A valuation framework & market cap projection for major blockchains—

See which chains are the most *overvalued* vs *undervalued* right now:

At any point in time you can think of a blockchain platform’s valuation as determined by 3 things:

1- adoption & usage

2- platform moat

3- crypto mkt condition

How do these 3 factors affect token valuation / market cap?

1- adoption & usage:

It’s the fundamental valuation driver. Users need a chain’s native token to pay txn fees. Larger number of *active* users means more people need to hold at least some amount of said token, leading to higher token demand & driving up price.

’Tis a mechanical relationship that has nothing to do w/ speculative demand or expectation of price appreciation. Hence a long term valuation driver.

2- platform moat:

This affects investors’ risk assessment of a platform. If a chain is perceived to have a large moat— b/c, say, it’s been around for a long time & has strong community— more people’ll view it as a safer bet.

Whether that view is correct or not is beside the question. Point is perception of bigger moat & lower risk allows token to command a premium price, other things equal. I call this a “platform-specific markup” (you’ll see what this markup is for various chains in a min).

3- crypto mkt condition:

Investor sentiment— e.g. level of risk appetite— on crypto affects demand for all tokens. So does overall level of crypto adoption. There’s no valuation of individual token to speak of w/o context of overall crypto mkt.

We can use active addresses or txn counts to measure a chain’s adoption & usage, while using total crypto mkt cap to proxy for mkt condition. This gives us:

A chain’s valuation = a1 * (active address or txn count) + a2 * (total crypto mkt cap) + (platform-specific markup)

Charts below plot a chain’s actual mkt cap (in log) against model-predicted mkt caps, for 12 major blockchains. The 2 models use active addresses & txn counts to measure chain’s adoption respectively.

A word on terminology.

I’ll call periods when actual mkt cap (green line) goes above predicted valuation (red & blue lines) “periods of *overvaluation*”, and the opposite *undervaluation*.

These are awkward terms b/c to say something is over- or under-valued, it implies there’s an objective, fixed true value somewhere.

Reality is all valuations are relative. A chain’s valuation today can only be assessed against its past & against context of overall crypto.

(It’s like your physical location— a seemingly real solid concept but is actually only relative to the location of earth, which is a random rock floating in space but I digress.)

What “overvaluation” here really means is current mkt cap is higher than how much investors would have historically valued the platform at if given current adoption level & crypto mkt condition.

But that’s a mouthful. So let’s stick w/ over- & under-valuation for now.













Below is ranking of gap, by chain, btw actual & estimated mkt caps as of 2 wks ago. Again, positive gap = overvalued, negative gap = undervalued.

Result shows most overvalued chains right now are:

  • Polygon
  • Ethereum
  • BSC
  • Flow

Most undervalued chains are:

  • Near
  • Ripple
  • Avalanche
  • Bitcoin

The rest— Optimism, Aptos, Algorand, Solana— have small gaps < 10%. I consider these more or less fall within margin of error.

(BTW, like this so far? Subscribe to my newsletter to get smarter about web3 & macro.)

I know these results will push some people’s buttons. If your favorite chain isn’t in the category you want to see, a few things to note:

One, these are results from empirical estimates. I’m not imposing any personal opinion. No need to shoot the messenger.

Two, there’re a thousand reasons one can come up w/ for why these results don’t apply to a “current situation”— phenomenon otherwise known as “this time is different”.

Example. You may say chain xyz is being priced higher right now b/c token supply is shrinking, or mkt is pricing in higher growth prospect as big projects are coming online. Or chain xyz is priced lower b/c it’s literally dead or will die soon.

Could those be valid reasons? Of course.

But no matter how good the reasons are, keep in mind historically periods of overvaluation tend to be followed by the token underperforming overall mkt in subsequent year. This overvaluation-underperformance relationship is very strong:

Can the case you have in mind really be an exception? Yes. Is it statistically likely? No.

Three, though these valuation gaps tend to mean revert, w/ over- or under-valuation periods generally lasting 6 mos to a year, there’s no way to predict exactly how long they’ll last.

Just b/c a chain looks undervalued today doesn’t mean it’ll self correct by tomorrow, vice versa. Typical “value investor” trap is to buy something that appears undervalued, which goes on to remain undervalued for ages.

A better approach when you believe something is undervalued is to put it on your radar. But only buy when you see some signs that trend may be turning.

Finally here’re estimates of platform-specific markups. Again these measure a platform’s moat or perceived risk level. If a chain is seen as having a bigger moat, i.e. more likely to continue surviving & growing, it can command higher price for same level of adoption & usage.

There’re some salient patterns in these markups. You’re smart. I’m sure you can spot what they are 🙂

Finally, though these valuation estimates are based on data of 12 public blockchains, same framework can be used to value other blockchains & in fact, ANY tokenized projects that have network effect potential, e.g. gaming platforms.

I’ll deploy a simple valuation tool soon where you can plug in usage numbers of any project & get its valuation estimate back. Very excited abt that. Stay tuned for announcement.

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