This is a topic that certainly needs more research.
The use of Discounted Cash Flow leads to the Market Cap being an important number. As DCF isn’t a good model, the Market Cap is almost meaningless, although it is frequently used today when comparing cryptocurrencies. Actually, because of continuous new issuance resulting in inflation, the situation is almost the opposite of dividends. Coin holders will effectively have to pay a kind of tax.
A key point of the valuation by Pfeffer is the Velocity, seemingly arbitrarily set to 7. This velocity depends a lot of whether you are a Coin Holder, or a user.
At system maturity, there will be a fixed (scarce) number of tokens; it is written into the core code and
agreed upon by the participants.
Even though it is written into the protocol, it is ultimately a thing up to social consensus. That is, an economic majority may decide to change it.
Defining the supply as the number of tokens in circulation is not the same thing as the total theoretical supply. A number of coins are lost forever. Also, when talking about the supply-demand relation, it usually refers to the current supply and demand at an exchange.
At a specific point in time, the supply of ether is constant.
This is a crucial observation. It is a common misunderstanding that some cryptocurrencies are “unlimited”. Yes, they are unlimited with increasing time, but not at a specific point of time. Because of this misunderstanding, some people believe that the value should be zero.
Besides the promise of future execution, there are a few additional reasons to withhold Ether.
This is also a crucial observation. If you only take this into account, the value of ether doesn’t have to be high at all. But ether also has another important role, and that is to pay for the security of the network.
Because supply is fixed, price rises and falls with demand alone.
And this explains why there is a high volatility.
Personally, I think the Velocity Of Money is an important tool when analyzing cryptocurrencies.
There is also the interesting effect of the Network effect (or the lack of it), as you mentioned. This is important when analyzing fork effects. Notice that the network effect usually isn’t quadratic, but more like n*log(n). Notice also that the network effect fails if blocks are “full”.
I have collected my various thoughts and ideas at Medium