value for the future value in the model. Depending on the business type and profile, its fate may or may not reflect adaptation or survival, let alone leadership or following. And in a time like we’re in now, this great unknown but always possible discounts back to a highly subjective and interpretive guess.

Note *: Borrowed song lyric in the title.

The assumptions revisited

It seems like an eternity ago that chiefs were out performing with some semblance of conviction, at least some variant of guarded caution, to an expectant audience that always pushed for more. The market watchers were out toying (as liquidity and portfolios can sometimes make one do) with metrics and configurations like these were a kind of tender. That was a while ago, though not so long, before the focus shifted as it has to the assumptions, the assumptions, the assumptions…

(Which can’t be emphasized enough.)

It’s possible to look past certain things, approximate results, or get swept up in the excitement when the funds flow, the IPOs are pricing, and the economy is trending in an upward sloping line. When the economy can be defined and its component pieces somewhat understood, visions may be influenced by keeping up, and the attention to assumptions – their elements, causality, and dynamics – can sometimes trail the outcome, so to speak.

When the mood changes from gain to survival, the focus on assumptions picks up steam. It’s natural that this should happen: for market watchers who now have to look more closely as portfolio positions start to correlate and the liquidity gets questioned, and for the chiefs who might get by without it, learning to depend only on the enterprise that is forever being reinvented.

(This is a welcome thing at every level, I believe.)

The current case is an extreme, perhaps, (I am reminded of a wise investor who once cautioned against thinking of anything as extreme, for it can always be extremer), and the circumstances are unfortunate to say the least. But if there is a silver lining in it all – as there is with the popularizing and advancements of biotech, its methods and innovations – there may be one as well in financial planning and analysis.

The talk of a swoosh shaped economic recovery…

What’s a swoosh anyway? Is it sharp, flat, long, short, wavy?

… and related top-down theorizing and crystal-ball hypnotics…


… might start to shift to a bottom-up approach that’s based on direct experience in the individual case, shaping value drivers and metrics that will hopefully get shared for scrutiny, making both the enterprise and markets more efficient and the economy more robust, in the future that is always arriving.

Perception, timing and efficiency

Perception and timing are forever interlinked in market valuations, which can drive and are driven by liquidity. Circularly this comes back again to timing and perception. That which cannot be escaped.

Perception: A seller of an asset, for example, might feel its value to be 2x +1, where x is some operating or financial metric, the multiple implies its future growth potential, and there is an added premium because the asset is perceived as scarce and special. The buyer disagrees and would pay x, best and final.

Timing: For a variety of reasons, the noted seller argues that it’s justified to accelerate value realization. The buyer does not see it the same way (or maybe can’t) and would defer that value transfer, or, if possible and better still, eliminate it altogether. The buyer would rather wait for proof of how it all plays out, the seller wants to lock it in.

In this way of seeing things, the asset’s liquidity will increase with the narrowing of timing and perception gaps. And liquidity itself may facilitate that narrowing. When money and resources are abundant, for the buyer or seller, either way, and when the choice of assets is diverse, there is a greater chance than not that some deal will clear the market. Conversely, when liquidity is thin, the gaps are much more difficult to bridge, and assets are more difficult to value in the absence of transaction evidence – which may circularly lead to illiquidity, as alluded.

That second case is referred to as market inefficiency by some, implying that the first case is efficient. What is or isn’t so, however, may more correctly be assessed by individual objective. When buyers and sellers all perfectly agree on timing and perception, there is no value realization opportunity for either side, though by conventional accounts that is a perfectly efficient market.

It’s good to disagree, it’s good for markets to be analytically (as opposed to operationally) inefficient. Timing and perception gaps drive risk, which leads to opportunity. The risk is in this case a healthy variety. The absence of a gap, by the same token, may lead to a collective shocks in unison, which is a different kind of risk entirely.

Alternative asset classes, which tend to be less liquid, are an interesting case.