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Crypto Market Cap: An In-Depth Review & Survey Of Emerging Alternatives

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This post was last updated on September 11th, 2019 at 03:45 pm

By Nathaniel Whittemore & Clay Collins

Overview


This piece is a guide to the metric that dominates discussions of value in cryptocurrencies: market capitalization. In this piece, we review:

  1. Why Metrics Matter
  2. The Non-Crypto Origins of Market Cap
  3. 4 Major Critiques of Market Cap:
    1. Tokens /= Stocks
    2. Inflation Schedules
    3. Circulating Supply
    4. Redemption Impact
  4. A Review Of Market Cap Alternatives:
  5. Market Cap Improvements:
    1. ~Fully Diluted Market Cap
    2. Realized Capital
    3. Market-Value-to-Realized-Value-Ratio
  6. Value Assessment Alternatives:
    1. Liquidity/Volume
    2. Security
    3. Community/Network Health

The goal of this piece isn’t to argue for or against market cap, or present any one alternative as the answer. Instead, it is to present the idea that communally agreed-upon metrics create their own incentives. As a crypto community, the better the metrics we use, the better the work we’ll do.

Table of Contents

Introduction


How we measure success shapes the actions we take to achieve it.

This truism is felt daily by students around the world forced to push any intrinsic joy of discovery to the side in favor of accumulating the knowledge that will allow them to perform on whichever standardized test they next face. It is felt in the creative war rooms of advertising agencies shilling clickbait content marketing when what they believe the brand really needs is to better define its purpose. This impulse is also at play in public markets, where companies are effectively competing to achieve the metrics and key indicators that keep shareholders excited.

In immature and emerging markets, this reflexivity takes on a whole new dimension. In the traditional startup world, companies are easily caught in the beauty contest of trying to raise the most money from the most prominent investors, regardless of whether they (strictly speaking) need that money, and premised on the theory that higher raises attract more attention and better talent.

Cryptocurrency is, of course, an even less mature and even more ill-defined market than web and mobile startups. It is a market where speculation and the promise of the future massively outweighs any rational assessment of current utility. What’s more, the unit at the center of the cryptoasset space – tokens – is a phenomenon different than either shares of equity, coming with no guarantees or rights to future cash flows, or money as defined in the fiat world. Even those crypto tokens that are attempting to be “new money” and a global digital reserve currency compete in part by emphasizing some properties of money over others.

The result is an industry where any objective determination of value is extraordinarily difficult, if not impossible. By extension, this heightens the reflexivity of crypto, as assets value assessment is largely a function of how value is perceived by market participants.

In this setting, there is one metric that is commonly applied across all cryptoassets: market capitalization.

On the one hand, market cap makes sense. Just like you can multiply shares outstanding and by current price to get a comparative sense for how the entirety of a company’s stock is valued, so it makes some intuitive sense that you could multiply the supply of a cryptoasset’s token by the price of those tokens to get an overall value of the network. If this heuristic holds, it makes it easy to compare assets to themselves over time and to the market of alternatives at any given moment.

Undoubtedly, market cap has been the most consistent and dominant metric in this young industry. Whether trying to capture the fear and FOMO of a retreat or the excitement of a surge, headlines inevitably plumb for changes in either asset price or market cap.

There are reasons, however, to be skeptical. For almost as long as crypto has used market cap as a metric, there have been those who have critiqued its use and pointed out why, at best, it can be misleading, and at worst, it can incentivize a host of unproductive, even damaging behaviors.

The conversation about market cap matters more today than it ever has. The war drums of Wall Street are beating louder than ever. In August, NYSE-parent company ICE announced Bakkt, which will begin futures trading in December. Last month, the world’s third largest asset manager Fidelity just announced its new custody and buying solution, Fidelity Digital Assets. These are some of the first, but will not be the last major financial institutions to jump into crypto at scale.

Today, the lack of sophistication of our measures like market cap sets up a system that is in many ways waiting to be gamed. To continue the metaphor, while up until now that game has been played like tee ball, these institutional movements mean that soon we’ll be in the big leagues. The tremendous force of attention and volume of capital poised to enter means we need to have better tools to actually understand the comparative value of crypto assets and strength of cryptoasset networks.

This essay is a comprehensive look at market cap as a measure of crypto network value. It profiles what’s useful about it; dives into the specific critiques; and explores the alternatives that people are proposing. This last category includes not only better versions of market cap metrics, but entirely different ways to conceptualize value.

How we measure success shapes the actions we take to achieve it. Our hope in writing this is that we might do better by the incredible transformative potential of Bitcoin and other cryptoassets by aligning our actions with the best possible metrics.

The Origins of Market Cap


So, what is market cap and why did it become the dominant measure of value?

The roots of Market Cap go back far beyond the crypto markets. In the 1880s and 1890s, Charles Dow began experimenting with a metric to indicate the overall health of the stock market. The first iteration, published in 1884 in the Customer’s Afternoon Letter (the precursor to the Wall Street Journal), included 9 railroads and 2 industrial stocks. In 1896, Dow calculated the first industrial average of strictly industrial stocks with 12 original participants. The Dow is not the mean of the (now 30) constituent stocks, but the sum of the price of one share of each.

The problem with a simple stock price comparison is that it doesn’t take into account outstanding supply. Put differently, a stock price doesn’t indicate what percentage of the equity available in the company a single share represents.

Standard & Poor’s designed its market-cap-weighted index in part as a reaction to the limitation of this approach. The company had experimented with indices since the early 1920s, but published the first S&P500 in March 1957. Rather than simply look at a composite of the prices, S&P weighted its index by their comparative market capitalization.

Interestingly, a report from Wisdom Tree argued that the particular methodology might have been an “accident of history,” due as much to the constraints of the availability of information and calculation tools as to intentional design. In other words, the team designing the index could look through the annual reports of 500 companies and multiply the shares outstanding by the current price.

What emerged is a metric that whose simple clarity has made it an important market indicator to this day. By normalizing for supply, market cap allows us to understand the overall public market value of a company as compared to other companies. Market cap also allows us to understand a company’s value as compared to itself over time. The simplicity of the measure also lends itself to quick high-level comparisons of asset value across sub-categories – such as tech vs. retail stocks.

It is perhaps no surprise that the crypto markets quickly adopted a version of market cap to measure their emerging assets against one another.

How Market Cap Is Calculated


The basic idea of market cap is to multiply the supply of an asset by the price of that asset in order to get a total value.

In the crypto markets, the exact methodology depends to some extent on who is calculating.

Price is generally calculated as a composite of the spot price from some index of crypto exchanges. In some cases, such as the small handful of index fund products currently available there is a more complex and robust system by which those prices are calculated to account for variation in the price of the trading pair. In other words, it is easy to create a composite price for an asset that trades against USD, but more complicated when that asset only trades against another crypto pair like BTC or ETH. Check out Nomics’ and Bitwise’s thorough articulation of their respective methodologies.

Token supply is somewhat more complicated than price. While most stocks have a fixed issuance, most protocols are designed to continuously expand and inflate their token supply over time, either until a fixed cap is hit (as in the case of Bitcoin’s fixed supply of 21 million) or in perpetuity. In the early years, ranking sites tended to favor calculations of total supply as a way to try to normalize different inflation schedules. As we’ll see, that led to unanticipated consequences in how crypto protocols designed their emissions schedules. Today, the more popular approach is to measure “Circulating Supply” – the total supply of tokens currently available to the market.

To review, for all intents and purposes, when someone speaks today about the market cap of a crypto, they’re talking about the price of that token multiplied by the circulating supply of that token.

The 4 Major Critiques of Market Cap


If there positives of using market cap as a measure are things like simplicity and ease of understanding, it should come as no surprise that there are critiques, as well. For our purposes, I’ve organized them into four primary buckets.

Critique #1. Tokens /= Stocks


There is a fundamental problem with the crypto market cap to stock market cap analogy. To put it simply, tokens are not stocks.

Stocks represents ownership of an economically-generative entity. Specifically, possessing stock gives the owner 1) a claim on future cash flows/profits; 2) a claim to participate in the upside of a liquidity event such as a sale or public listing. Additionally, stocks come with a set of shareholder rights around things like information and disclosures.

Tokens, on the other hand, represent participation in a voluntary value network. They do not come with any claim to future cash flows or liquidity event participation – in part because the issuing entities are often not structured as centralized, economically-generative entities but as decentralized networks or nonprofits. They do not, at least in general or so far, come with rights. Tokens do have a price, but that price is not based on the anticipated real value of future profits but instead speculation about the overall future worth of the voluntary value network (i.e. the long-term likelihood that the token stores value and/or is used for exchange).

Now, there are many projects emerging that are attempting to design equity/stock-like mechanisms into their tokens that would make the stock:token analogy more apt. What’s more, there are many experiments with tokens as guarantors of rights to participate in network governance.

These experiments, however, remain nascent, and not even close to the norm of cryptoassets that use “market cap” as a measure. For what it’s worth, the token/=stocks critique doesn’t mean that tokens are less interesting or even less valuable than stocks, but simply that they are fundamentally different. It’s Apples and Orangoutangs.

Critique #2. Inflation Schedules


Another place the token:stock analogy breaks down has to do with issuance. In the realm of equity, the total supply of stocked issued is fixed, and can only be changed through a stock split, where new shares are issued in proportion to the owner’s previous holdings.*

*It is worth noting that for the purpose of this article, assume every sentence starts with “in general.”  Our goal isn’t to be hyper comprehensive about every edge case in how public markets and private crypto markets work, but simply to paint enough of a comparison to help understand how tokens are and aren’t different.

Tokens, on the other hand, are designed with built-in emissions schedules. In other words, the supply of a crypto’s tokens is continuously inflating, based on some set of pre-defined and programmatic rules. This has a couple of important implications.

First, anticipated inflation makes it hard to use market cap as a way to compare the value of a cryptoasset network over time because there are two moving variables: price and supply. In other words, a larger market cap today doesn’t necessarily mean the crypto is doing better than it was previously. It could simply be that there is more of it.

Second is the issue of comparison across cryptocurrencies. When comparing the market caps of two different stocks, one can be confident that the comparison is valid because in each case, the price is the price set by the market, and the supply represents the total number of shares available for the company. When comparing cryptoassets, however, two assets can differ wildly in terms of a) their emissions schedules and approaches to inflation; b) how long they have been issuing tokens. In other words, a “lower” market cap might reflect simply that less of a token has been emitted.

This is problematic to the extent that we associate a higher market cap with a more successful cryptocurrency, as it creates an incentive for those cryptoasset networks to design emissions schedules that distribute more tokens faster to keep their market cap high, regardless of whether that decision is right for the network.

Critique #3. The Challenge of Circulating Supply


As we saw in the inflation schedules problem, one of the biggest areas of critique with regard to market cap as a metric for cryptoasset networks has to do with the challenges of determining what number to use for supply.

The concept of “Circulating Supply” – the approach which today dominates estimates of supply used by ranking sites like CoinMarketCap and Nomics – was actually a reaction against a previous approach. As articulated by Ethereum creator Vitalik Buterin, the previous metric of “total supply” created a scenario in which it behooved cryptocurrencies to pre-mine the majority of their tokens and simply hold them in reserve in order to artificially inflate their market cap, in turn making them appear like a more successful project and increase demand for the token.

Circulating Supply was meant to put an end to that particular type of market manipulation by only counting liquid supply. The challenge is that there are a number of problems with determining just what is liquid.

First, Circulating Supply approaches tend not to have a way to deal with lost coins. For example, every coin ranking site today lists Bitcoin as having between 17 and 18 million in circulating supply. At the same time, however, nearly every credible estimate suggests that some 2.3 to 4 million Bitcoins are lost. Treating these tokens as lost forever would reduce Bitcoin’s market cap by 10%-25%.

Second, lost coins aren’t the only “illiquid” tokens that tend to be included in circulating supply. When a cryptocurrency forks from a previous chain, some amount of the newly distributed tokens are never claimed, meaning that supply estimates that include those tokens also often significantly overestimate circulating supply.

Third, as regulatory scrutiny around ICOs and token sales increases, one strategy projects are turning to distribute their currency is “airdropping,” where users are sent a certain amount of tokens from a project, for free, direct to their wallet address. Airdrops add their own difficulty to supply accounting, owing to the fact that many if not most airdrop participants simply collect all the free tokens they can get, with the hope that some become market leaders and they can go back and cash in. In other words, airdrops tend to increase distribution but also illiquidity.

The common thread in each of the above challenges with circulating supply is an over-accounting for the supply that is actually available at any given time.

Critique #4. Redemption Impact


It wouldn’t be a long read unless we attempted to coin a new term, right? Even more than inflation, even more than overestimated supply; the biggest challenge to the market cap metric is that, for the vast, vast majority of cryptocurrencies, buy or sell orders of any significant volume at the market cap price would have a dramatic impact on the price.

Redemption Impact Score is a measure of how likely significant buy and sell activity around a token is to change that token’s price. It is a measure of liquidity and the “realness” of a price. The more liquid an asset is, and the more distributed supply of that asset is, the better able to absorb meaningful exchange volume without seeing a price shock.

Many have commented on the gap between the math of market cap and the practice of how that math would function in the real world. 

Redemption Impact is a way to put some teeth around the idea of what would actually happen. It was inspired by ETF specialist Gabor Gurbacs, who wrote:

One liquidity/redemption metric that large ETFs/multi-billion funds test for is the ability to redeem x% of total assets in y days with z% impact on the underlying market price. In analyses x is generally between 5-10%, y is 1-3 days and z optimized to 0.1-1% range, if possible.

When an asset has a low Redemption Impact Score, it means that it can sustain its current price through a meaningful redemption of that asset. When an asset has a high RIS, it means that a significant redemption would have a significant impact on the market price.

The vast majority of cryptoassets have high RIS, which means that their price doesn’t reflect the true ability to act at scale against that price, reinforcing the idea that market cap is simply a theoretical construct that, if anything, is more distracting than illuminating about the reality of an asset.

Market Cap Alternatives

Introduction

In the first part of this section, we’ll look at alternative measures of value that are, for all intents and purposes, better approaches to a market capitalization-style metric that address some number of the critiques above. In the second, we’ll look at a group of alternative measures of value whose proponents argue might be either better or at least complimentary ways to look at the overall value of cryptoasset networks.

Market Cap Improvements

Improvement #1: ~Fully Diluted Market Cap

Summary: ~Fully Diluted Market Cap is an attempt to normalize circulating supply by measuring the market cap at a fixed point in the future sufficiently far away that supplies of today’s assets become comparable.

Originators/Proponents: Messari-owned OnChainFX is one of the primary proponents of Fully Diluted Market Cap, using the year 2050 as their supply benchmarking point. Their methodology has been applauded by many, including recently USV’s Fred Wilson.

More Info:

  • ~Fully Diluted Market Cap is an attempt to fix the disparity in emissions schedules and lifetime circulating supply between different assets. Because tokens are mined, minted or released on a specific timeframe, market cap – and specifically, circulating supply – can fail to tell the story of how one asset compares to another. One of the assets may simply be newer. To reiterate, this doesn’t matter in a world where market cap isn’t used to judge the strength of an asset. When it is, however, it creates an incentive for protocols to emit more of their supply faster.
  • ~FDMC is a methodology to address this problem by normalizing all supply schedules for a specific date in the future. Using the published emission and inflation schedules for various assets, you can calculate what the anticipated circulating supply will be. Originally, OnChainFX called this “Year 2050 Market Cap,” selecting 2050 as the point sufficiently far in the future to make different assets comparable. The term was confusing, as many assumed that “Year 2050” meant some projections of the future price or success of the asset, rather than simply a mathematical zoom out of the supply based on available data. The name Approximate Fully Diluted Market Cap was adopted to better reflect the idea. We say “approximate” to reflect the idea that, in some cases, the measure is simply mostly diluted. This owes to the fact that certain protocols have ongoing emissions schedules extending far into the future.
  • ~FDMC is not without its critiques. The first is that, even selecting for a relatively far out point like 2050, there are still many protocols that are designed to continue to inflate their supply in perpetuity, making it difficult even for a future point of comparison to be a true apples-to-apples supply comparison. Perhaps an even bigger challenge for the metric is that when calculating expanded supply, it holds price constant, as thought available supply didn’t have a direct impact on price. In reality, more supply being emitted would almost assuredly impact price, making it challenging to make conclusive assessments of overall network value from asset-to-asset comparisons. These critiques are not to delegitimize the value of ~FMDC, which is an earnest and thoughtful attempt to improve market cap. Instead, it’s to point out that even when one tries to fix one problem of crypto market cap, another problem tends to pop up.

Perhaps then, we need a bigger change.

Improvement #2: Realized Capital

Source

Summary: Realized Capital is an attempt to get a more accurate picture of circulating supply by removing lost, dormant, or never-activated coins.

Originators/Proponents: Realized Capital was developed by Nic Carter and Antoine Le Calvez and unveiled by Nic Carter at Baltic Honeybadger 2018.

More Info:

  • One of the biggest problems with the Circulating Supply number most market cap formulas use is that it tends to significantly overestimate actual supply by including tokens that aren’t actually available to anyone. Realized Capital takes advantage of UTXOs or Unspent Transaction Outputs. Gavin Andresen defines UTXOs like this:
  • UTXO is geek-speak for “unspent transaction output.” Unspent transaction outputs are important because fully validating nodes use them to figure out whether or not transactions are valid– all inputs to a transaction must be in the UTXO database for it to be valid. If an input is not in the UTXO database, then either the transaction is trying to double-spend some bitcoins that were already spent or the transaction is trying to spend bitcoins that don’t exist.
  • Realized Capital aggregates all UTXOs at their price of last movement to come up with a sum total for the value of the cryptoasset network. So, for a UTXO of 14.7 BTC last moved on Halloween in 2011 (when BTC was $3.12) would add ~$45.86 to the Realized Cap.
  • For Bitcoin, the granddaddy of cryptos, Realized Cap is a good way to address coins that have been lost over time. For forks like Bitcoin Cash, Realized Cap addresses tokens that were never claimed or activated. In his Baltic Honeybadger presentation, Nic Carter pointed out that while BCH’s market cap topped out around $60B, its Realized Cap peaked at more like $11B. The difference between the two wasn’t lost coins like in the case of BTC, but owed to the fact that many people never activated BCH airdropped to them in August 2017.
  • In the same presentation, Carter calculated the Realized Cap of BTC at approximately ~$88B, as compared to a then-market cap of approximately $110B. This ratio, as we’ll see in the next section, becomes more relevant.
  • One weakness of Realized Capital that Carter himself pointed out was that it can’t tell the difference between coins that are long-lost and coins that are long-held with intention. Net-net, the inaccuracy of a version of market cap that includes lost coins is almost assuredly more egregious than that which includes long-term holders.

Improvement #3: Market Value-to-Realized Value Ratio

Source

Summary: The Market-Value-to-Realized Value (MVRV) ratio is an attempt to incorporate market cycle analysis into market capitalization by determining how comparatively over- or under-valued an asset (specifically Bitcoin) is at any given moment. It is calculated simply by dividing the market cap by the realized cap.

Originators/Proponents: David Puell and Murad Muhamadov proposed MVRV based on the Realized Capital work of Carter and Le Calvez

More Info:

  • In their introduction to MVRV, Puell and Muhamadov make the point that both market cap and realized cap tell a different story. Market cap tells the story of the state of the relative hype and excitement in the market – in both exuberance and despondency. Realized cap on the other hand not only strips out the lost coins, but also indicates “where groups of long-term, legit, buyer-hodlers entered into their Bitcoin positions, with local and immediate emotions and manias stripped out.”
  • The relationship between these two measures becomes particularly interesting for understanding the market cycle. As hype grows, new demand floods the market, driving the price up, expanding the market cap, and ultimately increasing the MVRV ratio. On the other hand, when the market contracts and becomes despondent the price, market cap, and ultimately MVRV ratio come down to earth.
  • Puell and Muhamadov suggest that the historic MVRV ratio indicating Bitcoin being overvalued is 3.7. To them, however, the even more interesting number is when MVRV equals 1 or lower. Those are the period, historically, where the market has underpriced Bitcoin relative to its base-level value to the buyer-hodlers who aren’t subject to market manias. Consequently, these periods have tended to be good times for accumulation.
  • MVRV contributes to market cap alternatives an ability to add market cycle context to otherwise static measures.  

 

Market Cap/Value Assessment Alternatives

Introduction

The Market Cap alternatives above are attempts to provide a better macro indicator built on the price x supply heuristic. But of course, that entire heuristic is just one of the ways to look at the heath of a cryptoasset network. In this section, we look briefly at a handful of different approaches to determining the overall value of a network.

Alternative #1: Volume & Liquidity

As discussed above in the Market Cap critique section, one of the major problems with market cap measures historically has been that they tend not to reflect the reality of true cryptoasset liquidity and Redemption Impact. Why not, then, simply measure liquidity itself?

The idea of liquidity and volume as an indicator isn’t new. Most coin ranking sites list 24-hour volume right alongside price and circulating supply. One indicator that many use is Network Value to Transaction ratio – or NVT, popularized by Willy Woo.

NVT is measured as [Price x Supply] / Transaction count. NVT is an indicator of the strength of a cryptoasset as a payment network or settlement layer as compared to its market value. When NVT is high, it means that the valuation of the network is outstripping the actual value being exchanged with the network. When NVT is low, on the other hand, it may indicate that the overall network is being undervalued compared to the utility it is providing.

Another indicator of volume strength popped up recently when a number of prominent community members pointed out a metric called “Buy Support” introduce by coinmarketbook.cc

CMB defines Buy Support as the “Sum of buy orders at 10% distance from highest bid price,” using exchange data from a handful of prominent exchanges including: BitMEX, Binance, Bithumb, Bitfinex, OKEx, Huobi, Bittrex, Poloniex, Kucoin, Cryptopia. They also measure a Buy Support Ratio, which is the Buy Support of an asset as a relative percentage of the Buy Support of Bitcoin.

The idea is to understand how liquid the asset is by understanding how many orders are preparing to buy. And Buy Support does certainly show how illiquid most random ICO tokens most likely to hold up their market cap as a health indicator are.

On the other hand, almost as soon as CMB began to be noticed, another large portion of the community called out the problems with using public buy orders as a proxy for liquidity. The issues brought up include: 1) most people who want to buy at a price different than the current won’t want to lock up their money on an exchange; they’ll simply wait till the price moves closer to what they want; and 2) order books are easy to pad and easy to spoof.

Indeed, fake volume is one of the biggest problems in crypto. In March of this year, Sylvain Ribes called it a “crypto-plague” and argued that more than $3b of volume was faked, including 93% of the volume on then-#1 exchange rated by volume OKex.

One other interesting liquidity metric comes from anonymous trader Rae: Retail Trading Volume.

The goal of Retail Trading Volume is to understand what percentage of overall trading volume (using Bitcoin as a proxy) is coming from retail – i.e. infusions of new money – versus active traders. To determine the percentages, Rae compared volume from exchanges used most prominently by traders to a basket of exchanges used by retail investors. During the 2017 bull market, RTV averaged 46% – meaning new money was driving growth. Average retail volume in 2018 (at the time of Rae’s writing in June) was ~15% and had hit a low of 5.8%, indicating that most of the volume was traders. Like MVRV, Retail Trading Volume adds a market cycle picture to the overall liquidity and volume health indicator.

Alternative #2: Security

A fundamental principle of blockchains is that they are costly to secure from attacks. One idea that follows from that is to look at how much money has been spent securing the network as a determinant of value. In the same presentation where he introduced Realized Capital, Castle Island Ventures’ Nic Carter also shared a rough heuristic he called “Accumulated Security Spend.” The principle of Accumulated Security Spend (which can’t be easily acronymized for obvious reasons) is to look at aggregate miner revenue over time as a proxy for network value. It is based on the assumption that miners have fiat denominated costs, and have to immediately sell some portion of the Bitcoin they mine to cover those costs. Because there have to be buyers of that asset, the proceeds of BTC sales by miners gives a minimum floor for the wealth inflows to Bitcoin.

Analyst Matteo Leibowitz has also recently explored the relationship of security and network health in the context of the “Fee Ratio Multiple” which looks at what it would take for Proof of Work chains to secure themselves exclusively through transaction fees rather than through a combination of Tx fees and block rewards. Leibowitz measures FRM as Miner Revenue [Block Reward + Transaction Fees] divided by Transaction Fees, and argues that “FRM implicitly measures the strength of an assets properties as a Store of Value”

“..A low FRM suggests that an asset can maintain its current security budget (miner revenue) without having to rely on an inflationary subsidy. Conversely, a high FRM suggests that an asset will require heavy inflation via block reward subsidies in order to maintain its existing security budget.”

Alternative #3: Community/Network Health

Finally, as we think about the overall value and health of a cryptoasset network, we can look not only at outputs but at inputs and the strength of the community of contributors to that network. In a tweet in 2016, Monero lead Ricardo Spagni (aka Fluffy Pony) articulated this point of view, saying “We don’t view market cap as a measure of success; commits, issues closed, & network health matter!”

Some coin ranking sites have picked up this idea and run with it. CoinGecko, for example, pairs its normal market indicators with additional tabs around both social network strength and developer network strength. The social section tracks Twitter followers, Facebook fans, Telegram group members and subReddit subscribers. The developer section meanwhile looks at code changes, commits in the last 4 weeks, contributors, watchers, forks, and stars.

These community indicators, of course, do not give us the same degree of actionable information as market metrics. At the same time, they are, in many ways, more powerful as indicators of future network success than any immediate snapshot of price and market cap. The fact that these types of metrics are so much less prominent is a reminder that the demand for statistics like market cap comes from investors who want to make money now more than long-term network builders.

One exploratory metric that combines price with network value is the Network Value to Metcalf (NVM) ratio, pioneered by Cryptolab Capital. The experimental methodology tracks asset price against daily active addresses as a way to understand whether an asset is relatively overvalued or undervalued as compared to the growth in its network of users. For more, check out Rethinking Metcalfe’s Law applications to cryptoasset valuation

Conclusion


Any full look at the concept of crypto market cap is bound to conclude that it is an imperfect measure at best, and genuinely distracting at worst. In the short term, it seems unlikely that we’ll see the industry move to an alternative. That said, the emergence of alternatives and speed with which they’re being considered and even integrated into coin ranking products is extremely promising for this young asset class.

The conversation about market cap is more than a question about metrics. It is a conversation about value – and specifically, how to understand the overall value of crypto asset networks. If this is, indeed, a new asset class, it feels inevitable that the way value of that asset is measured will diverge, to some extent, from previous.

By continuing to improve the metrics by which we measure network value, we don’t just make it easier for traders to compare coins, but make it easy for teams and communities to benchmark their work to make their networks value. Better metrics mean better networks.

Reading List:

Authors:

Nathaniel Whittemore works with crypto funds and projects on communications and strategy, with an emphasis on understanding and utilizing market narratives. On Twitter @nlw, he is known for his Long Reads Sunday threads. Before accepting the call of crypto Cthulhu, Whittemore built a global impact program design center later endowed for $100m at his alma mater Northwestern University and was eventually lured to Silicon Valley to help scale impact with Change.org. In his decade in SF, he bounced between venture capital and helping big corporations like Coca-Cola, L’Oreal, and MasterCard understand new technology and adapt their marketing strategies. He is glad to have his soul back.

Clay Collins is currently the CEO and Co-founder at Nomics (which has a crypto market cap listing of its’s own) and Board Chair at Drip/Leadpages.  Clay hosts The Flippening and Nomics Daily Update podcasts. Before co-founding Nomics, Clay founded Leadpages, where he drove growth to over 48K paying customers (and 175 employees), led the company’s acquisition of Drip, and raised $38M in venture capital financing.  Clay is most responsive on Twitter and Linkedin.

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