One of the biggest pressing questions about blockchain-based tokens is, “What is this digital asset really worth?”

In fact, this question continues to swirl around the general issue of what is any digital asset or cryptocurrency worth at a given moment?

A lot of criticism has been levied at Bitcoin regarding the actual value regarding something trading like a security, but having no intrinsic corollary to a share of equity. Shares of company equity grant voting rights and a claim against the assets of a corporation. Thus, the value of a share can fluctuate against the speculation of the future output of the organization.

But in cryptocurrency, there has been a tremendous amount of speculative trading against something that yields no future value except for the willingness of the market to pay a premium out of nothing but the emotional desire to get into the game.

Greater fool theory? Maybe.

But does this mean there’s no basis to the valuation of a digital asset in general?

My answer is an emphatic, resounding NO.

Network Effect Economics

I’ve spent a lot of time over the past several years analyzing the growth of Bitcoin, and later Ethereum. My observations of the patterns of the market mirror the actual mathematical theory of the network effect on the economics.

The more people who use a network, the more valuable it becomes.

A network effect (also called network externality or demand-side economies of scale) is the effect described in economics and business that one user of a good or service has on the value of that product to others. When a network effect is present, the value of a product or service is dependent on the number of others using it.

The classic example is the telephone, where a greater number of users increases the value to each. A positive externality is created when a telephone is purchased without its owner intending to create value for other users, but does so regardless. Online social networks work similarly, with sites like Twitter and Facebook increasing in value to each member as more users join.

The expression “network effect” is applied most commonly to positive network externalities as in the case of the telephone. Negative network externalities can also occur, where more users make a product less valuable, but are more commonly referred to as “congestion” (as in traffic congestion or network congestion).

Over time, positive network effects can create a bandwagon effect as the network becomes more valuable and more people join, in a positive feedback loop.

Stock exchanges and derivatives exchanges feature a network effect. Market liquidity is a major determinant of transaction cost in the sale or purchase of a security, as a bid-ask spread exists between the price at which a purchase can be done versus the price at which the sale of the same security can be done.

As the number of buyers and sellers on an exchange increases, liquidity increases, and transaction costs decrease. This then attracts a larger number of buyers and sellers to the exchange.

The network advantage of financial exchanges is apparent in the difficulty that startup exchanges have in dislodging a dominant exchange.

For example, the Chicago Board of Trade has retained overwhelming dominance of trading in US Treasury bond futures despite the startup of Eurex US trading of identical futures contracts.

Similarly, the Chicago Mercantile Exchange has maintained a dominance in trading of Eurobond interest rate futures despite a challenge from Euronext.Liffe.

Valuing Bitcoin

So then, how can we leverage our understanding of network effect economics to value any given token in the digital asset sphere?

Back in the summer of 2015, Wedbush Securities released a report forecasting Bitcoin’s growth in value, and specifically pegging the valuation to the expectation of growth against the penetration of large target markets.

In particular, the report suggested that Bitcoin could end up powering 10% of online payments and 20% of global remittances by 2025.

Wedbush indicated it sees bitcoin demand stemming from its increasing use in e-commerce payments, remittances and micro-payments due to its ability to reduce costs in these industries. For instance, the report estimates bitcoin can lower online payments fees from 3-8% to less than 0.5%, while it can cut the cost of remittances from 5-10% to less than 1%.

Secondary to these industries, the report predicted, will be bitcoin’s growth as a “banking alternative” in times of economic crisis, its applications for machine-to-machine transactions and applications of the blockchain as a distributed ledger.

For its calculations on the subject, Wedbush also sought to determine how many bitcoins could be expected to be in circulation and held for investment annually until 2025.

The report notably foresees the percentage of bitcoins being held for speculation decline at a 2% rate annually over the next decade, falling from an estimated 24% today to 4% in 2025.

At that time, Wedbush expected bitcoin to account for 10% of the $5.9tn online payments market, 20% of the $744bn remittance market and 20% of the $924bn micro-transactions market.

Using these calculations, Wedbush forecasted the bitcoin network could support $595bn in online payments volume, $148m in global remittances and $184bn in micro-transactions.

Additional inroads are expected in enabling financial services in the developing world, with the bitcoin network accounting for $596bn in this financial activity.

“We see the scope of disruption as substantial considering 20% of US GDP is generated by industries whose main function is as a trusted third party,” the report stated.

The calculations led the Wedbush authors to conclude that, based on the amount of bitcoin needed to support such financial activities, the price of bitcoin was currently trading at 40% below its expected future volume.

Looking back on their forecasted proforma, we can see a couple of things: 1) how conservative their projection of adoption was at the time; and/or 2) the acceleration of the network effect’s impact on supply and demand economics.

Both of those things have yielded a much faster acceleration in the price of a Bitcoin, which is now north of $5,000 per.

Utility Token Valuations

So now we’re well into the ICO era, where projects are raising millions of dollars by selling tokens in various legal and financial structures – many of which are a globalized structure to either skirt compliance, or attempt in some fashion to conform to the patchwork quilt of securities and currency regulations.

How do these various economic models impact the valuation of any utility token and project?

First of all, many of these projects aren’t even companies. Crypto asset valuations don’t conform to traditional cash flows, therefore making it extremely difficult for traditional investors to arrive at a comfortable methodology to assess what it’s actually worth. We can’t reliably use Discounted Cash Flow (DCF) as a means of valuing the network.

Valuing a crypto asset requires the defining of models which are structurally similar to DCF in appearance. This includes projection for each year forward, but instead of sales revenue and profits margin, the assumption of an equation of exchange must be used to derive each year’s current utility value (CUV).

Then, since markets price assets based on future expectations, one must discount a future utility value back to the present to derive a rational market price for any given year.

Within its native application network, a crypto asset is the means of exchange, store of value, and unit of account.

Therefore, each crypto asset serves as the intrinsic currency within the protocol economy it supports.

The equation of exchange must be adopted to understand the flow of money needed to support any economy

This is the foundation to crypto asset valuation.


It is still extremely early in the emerging crypto economy. As we continue to explore new asset classes and emergence of new transactional networks, the economic formulas use to arrive at valuations will invariable shift.

However, supply and demand, utility value, market penetration, and network effects are still fundamentally the same.