One of the biggest challenges in the world of crypto is keeping things simple, and nowhere is this more true than when it comes to valuation and pricing. The analytical tools currently used tend to be complex, and the more complex the analytical tool, the more likely something will go wrong. Discovering the value of a token should not require us to have a “Beautiful Mind”.
The purpose of this post is to describe the analytical tools available for valuation and price discovery of utility tokens and analysis of the best ones to choose for your use case.
Why is this important?
Sales of tokens are booming, but the way in which they’re sold is inefficient. Valuation and pricing decisions are made in isolation and, in any case, generally use the wrong information and analytical tools. This has led to confusion among buyers, extreme price volatility, and in some cases significantly reduced income for sellers. For example, many investors are now waiting for secondary market pricing to buy into certain tokens for fear of subsequent price collapses or “pump and dumps”.
Before getting into analytical tools for utility tokens, here is a quick primer on the terminology used in this post:
Valuation - Valuation is part art, part science. It’s the act of stating how much something would be worth, if sold for money. Valuations can be absolute or relative in nature (more on this below).
Price discovery - Price discovery is based on supply and demand. It’s the act of determining the price of an asset in a marketplace through interactions of buyers and sellers.
It’s important to understand that price discovery and valuation have the same goal of determining fair market value, but different ways of arriving at that number. The price discovery process involves buyers and sellers coming to an agreement on a transaction price, creating an empirical measure. Valuation, generally speaking, is an opinion of how much something is worth, a more theoretical number.
Utility tokens are digital assets that give holders access to products or services within a particular platform or network. They don’t have underlying cash flows, earnings, or easily quantifiable metrics like traditional financial instruments, and this makes their valuation challenging to determine with established analytical tools.
That’s a big reason why, when it comes to launching a token, price discovery tools are a highest priority. Once a price is established, using valuation tools for various requirements (tax, M&A, litigation, financial reporting) or evaluating investment opportunities becomes easier. Here are the price discovery options available for utility tokens starting with the most preferred in bold.
Price Discovery Tools
The lack of information transparency around the pricing of utility tokens means it can be hard to make informed valuation decisions, and this in turn puts a drag on trade. The information that really matters to utility token sellers is determining what a willing buyer wants to pay for a token -- auctions fulfill this purpose.
Blind Auction - Hides the bidding history of other participants.
English Auction - Sellers auction off bundles of utility tokens to a group of potential buyers in an ascending price format.
Dutch Auction - Sellers auction off bundles of utility tokens to a group of potential buyers in a descending price format.
Channel Auction - Combines aspects of English and Dutch auctions into a single auction format.
Auction sales have challenges, however. The most common one is that buyer can game the system by taking advantage of information asymmetries. Furthermore, unlike established markets, there’s no price-indicating trading history, prospective buyers may not know how to value the tokens.
Both of the above can be mitigated with clever auction design, however.
Different auction tactics exist, and are described below.
Dynamic pricing lets the demand for a token and the token sale performance dictate the final token price (as opposed to the seller setting price). Prior to the sale, buyers are notified of the maximum price they would pay if the sale target is reached. It is calculated as:
Maximum Token Price = (Fundraising Target) / (Number of tokens being sold)
If the sale target is not reached the final price a purchaser would pay is calculated as:
Final Token Price = (Total money contributed to the sale) / (Number of tokens being sold)
This is a simple and fair token pricing structure for purchasers. In addition to every purchaser paying the same price per token, another benefit is that if the sale target is not reached, purchasers get a better token price than originally anticipated.
The needs of the platform determine token pricing. In a way similar to how venture capital works, the token seller will specify the amount of funds needed to get the platform to a certain milestone (i.e. release MVP, generate revenue, cash flow positive, major technological development, etc.). It is calculated as:
Final Token Price = (Funds needed to reach milestone) / (Number of tokens being sold)
The milestones and number of tokens being sold varies, but generally will be less than a typical token offering. The idea here is to show the market you are capable of executing on your plan with less upfront capital. A higher number of tokens is held in Treasury for future “rounds”.
This is another simple pricing structure but relies on the team and realistic goals for an investment to make sense to purchasers.
For effective valuation, data is needed from operations of the platform in question. In the case of utility tokens, there’s a limited amount of the most important data (input variables) that drive valuations because of the lack of both uptake and reporting and the sheer newness of the industry.
Because of this, there is still a long way to go to test and/or establish better valuation criteria and frameworks. But even though valuation in crypto is a new concept, the frameworks below still have merit.
Valuation tools can be grouped into two different types. Absolute and relative. Both can be used when there is existing platform data to draw upon.
In traditional finance, absolute value models try to determine a company or asset’s intrinsic worth based on its projected cash flow. Since utility tokens do not have cash flows in and of themselves, we must take a different approach.
Equation of Exchange
One of the best-known methodologies for determining absolute utility token value is from Chris Burniske. He proposed a model based on the equation of exchange (MV=PQ). As it pertains to a token economy, this equation showcases the relationship between token supply, the velocity of the token, the price level and an index of expenditures within the economy. The model now has a couple variants, based on the inputs, described below:
1.Static Velocity -In the original model from Chris, one of the inputs used, Velocity, is static. A critique of this is that when the platform assumes growth or the token utility changes over time, velocity should technically change as well.
2. Dynamic Velocity- Another variant of the Equation of Exchange introduces a changing velocity over time. A critique of this is that the complexity to calculate a dynamic velocity may make the valuation less sound compared to static velocity.
Forecasting Equation of Exchange inputs with any accuracy and projecting how long the inputs will remain on a growth trajectory is challenging, especially without any actual platform data. Using this model prior to launching a utility token is an academic exercise and not actually reflective of fair market value. Using it with actual platform data could make the model more robust, but the complexity is still a hurdle to overcome.
In traditional finance, relative valuation is a method of determining a company or asset’s value by taking into account the established valuations of similar companies or assets. When it comes to utility tokens, a completely different set of ratios and data are analyzed, versus Absolute Valuation.
Platform Value-to-Transaction Ratio (“PVT”)
PVT (also known as NVT) is a relative valuation ratio that compares the platform value to the platform’s daily transaction volume. It works according to the following formula:
Platform Value-to-Transaction Ratio = (Platform market cap) / (Daily transaction volume)
PVT may indicate whether a utility token is over- or under-valued by showing the market cap relative to the platform’s transaction volume. The ratio is intended to represent the utility users get from the platform. When the ratio becomes very high (or low), it indicates potential over (or under) valuation of the token.
For example, imagine that two comparable platforms, ABC and XYZ, have native utility tokens with PVT ratios of 2.0 and 1.0 respectively. Base on this, one could say ABC is overvalued compared to XYZ.
This analytical tool has its downfalls, however, specifically when it comes to calculating transaction volumes. For example, Bitcoin uses an unspent transaction output model (UTXO), meaning that there is a possibility of the transaction volumes being overinflated. For more on this check out this article.
Daily Active Addresses (“DAA”)
DAA is an indicator of the number of users that make transactions on the platform on a daily basis. This is similar to how software companies gauge success based on the amount of users they have. Used on its own, DAA is basically a vanity metric, rather than a relative valuation methodology. When multiplied by a value per DAA, an overall valuation can be determined. The value per DAA is subjective; we’re not sure if there are any industry benchmarks at the moment. This can be expanded to the Metcalfe valuation described below.
Multi-Factor Model (“MFM”)
In traditional finance, an MFM combines individual factors that contribute to a company or asset’s relative valuation. For instance, the CAPM model includes factors for expected excess return, risk premiums, liquidity premiums, book to market ratio, etc. A similar exercise can be completed using different factors, with different weights. This would include the following:
Utility Token MFM = PVT Factor + Metcalfe Factor + Exchange Factor + Community Factor + Token Retention Factor
PVT is described above. Each other factor is explained below:
1. Metcalfe Factor - The ratio of platform market capitalization to 7-day moving average of DAA, squared. This is useful to analyze the market value growth as a function of users.
3. Exchange Factor - The ratio of listings of the utility token on the top 25 exchanges, by trading volume. This is useful to gauge how liquid the token is.
4. Community Factor - The 7-day moving average of Telegram channel views to the total Telegram channel subscribers. Note, bots can be an issue here. This is useful to gauge how much user support or momentum a project has.
5. Token Retention Factor - The percentage of token offering participants that still hold their tokens 50 days (or 100/200/300 etc.) after the tokens have been distributed and unlocked. This is useful to gauge store of value characteristics. Note, wallets aren’t 1:1 with people. This only accounts for on-chain transactions and could be tough to compare timelines.
While this list is not comprehensive, it can be a preliminary guide for people interested in how utility token pricing and valuation actually gets done. This is still uncharted territory, remember, so nothing is off-limits in terms when it comes to developing better analytical tools.