Clusters of decentralized influence
Two characteristics of the Bitcoin trade are generally overlooked in the discussion: (1) Distributed networks tend to concentration over time, and (2) the price of Bitcoin can’t, by definition, be a bubble.
If a value bubble is definable as a wide and growing gap between the technicals of a traded asset (financial supply and demand) and the asset’s fundamentals (product or use case supply and demand), then in the case of Bitcoin the technicals and fundamentals are the same — its principal use case (for now at least) being financial speculation.
In this activity, the asset’s network profile is, or ought to be, a key consideration. One element of that would be the network concentrations that are growing. These aren’t bubbles and don’t give rise to such, as noted. Rather, the resulting patterns could be best considered on their network terms.
A distinguishing feature of Bitcoin and its speculative activity — unlike that of traditionally speculative assets such as stocks or fiat currency — is that it exists on and is in ways synonymous with the platform’s distributed network. Thus, Bitcoin’s price and trading volume (as in the picture with the title of this post) depict something like a measure of the network’s size and user engagement, particularly on a relative basis over time. The occasional spikes — especially the major ones, the inflections — should not be seen as bubbles but as network tipping points.
With network growth and increased engagement, there will be certain nodes that expand past the others in the mesh, and sometimes there are clusters that will form to act more or less in concert and to dominate attention. Whether as a consequence or cause of network growth, or more correctly both these in a cycle that can be referred to as network effects, these masses that develop and evolve can be mapped out to show a power law effect. In this, the group of the most active, influential and attention-grabbing rises to the top, followed by the fragmented thin line that is the long tail of the crowd.
This is observed in all popular social networks, and there is no reason to believe that the Bitcoin network platform should demonstrate a different behavior. The bigger miners, the exchanges, and the so-called “whales” that have with time emerged, are the beginnings of this inevitable network evolution. More recently these bigs were joined by newer entrants to the field, which seem to have arrived together and in mass. We may think of them as a large network cluster.
The last significant inflection point took place around the New Year timeframe, 2021, (seen in the title chart again, in both price and volume). It was around this time that large and well established corporations, institutions and other widely tracked investors had begun to visibly participate. It was around this time, as well, that IPOs of crypto brokerages began to factor in planning and anticipation. The list doesn’t require specificity — we’ve seen or can look up the headlines of the giant buys, the commercial activities that were announced, and the research publications from the big-brand outlets in support.
The details, for purposes of the argument at hand, are not consequential. The point is not that with large institutional and corporate participation the price of Bitcoin has exploded — everyone knows this, the recent correction notwithstanding — but that from the presented case of network behavior this makes sense. The growth in network traffic and engagement (i.e., the upward price/volume momentum) when the deepest and most influential pockets get involved, is not a consequence of money flows alone but also of the signaling that comes with it.
And in this sense — the money flows and signaling — one may be excused if one’s reminded of some other situations of some other money networks, centralized in nature, that we know. We call the leaders of these more traditional participants in the more traditional money market central banks, and if we should be so inclined, we possibly could draw a power law representation where these too would show up at the head of the deep network that they influence (and oftentimes control).
The newer network entities described — the leaders in both liquidity and influence — are now more prone to act than they had been before the tipping point of their big entry, now that they visibly hold big positions that were loudly advertised. For institutions whose investor money flowed into the system, and for corporations the balance sheets of which may now include a Bitcoin line-item to be marked to market every quarter, it is counter to their interest (for more than financial reasons) that the price should sink too low.
Much like a securities underwriter that provides price support in the after-market, or a central bank, as stated, that underpins its currency, the large and growing element of giants in the trade may now serve a similar market-network function.
For speculative purposes — which is the use case, once again — it helps to think about such levels of support, but also levels of resistance. If the preceding was an argument about price support, there may be a parallel analysis on price resistance (which is to say, the upside limitations), similarly based on a distributed network profile and characteristics. The financial upside in the case of networks is their perceived optionality — Bitcoin’s use case may not be financial speculation forever — and for a look at this in a generic market sense, please see this other commentary that speaks to future value.
Other related reading:
Linear perception, exponential change, and the new value (2021)
Extremes of sentiment in markets (2021)
Reinterpreting the networks (2020)
If it’s not a bubble (2018)