Analyzing Bitcoin’s Network Effect | Crypto Channel

One of the most powerful things to look for in an investment is a network effect.

A network effect is an attribute of a company or other system such that as more people use the network, the network becomes exponentially more valuable for each user. It’s one of the strongest economic moats that a system can have against competitors.

This article takes a look at how bitcoin derives its value from its network effect, why that network effect is difficult for a competitor to displace, and what some of the risks are to be aware of so that investors can continue to assess the health of the network.

Rather than being about the short-term, this is about longer-term fundamental analysis on the protocol. In the short-term, bitcoin can move up or down significantly based on sentiment and broad macro factors.

## Network Effect Examples

Before I dive into details on bitcoin, we can isolate a few examples of different networks.

Telephone: One-Sided Network

One of the early examples of a network effect was the telephone. A single telephone is useless, but as more and more telephones began to exist, the telephone became one of the most important inventions of its era.

And we can mathematically derive why the telephone network gets quadratically more valuable as more people use it, rather than just linearly more valuable.

If there are two telephones or “nodes” on the network, there is only one possible connection between them. If there are three telephones (A and B and C), there are three possible connections (A to B, A to C, and B to C). If there are four telephones, there are six possible connections. If we jump to ten telephones, there are 45 possible connections. With 100 telephones, there are 4,950 possible connections.

Where “c” represents the number of connections, and “n” represents the number of nodes, the equation is c = 0.5*n*(n-1).

As “n” grows extremely large, the equation asymptotically approaches c= 0.5*n^2. This equation is known as Metcalfe’s law, and was originally presented for computer networks.

With billions of mobile telephones in the world (which now are combined with the internet), there are quintillions of possible connections between them.

The telephone and internet are both examples of one-sided networks, meaning that users could connect with other users, and each type of user or “node” is basically the same. There are also infrastructural elements like switch operators in the middle, but those services grow as necessary to support the userbase of nodes, which are all similar to each other.

Payment Networks: Two-Sided Network

Some networks are two-sided, meaning there are two very different types of “nodes” on the network. A type “a” node wants to connect with a type “b” node, but doesn’t generally want to connect with another type “a” node.

An example of a two-sided network would be buyers and sellers. eBay (EBAY), for example, exploded in value by getting a critical mass of buyers and sellers onto its online platform. An advertising network like Google AdSense is similar; there are websites that want to make money with ads, and there are advertisers that want to advertise on popular websites, and a marketplace for them to come together is exponentially valuable to find an ideal match, whether by human selection or by algorithm.

The equation for a two-sided network is also exponential. The number of possible connections in the network equals the number of nodes on one side multiplied by the number of nodes on the other side.

If you have 2 sellers and 4 buyers, there are 8 possible connections between buyers and sellers. If you have 3 sellers and 3 buyers, there are 9 possible connections. If you have 10 sellers and 20 buyers, you have 200 possible connections. Where “c” represents the number of connections, “a” represents the number of nodes on one side, and “b” represents the number of nodes on the other side, the equation for the number of possible connections is c = a*b.

This table shows how it scales, assuming for simplicity an equal number of nodes on each side:

If you have a merchant network with 5,000 sellers and 10,000 buyers, there are 50 million possible connections.

As the number of users grows into the millions and consequently the number of possible connections reaches into the trillions, the odds of a seller finding buyers for her products, or a buyer finding sellers of things he wants to buy, even if the products are rare or niche, increases. At a certain point of critical mass, the network becomes a “one stop shop” for just about anything, which is what makes it so valuable and dominant, and hard for a smaller start-up network to displace.

Another example of a two-sided network is the payment card, which can take a few different forms like a charge card, debit card, or credit card. There are only four major brands in the US: Visa (V), Mastercard (MA), American Express (AXP), and Discover (DFS), and they extend globally with various levels of reach. Among those four, the first two are the biggest and operate as independent payment platforms for banks to issue cards on, while the second two are smaller companies that combine the payment platform with the bank that issues the cards.

Over many decades, why weren’t there more? Why aren’t there twelve credit card brands instead of four? The reason for there being so few, and only two or three truly dominant ones, has to do with the network effect.

Merchants won’t accept cards that aren’t popular, because it’s not worth the hassle. Consumers won’t get cards that merchants don’t accept. It’s a circular problem; a catch-22. That’s why a network effect, once created, is hard to displace. It would be exceedingly difficult to create a new credit card network.

Only with the rise of the internet, which launched a rare Cambrian explosion of innovation that disrupted existing networks, did we begin to see some brand new payment networks like PayPal (PYPL) and Apple Pay (AAPL). Even then, however, they worked with the existing credit card networks and alongside them rather than strictly against them. And the internet made existing credit card networks even more valuable as well, since you can’t use physical cash over the internet. So, the internet expanded the available market share for these payment networks. They all began taking more and more market share from cash. Alipay (BABA) and WeChat Pay (TCEHY) of China had similar explosions for the value of their networks.

Shipping Network: Failed Disruption Example

Here’s an example of how difficult it can be for network effects to be overcome by competitors.

In the US, we have three main shipping networks. The two corporate ones are UPS (UPS) and FedEx (FDX), and then we have the United States Postal Service. These entities have network effects due to their widespread infrastructure- shipping centers and truck systems and airlines and trained personnel that operate them. This existing infrastructure base keeps the per-package shipment cost very low.

In 2002, the world’s largest shipping company, Deutsche Post (DPSGY) of Germany, tried to break into the lucrative US shipping market. It was independently larger than either UPS or FedEx, but its center of network density was in Europe.  So, this was the most well-capitalized possible competitor in the industry to compete against them.

But by 2008, Deutsche Post failed to enter the market:

Deutsche Post, owner of DHL Express, said it would close the parcel carrier’s U.S. operations after an unsuccessful five-year, \$10 billion attempt to crack into a \$61.1 billion market dominated by UPS Inc. and FedEx Corp.

The express unit will shut down Jan. 30, but DHL International will maintain its freight forwarding, contract logistics and international parcel shipping operations in the U.S., for which it will still try to complete an agreement with UPS by year’s end to handle airlift.

Deutsche Post, the German post office, bought DHL International in 2002 and acquired Airborne Express in 2003 as a platform for U.S. operations. But it never was able to rise above fourth place in market share, behind UPS, FedEx and the U.S. Postal Service, and by the third quarter of 2008, it actually had lost market share.

“The U.S. market is a highly concentrated duopoly,” John Mullen, global chief executive officer of DHL Express, said Nov. 10. “In spite of our investing massive amounts of money to be a credible third choice, the reality of the lack of scale [for DHL], the productivity that [UPS and FedEx] have, the market reach and the brand awareness make it impossible for us to make it economically viable,” Mullen said in a conference call with reporters.

For a while, DHL stuck around as an international courier, having given up on the domestic market. Ten years later, Deutsche Post tried to find another niche and began offering ecommerce deliveries within certain cities.

So, it’s possible to find niches that the big networks aren’t servicing completely, but it’s extremely hard to dislodge the leading networks from their core operations.

Social Network: Successful Disruption Example

The most-cited example of a successful network disruption was Facebook (FB) bypassing MySpace as the leading social network in the United States.

MySpace was founded in mid 2003. It reached over 100 million users at one point, and in 2007 hit a peak valuation of \$12 billion. Its valuation quickly collapsed thereafter.

Facebook was founded about six months later in early 2004, in a few years surpassed MySpace, and went on to reach billions of monthly users and attain a peak valuation of about \$800 billion so far. They also acquired Instagram, WhatsApp, and other key networks (which is now bringing some anti-trust scrutiny).

Despite some growing disapproval among governments and the public regarding how it tracks data or buys other networks, Facebook has so far survived multiple #DeleteFacebook campaigns and lawsuits and continues to grow, albeit with an older average age of users. Maybe one day it’ll be broken up or stagnate, but as of now it’s 17 years into its life and going pretty strong in the global sense.

One naturally wonders how Facebook was able to surpass Myspace, despite the head start that MySpace had. There are several reasons that could be cited, but I’ve seen two particularly compelling explanations that both played a key role.

The first reason is that Facebook began as a niche network and expanded from there. Facebook made users list their real names rather than being anonymous, and kept the network exclusive for university students at first. It rapidly achieved dominance in that niche. From there it expanded to everyone. To use an over-the-top analogy, kind of like how the invasion of Normandy by the Allied Forces in 1944 allowed them to gain a foothold and begin disrupting the western front of Nazi-held Europe, Facebook’s invasion of the college scene gave them a foothold to begin disrupting MySpace’s broader network.

The second reason is that MySpace was slow to adopt to mobile use, while Facebook was quick to. MySpace’s peak valuation was in 2007. This is the same year that the iPhone came out, beginning a wave of consumer mobile internet usage that would disrupt many industries. Facebook’s valuation was about the same as MySpace that year at \$15 billion, and continued exponentially increasing while MySpace’s valuation quickly collapsed. The social scene became the mobile scene, and Facebook was fully onboard.

Jeff Booth, a technology entrepreneur and author of The Price of Tomorrow, has argued that Facebook’s mobile strategy was their “10x moment”. The argument is that in order for an existing network to be disrupted, a new competitor must be 10x better. Because the existing network gives the incumbent such a large entrenched advantage, a new network can’t just be a little bit better, or even twice as good; it has to an order of magnitude better to convince a critical mass of participants to move to it.

Facebook’s combination of real names, dominating the college scene, and adopting quickly to smartphone proliferation while MySpace lagged at mobile adoption, made Facebook 10x better than MySpace in terms of viral potential, and from there the difference was unrecoverable.

However, given that there was only a six month difference between the companies’ beginnings, MySpace wasn’t the hardest network to attack in the first place. MySpace also went through a leadership change a couple years before Facebook surpassed it, when it was sold by the original founders.

Michael Saylor, the billionaire founder and CEO of MicroStrategy (MSTR), has cited \$100 billion as his threshold for when a network achieves near-certain dominance. When a company with a strong network effect reaches a \$100 billion valuation in today’s money and is far larger than any of its competitors, the divide is virtually unrecoverable and the risk/reward for betting on that leading network company to continue to succeed is very favorable. His 2012 book, The Mobile Wave correctly predicted the vast importance that mobile internet adoption would have on multiple industries.

By applying Saylor’s way of thinking, MySpace was disrupted before it ever reached true network dominance.

Social Network: Failed Disruption Example

We can continue Facebook’s story to add another example of a failed disruption attempt, kind of like the earlier Deutsche Post example. In 2011, Alphabet (GOOG) launched their social network competitor, Google+.

Facebook at that point was the leader in social networking, far bigger than MySpace ever was, and worth tens of billions of dollars, nearly at 1 billion global monthly users, and thus was basically right at the point of unstoppable network dominance.

Google, however, was an extremely well-capitalized competitor, being older and more cash-rich than Facebook, and with extensive server infrastructure already in place. Much like Deutsche Post thought it had a decent shot at breaking into the US logistics market, Google thought it had a decent shot at breaking into the social network market.

Google at that point had a dominant internet advertising network effect, and was the most-visited website in the world. Google put a link to Google+ right on its homepage, so that countless people would see it all the time. In other words, it tried to use its existing massive platform as its Normandy-like foothold to build a network effect in another industry.

However, Google+ only reached a peak of several hundred million users, never had very high engagement, and was shut down in 2019. They failed to make a 10x better product; there was no “special sauce” or combination of attributes that gave them, even as a larger internet titan, a real shot at breaking Facebook’s massive lead in social networking.

Alphabet did, however, successfully buy YouTube in its infancy, which went onto become  the most dominant network effect in its own niche.

Network of Networks: The Amazon Effect

It’s very challenging to find examples of \$100 billion networks that were later surpassed. All of the major examples of such a thing happening would basically be pre-internet and post-internet events, meaning that “making native use of the internet” was the 10x better usage that allowed newcomers to disrupt existing networks. Email disrupted physical mail, and e-commerce disrupted physical commerce, for example.

Besides that major epoch of technological disruption, there aren’t many examples of dominant network disruptions. The leading financial exchanges have remained the leading stock exchanges for decades. The leading credit cards have remained the leading credit cards for decades. Disruption is near-impossible once critical mass is achieved, because it’s very rare to come up with a 10x better solution. Old companies in fading industries fail all the time, but true network-effect companies tend to have extreme longevity.

The one company that has made good headway for breaking some network effects is Amazon. They’ve successfully turned one network effect into another and another, unlike Google and unlike Deutsche Post, but even that came with caveats.

Amazon began as an online book seller at the dawn of the consumer internet in the 1990s, which was its Normandy moment, gaining its foothold. It then became the leading e-commerce website across categories rather than just books, began building out a bigger and bigger warehouse and logistics system, and achieved network dominance in its industry.

Amazon then went after cloud computing. There wasn’t much of a leader at that point, since it was a new field. The leader for enterprise computer platforms was IBM, but like MySpace was slow to move on mobile, IBM was slow to innovate in this space. Amazon harnessed the utility of its massive ecommerce server space to offer cloud services to various companies, and quickly became the leading cloud service provider.

Amazon’s two networks, ecommerce and cloud, benefit each other. Profits from its cloud arm help keep its ecommerce prices low. Ecommerce alone tends to be a very low-margin and often unprofitable endeavor. Amazon needs a lot of extra server space anyway to handle spikes of traffic on key shopping days, so it made economic sense to further expand this capability and offer server space to others as well.

Amazon then went after online marketplaces by allowing other sellers to provide products to its existing userbase, which stole some of eBay’s growth potential as the leading online marketplace. Facebook also launched marketplace services as well. However, eBay is still around, still slowly growing, had a period of problematic management and distraction into other industries for a few years, and is now re-focusing, and never was anywhere near \$100 billion in valuation anyway.

For a while, Amazon has been expanding its logistics footprint, putting pressure on FedEx and UPS. Amazon started as their customer and remains so, but has increasingly wanted to own the last mile of delivery as well, which potentially puts margin pressure on those logistics companies. In this sense, Amazon has been more successful than Deutsche Post at becoming a leading logistics company. And yet, UPS and FedEx are still growing as the dominant last-mile players.

So even here, Amazon never cleanly took down a \$100 billion dominant network and replaced it. At best, it took the lead in certain industries that existing companies could have dominated but didn’t (like IBM), became a leading competitor that took some growth from existing sub-\$100 billion networks (like eBay), and became an increasingly relevant actor that affects pricing within an entrenched infrastructure duopoly (like UPS and FedEx).

## Analysis of Bitcoin’s Network Effect

I first wrote about bitcoin in November 2017, when bitcoin had that big bull run that caught the world’s attention. I took a rather deep look at it, and sorted through the broader digital asset space as well. I came up with some rough pricing models, but I had concerns about the health of bitcoin’s network effect and potential loss of market share, along with euphoric price action.

At that time, bitcoin was about \$7,000 per coin and had a total market capitalization of roughly \$100 billion. However, bitcoin dominance (referring to the share of bitcoin’s market capitalization relative to the broader digital asset industry) was at a low point and declining, and bitcoin cash had hard-forked from bitcoin and split the developer community to some extent. There were over a thousand cryptocurrencies including some large ones like ethereum.

Back then, I couldn’t put together a good risk/reward model for bitcoin or the others, especially given how much price enthusiasm there was, so I passed on participating, and just kept watching. Over the next two years, the industry had a big bear market, and many digital assets collapsed in price. Most of them still haven’t recovered to previous all-time highs.

However, bitcoin’s network effect continued to strengthen since then. I ended up buying bitcoin in April 2020, ironically at the same price of just under \$7,000 that I first analyzed it at back in late 2017, but with significantly less risk in my view. Even as the price has increased since then, I continue to view bitcoin as a favorable network investment, although it has periods of being locally overbought.

Ultimately, this decision came down to an analysis of its network effect, with the protocol likely having achieved escape velocity.

Bitcoin’s Strengthening Network

Bitcoin is primarily a savings technology and payment settlement network.

Smart contracts, apps, and other things are being built on top of it, but at this time that’s not its dominant use-case yet.

Its hash rate has reliably made all-time highs, whereas many cryptocurrencies still have their all-time high hash rate back in 2018.

This high hash rate makes it extremely expensive to even attempt an attack on the bitcoin network, because it would take as much electricity as a small country to do so, along with server farms filled with dedicated hardware which are often in short supply.

In comparison, the capital it would take to attack litecoin, bitcoin cash, bitcoin satoshi vision, or others is significantly lower. They have much less security.

Similarly, the number of bitcoin addresses holding 1 BTC, 0.1 BTC, and 0.01 BTC continues to increase.

Chart Source: Coin Metrics

It’s hard to measure how many people use bitcoin or other digital assets, or how concentrated the network is, because one address does not necessarily correspond to one person. Large addresses are often custodial accounts for thousands or millions of users, and large users often store their bitcoin in more than one address. However, it’s good to see the number of small addresses continue to increase.

The popular crypto exchange Coinbase alone has over 40 million users. Adding multiple exchanges together and factoring out likely duplicates results in over 120 million users around the world.

If I look at the ways that bitcoin’s network effect has strengthened over the past 2-3 years specifically, here’s a start:

1) Hard Forks Resolved

The hard fork between bitcoin and bitcoin cash in 2017 was sorted out by the market over the next few years; bitcoin retained the vast majority of the market share, while bitcoin cash diminished in comparison, and then split again between bitcoin cash and bitcoin satoshi vision.

Both of those tokens have reliably hit new lows in price relative to bitcoin, and each are currently worth less than 1-2% of bitcoin’s market cap. Neither of them have a significant hash rate compared to bitcoin, and both of them have fewer nodes.

Chart Source: BitInfoCharts

A lot of people ask, if a blockchain is open source and protocols can be forked, then is bitcoin really finite?

The answer is yes, as long as the community remains focused on one protocol.

I could technically copy Wikipedia (all of the data can fit on a thumb drive) and try to host it on my website as Lynpedia. Would I be a real challenge to Wikipedia’s traffic if I did? Of course not. Even if I copy the full text, I can’t copy the hundreds of millions of links on countless websites pointing to the real Wikipedia, the top search rankings and massive server capacity that Wikipedia has, or the community of people that continually update Wikipedia. It would be a non-serious competitor.

Similarly, anyone can copy bitcoin’s blockchain and fork it into their own design. The question is whether they can convince the majority of miners, node operators, and users to consider their fork to be the “real” bitcoin. So far, no contest.

2) New Layers Developed

Additional layers like the lightning network, as well as third-party custodial services, have improved bitcoin’s scalability. In 2021, major exchanges like Kraken and OKCoin agreed to use lightning.

Chart Source: Lightning Network Explorer

Scalability, specifically referring to the number of transactions per second that the network can do, is the metric that bitcoin sacrifices on the base layer in order to maximize other metrics like security and decentralization. Bitcoin can only do about 120 million transactions per year, and a few hundred million payments per year since each transaction can have multiple destinations. So, any layers that improve bitcoin’s scalability, including trustless or non-trustless solutions, can enhance the network’s value and alleviate future concerns about bottlenecks.

If we look at the global payments system, there are big settlement layers like Fedwire, and then there are layers on top of them that can handle more transaction throughput, and the banks settle those transactions in batches on the base settlement layers. Bitcoin has been evolving in the same direction.

Many people incorrectly compare bitcoin transaction throughput to something like Visa transaction throughput, but that’s an apples to oranges comparison. Bitcoin is a final settlement layer; Visa is a layer of frequent and reversible transactions built on top of a deeper final settlement layer.

Lightning is a layer on top of bitcoin that can handle an arbitrarily high transaction throughput over time, while still basing itself on bitcoin’s underlying security. It works by opening multi-signature channels between nodes, so that a user can send coins from one node to another, using a series of interconnecting nodes along the way.

It’s hard to measure exactly how many lightning nodes or channels there are, since many are not public. However, from speaking with lightning developers, the number of apps and the number of users on the network is increasing rapidly over the past 12-18 months.

Strike Global is one app in particular that I’m watching as it relates to lightning since that opens up a lot of payment options for folks who don’t even necessarily care about bitcoin as an asset. It’ll be able to transfer fiat payments using the lightning layer on the bitcoin protocol, without any real exposure to bitcoin’s volatility. In less than a second, the app can exchange dollars for bitcoins, send the bitcoins over the lightning network to a recipient address, and then exchange the bitcoins to dollars, euro, yen, stablecoins, etc.

Lightning itself is like the bitcoin base layer in the sense that it’s open source and nobody owns or controls it. However, some major developers like Lightning Labs are building the infrastructure tools that a lot of these types of app providers use in order to interact on the lightning layer.

In many ways, the network effect applies to the lightning layer more than even the base layer of bitcoin itself. The major limitation of the lightning layer is liquidity; it relies on a sufficient number of unique channels between unique nodes, unlike the base layer that relies on broadcasting transactions to all nodes. As more and more channels are created and maintained, liquidity improves on this secondary layer, and this allows for more adoption and leads to more channels in a virtuous cycle. And as tools keep being built and improved, it makes it easier for apps to onboard to lightning and improve the user experience.

I’ve spoken with Lightning Labs CEO Elizabeth Stark a number of times, and one of her key points is that the future of the lightning network should eventually work in such a way that most users don’t even realize they’re using it, in a similar way that most folks don’t know the technology stack that they indirectly use whenever they interact with the internet.

Institutional-grade custody solutions have rolled out, including by Fidelity. These solutions provide robust on-ramps for institutional money to enter the industry. Previous bitcoin bull runs were driven by retail investors and speculators, while 2020 was the year of institutional interest.

In December 2020, the largest bank in Singapore announced that they will make an exchange and custody service for institutional and accredited investors (no retail), and that it will support trading in just four digital assets to start with, including bitcoin of course. NYDIG was founded in 2017 as another key custodian that focuses on large clients and specifically bitcoin.

Similarly, PayPal’s new program allows retail investors to buy the top four digital assets. Square’s Cash App allows retail investors to buy bitcoin only.

4) Major Investors Onboard

Thanks to these above efforts, bitcoin has reached institutional investors in a way that no other digital asset has.

Three companies on major US stock exchanges, MicroStrategy (MSTR), Square (SQ), and Tesla (TSLA), directly hold bitcoin on their corporate balance sheet now. Investors like Paul Tudor Jones, Stanley Druckenmiller, and Bill Miller have all gone long bitcoin. One River Asset Management launched a bitcoin fund and an ethereum fund for institutional investors that are expected to collectively hit hundreds of millions in assets under management. SkyBridge Capital just launched a bitcoin fund in early 2021 as well. NYDIG has spent years building a platform for institutional allocations and it’s getting a lot of traction over the past year, with huge inflows.

Bitcoin now has enough scale, institutional buy-in, and establishment credibility, to have a political/legal lobby. This can potentially mitigate regulatory attacks against it.

5) Bitcoin-Only (Not “Crypto”) Separate Ecosystem

There has been a rise in bitcoin-only and bitcoin-first companies.

Swan Bitcoin, for example, is a bitcoin-only accumulation firm, focusing on letting users dollar-cost average into bitcoin for a low cost, and with real customer service.

The key theme with these bitcoin accumulation platforms is you get a much better deal in terms of support and price than if you try to accumulate on most broad crypto exchanges that focus on high-turnover trading across many different tokens.

Coinkite and Specter Solutions have launched bitcoin-only hardware wallets with robust security features for techies, developers, and enterprise holders, whereas many earlier-generation wallets from other firms are multi-token. There has been a similar increase in bitcoin-only wallet software apps.

Casa is a bitcoin-first company, focusing on building multi-signature security solutions for safely holding sizable amounts of bitcoin.

Square’s Cash App lets users accumulate bitcoin and not other digital assets. Square also has bitcoin on their corporate balance sheet now.

The Strike app as previously mentioned is using the bitcoin/lightning network to send fiat-to-bitcoin-to-fiat payments globally. It does incorporate stablecoins from utility protocols as well.

Bitcoin’s ecosystem for hardware, security, and accumulation platforms is miles above any other individual network in this industry, while its ecosystem for development is in the top two along with ethereum.

6) Satellite Backup

The robustness of the bitcoin network continues to improve, and shows how hardcore the bitcoin community is about security.

It used to be said that bitcoin could be accessed by anyone with an internet connection. Well, now there are bitcoin satellites.

As Blockstream describes it, “The Bitcoin blockchain from space. No internet required. The Blockstream Satellite network broadcasts the bitcoin blockchain around the world 24/7 for free, protecting against network interruptions and providing areas without reliable internet connections with the opportunity to use Bitcoin.”

7) Bitcoin Rewards Cards

Bitcoin rewards cards exist now.

The Fold App lets members earn bitcoin on their purchases. BlockFi is launching a bitcoin rewards card. Cash App’s Cash Card lets users earn bitcoin on their purchases.

These are are all automatic accumulation platforms for folks buying into bitcoin on a regular basis in small amounts, against a finite supply.

A lot of people dismiss bitcoin and the broader crypto space as “speculative”, and that’s certainly true to an extent, since a lot of buyers are indeed speculating and trading.

But unlike many of the crypto tokens, and unlike many hot growth stocks out there to which bitcoin is often compared, bitcoin in particular has a huge community of dollar-cost averaging investors. This HODLer community focuses on buying in small tranches on a regular basis, and holding for years in cold storage.

From an outside perspective, I see some traditional folks put “crypto” and “bitcoin” and “wall street bets” and “retail speculators” all into the same bucket, but if you examine the communities up close, they’re actually quite different, with only partial overlap. One of these groups is not like the others in terms of the propensity to buy and hold.

## Bitcoin vs Other Tokens

According to CoinMarketCap, the cryptocurrency market capitalization is a little under \$1.6 trillion.

Bitcoin’s market capitalization is over \$950 billion, or 60% of the total. However, bitcoin’s market share among tokens that try to optimize for being decentralized stores of value is even higher.

Stablecoins

Of the total cryptocurrency market capitalization, tens of billions of dollars and climbing consist of stablecoins. These stablecoins are just an extension of fiat currency, so I don’t consider those to be competitors.

In fact, investors exchange fiat into stablecoins mainly so that they can trade other digital assets including bitcoin, with crypto-native liquidity that allows them to quickly move money around and arbitrage price spreads between exchanges.

Monetary Competitors

Then we have \$13 billion for litecoin, \$10 billion for bitcoin cash, and less than \$4 billion each for bitcoin satoshi vision and monero. Besides bitcoin, these and a few others are the largest coins that attempt to optimize for being stores of value and mediums of exchange.

Compared to bitcoin, these tokens have fewer nodes, far less hash rate, lack of dedicated hardware/security ecosystem, and lack of institutional interest, so their network effects are not remotely close. Each one has a market capitalization of less than 2% of bitcoin’s market capitalization.

However, not all altcoin projects are created equal. I’m not, for example, comparing litecoin to bitcoin satoshi vision, as they have different levels of seriousness.

Ripple/XRP

Then we have XRP at a little over \$20 billion in its own category, which is being charged by the Securities and Exchange Commission as an unlicensed security.

Their inventor, Ripple Labs, raises money from investors and actively promotes XRP usage, so financially, it’s a very different situation than bitcoin. Bitcoin’s launch process was totally unique, with no pre-mine and no central promotion hub.

Ethereum

Finally, we have ethereum and other utility protocols like cardano that attempt to optimize for other things besides simply being a store of value or medium of exchange.

Ethereum with a market cap of about \$200 billion, which serves as a platform for countless other tokens, is the one protocol besides bitcoin that has a substantial network effect at this point. I wrote my analysis of ethereum here. Cardano is over \$36 billion, and Polkadot is at \$32 billion.

Bitcoin focuses on doing one thing very well: being a decentralized and secure store of value and payment settlement layer. Other layers built on top of bitcoin can expand this capability, but that simple thing is what the base protocol does. Bitcoin is over 12 years old and hasn’t radically changed since inception. Changes occur slowly as needed to improve security, and the biggest recent update was SegWit in 2017, which improved scalability and solved certain technical problems so that the lightning network and other layers could be built on top of it.

Depending on how you look at it, the bitcoin base layer has been a finished (post-beta) project since 2017 when SegWit was implemented and the fork wars ended, and arguably well before that.

Ethereum doesn’t optimize for being a store of value, and instead aims to be a world computer that runs smart contracts for a large number of decentralized applications, with the premise that its tokens may appreciate in value if the network continues to grow and improve, since the second version of the ecosystem will have built-in liquidity sinks in the form of staking, and collateralization that can make holding ethereum tokens attractive. It’s like an operating system with a side order of money, and so it’s not exactly a direct competitor to bitcoin, although ethereum bulls argue that it could be if enough pieces fall into place from a technical perspective.

Ethereum 1.0 has been planning to change into ethereum 2.0 for a long time, and is rolling out that process currently and for the next couple years, which if enabled will radically alter the protocol, change its monetary policy, and transform it from using a proof-of-work mechanism to a proof-of-stake mechanism for its transaction verification process. This could improve the protocol’s current limitations, but comes with significant implementation risk. I also don’t view ethereum as being as decentralized as bitcoin.

Meanwhile, two other proof-of-stake utility protocols, cardano and polkadot, have gained some market capitalization. Together, they have about 30% as much market capitalization as ethereum, which puts them closer to the leader than some of bitcoin’s monetary competitors are to bitcoin. So, if ethereum slips in its ethereum 2.0 transformation, there are some competitors looking for market share in the utility protocol competitive landscape.

Unlike bitcoin, I have no price model or firm risk/reward viewpoint towards ethereum tokens. If I had to guess, I’m rather bullish on ethereum whenever bitcoin does well, since some investors will pour into ethereum, and the ecosystem hosts an active trading community in DeFi. And by extension, I’d be rather bearish on ethereum whenever bitcoin is in a bear market.

There was a research paper by John Pfeffer back in late 2017 that explained why utility tokens, in and of themselves, are unlikely to accrue a lot of long-term monetary value.

That paper has been debated back and forth, but so far has indeed mostly played out as written over the subsequent 3+ years; the amount of value transacted on ethereum has nearly tripled since then due to its usage for high-frequency stablecoin trading and decentralized exchanges, surpassing bitcoin in peak transaction value, and yet ethereum’s market capitalization hasn’t grown by that same percentage.

Source: Messari, CoinMetrics

Being a utility protocol does not preclude the tokens from also having store of value properties if things go well as part of the ethereum 2.0 overhaul; it just makes it challenging to do so since the protocol has to optimize for multiple things simultaneously. It has to optimize for being a utility protocol while also having liquidity sinks and incentives to hold the tokens, which ethereum 2.0 will do via staking if things go as planned, and which is already happening on ethereum 1.0 in the form of collateral.

Market Concentration

Adjusted for liquidity, bitcoin and ethereum dominate the digital asset ecosystem. Bitcoin and ethereum together have a very large percentage of ex-stablecoin crypto market capitalization among major protocols, which excludes a long tail of tiny illiquid protocols:

Chart Source: Bridgewater Associates

I get emails from folks regularly about their favorite protocol and how it’s just around the corner of displacing bitcoin or ethereum. They’ll provide a long list of why, in their view, this coin of theirs is technologically superior.

However, if it’s not 10x better, its chances are remote against the likes of bitcoin. Imagine, for example, that I were to invent a social network that, according to a sample of folks, had a slightly better interface than Twitter or Facebook. Would I have a chance of displacing them? Of course not. Going up against a billion-member network is impossible unless I’m doing something radically better or radically different. The same is true for any altcoin that is intending to be a store of value vs bitcoin.

Bitcoin hasn’t yet been displaced in twelve years despite the arrival of over 8,000 competitors. In other words, “if you come at the king you best not miss”, and so far there’s a graveyard of 8,000 misses, and a small handful of major protocols.

## Final Thoughts

Determining whether bitcoin is a good place to allocate capital to or not, ultimately depends on an investor’s assessment of its network effect.

In the meantime, it’s a machine for generating market capitalization in an algorithmic way. Every two weeks (2,016 blocks), the network undergoes an automatic difficulty adjustment to ensure that new blocks are being generated by miners every 10 minutes on average. Every four years (210,000 blocks), the number of new coins generated for each new block gets cut in half, resulting in a supply shock.

This pattern tends to drive the price up over time in a consistent cycle:

Chart Source: Blockchain.com

It’s unclear when this pattern will eventually break, but with its strong track record and the ongoing development in the surrounding ecosystem (hardware products, payment apps, security apps, custody solutions, regulatory improvements, and second-layer development), I think bitcoin deserves a consideration for a nonzero allocation in a portfolio.

However, investors can study the protocol and the ecosystem and come to their own conclusions.