Where will other people buy ETH?
A 'value' framework
A 'value' framework
ETH is a complex asset to analyze
It has monetary and network value capture aspects
ETH captures a x% fee on all network transactions
ETH is also needed to settle transactions
Higher ETH prices create higher fees
The network is recursive
It has monetary and network value capture aspects
ETH captures a x% fee on all network transactions
ETH is also needed to settle transactions
Higher ETH prices create higher fees
The network is recursive
Every transaction on the ETH network requires ETH
This is the usage fee and is the core way ETH accrues value
Usage fees are simple to calculate given open source network
This is the usage fee and is the core way ETH accrues value
Usage fees are simple to calculate given open source network
Iβve published about how I look at ETH fees / valuation before
I use the monetary equation M * V = P * Q
P * Q = ETH network transactions
M = ETH Mkt Cap
V = Velocity which is implied
I use the monetary equation M * V = P * Q
P * Q = ETH network transactions
M = ETH Mkt Cap
V = Velocity which is implied
Why do I care about velocity?
If I take ETH and lever loop it 10 times I generate 10 transactions
That shows up as 10 separate usage fees
Velocity increases in speculative environments due to leverage folding
Bull markets over-earn network fees
If I take ETH and lever loop it 10 times I generate 10 transactions
That shows up as 10 separate usage fees
Velocity increases in speculative environments due to leverage folding
Bull markets over-earn network fees
The velocity range is 5x to 20x
This means each ETH is rehypothecated between 5-20x
The higher the number = more transactions = more fees
Here is monthly ETH txns vs velocity over time
This means each ETH is rehypothecated between 5-20x
The higher the number = more transactions = more fees
Here is monthly ETH txns vs velocity over time
We get 'organic usage' by dividing ETH txns by velocity
We can use this number and apply a velocity to create a network transaction sensitivity
So if organic usage is $20bn/mo and velocity is 10x then network transactions is
$20bn * 12mo * 10x = $2.4trn
Here it is over time
We can use this number and apply a velocity to create a network transaction sensitivity
So if organic usage is $20bn/mo and velocity is 10x then network transactions is
$20bn * 12mo * 10x = $2.4trn
Here it is over time
We now apply a fee % to ETH network transactions
This is effectively the price of gas β which is volatile
Gas fees seem to have settled between 0.20% - 0.30% over time
This is effectively the price of gas β which is volatile
Gas fees seem to have settled between 0.20% - 0.30% over time
With ETH network txns and fee % we can derive ETH earnings stream
We then apply a range of valuation multiples
This is how we can frame the ETH price
We then apply a range of valuation multiples
This is how we can frame the ETH price
What is the mkt implying today?
ETH is $1,200 now
Letβs assume the mkt will trade the network at 25x
That implies a 25bp fee take and $20bn organic monthly txns & 9x velocity
That is effectively where we were in KPIs for May (see earlier charts)
ETH is $1,200 now
Letβs assume the mkt will trade the network at 25x
That implies a 25bp fee take and $20bn organic monthly txns & 9x velocity
That is effectively where we were in KPIs for May (see earlier charts)
What does that mean?
Iβd be uncomfortable holding ETH here
$20bn monthly network txns seems overearned given NFT volumes and velocity should plummet to 5x
0.25% take rate is reasonable end of range but has risk
I constantly check / calbirate these numbers
Iβd be uncomfortable holding ETH here
$20bn monthly network txns seems overearned given NFT volumes and velocity should plummet to 5x
0.25% take rate is reasonable end of range but has risk
I constantly check / calbirate these numbers
Framework here is about isolating the rehypothecation over-earning in a bull market
You then step back and size the fee % and apply a multiple
Reasonable people can disagree on what numbers to base case but the historicals are clear
You then step back and size the fee % and apply a multiple
Reasonable people can disagree on what numbers to base case but the historicals are clear
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