When the crypto community is blinded with ICO hype, there are few attempts to determine the best methods for evaluating cryptocurrencies and finding those with a utility value. I believe many more attempts will be made when the industry matures, but I am still shocked how little has been written about this topic compared to the $150bn plus market capitalization. On the other hand, the current environment doesn’t really incentivize such attempts, and therefore it is probably better to spend time for an ICO instead.
One insightful concept of token valuation is Chris Burniske’s Crypto J-Curve. The model splits token value into current utility value and discounted expected utility value. My question is how much of the value can really be attributed to the current environment, where many market participants don’t really care about or understand the specifics of a token’s utility as long as there is a common perception of successful fundraising and exchange listing. Sometimes I think a successfully funded ICO is like the concept of money: if you believe it works, I do too. But the “issue” is that you think the same way I do and we both invest under the assumption of a common belief, not because we understand the utility of the token. It’s a bit of a bold statement and probably too much of a generalization, but it holds true for a large number of projects out there.
Burniske’s model for Storj valuation is another good attempt at approaching valuation by discounting each year’s transactional value of a token. In short, he estimates the global market for cloud storage and the share of this market taken by Storj customers and applies discount to each year’s token usage in dollar terms. He basically performs discounted cash flow analysis on estimated consumption of tokens. This is clean, simple and contrary to classic equity valuation, where free cash flow for equity holders is considered. Here Chris considers the actual “consumption” of tokens each year by buyers and discounts it.
The important factor when using this kind of model is the discount rate, which is 30% in his case. Those familiar with these methods know that discount rate is the most sensitive input — it doesn’t matter how accurately you estimate client growth and other inputs if a change in the discount rate of 10% changes your end valuation by 50% or more. This is why I also like Jonklaas’ piece on token value, which does a great job parametrizing all inputs using the discounted cash flow model. I especially like his attitude toward discount rate. He proposes a definition of qualitative and quantitative factors of particular companies that then determines an appropriate discount rate using different bands.
Every attempt at valuing utility tokens I have discovered so far is a great contribution to this new asset class, but all of them are missing one key input: the activity of the network, represented by velocity of token.
As I wrote in my previous article, protocols on which cryptocurrencies with a utility function are based, resemble micro-economies. A token is just another currency used in the economy that specializes in the exchange of a particular service. As William Mougayar pointed out, the token enables the creation of private (transactional) economies.
This turns classic enterprise valuation upside down, since we don’t value cash flow to investors but use of the token by consumers. In token evaluation, we want to measure how large and active the exchange of service is, reflected in the aggregate value of transactions (can be in $ terms) and the number of transactions of each token represented by its velocity.
Yannick Roux from Token Economy wrote a great article in which he showed that if one owned all the tokens outstanding of a certain network this would dry up and kill the economy because there would be little or no activity. Normally, if you acquired 100% of a company’s shares, you would have to pay a premium for control, but if you were to acquire 100% of a network’s tokens, your paid price would be at a considerable discount in relation to current market capitalization, since your “takeover” of a network would indirectly affect the activity of exchange and cause network output to slow down.
This is why I believe such ecosystems should be treated as micro-economies or network economies in which the value of exchange plays an important role but also the velocity of the token used. Imagine two identical Siacoin protocols, where the aggregate transaction value in each protocol are the same but one has 10,000 active users and one has 100,000 active users. Surely, the second will be worth more, since activity on the network is higher despite the same aggregate exchange of value. Why is that? Because such protocols are nothing less than platforms that have their value determined by network effects and number of interactions between parties on both sides of the market.
So how can we incorporate activity in the network value? There should be some kind of adjustment of network’s transaction value for its activity of users. When valuing network we look at transaction value of each year, but we should account for the velocity of tokens. The more tokens circulate between users, the more interactions, the more network effect and healthier network.
The quantum theory of money says that spending equals the supply of money times its velocity. This is how spending of any country is measured. Same formula could apply at any crypto network, where token velocity could be obtained and should have an important meaning for future of the network growth since blockchain protocols are open and allow social scaling. I believe there should be more focus on analyzing network output rather than on market/network capitalization. As shown, capitalization of a network doesn’t actually tell you much. When we compare economies we usually compare capabilities to produce, not how much economy “costs to acquire”. We don’t measure market capitalization of euro.
Utility value is therefore not the only variable for a successful protocol. Protocols must also have a well established underlying “monetary system” that controls token scarcity and its issuance or burn metrics. This is what’s missing from most tokens out there today: teams rush to launch a product but rarely address the flow of tokens. Normally you would need to carefully examine and analyse the supply and demand of the particular service offered on your platform. There may be a need for a role that functions like a “chief economist” who sets protocol to manage monetary metrics.
Thinking further, what ratio of investors relative to actual consumers should a particular network economy consist of? In monetary systems, managing inflation is important because you want to prevent people from hoarding tokens. You don’t want your token to become speculative or a store of value asset, but rather a token that is consumed. Imagine having a large amount of investors who are hoarding tokens, and suddenly, because of a volatile event, they all liquidate their positions due to safe haven flight. Wouldn’t it be better to have actual consumers holding tokens who wouldn’t care if their tokens’ relative price fell, since they need the service anyway?
When I think of such networks and how tokens will affect daily life, I am still uncertain how this path will unfold. Are we really going to have millions of versions of tokens, each for one particular service? Doesn’t this lead us back to bartering?
I think bartering will be just another option among many. You will be able to exchange your 1% stake in some house for one year’s usage of a car. Tokens will fly and exchange will occur in the background without you knowing. This could be done with massive liquidity coming in and many assets being tokenized.
Which brings me to another troublesome topic. The growing liquidity that we are witnessing at this moment has little to do with fundamentals, but a lot to do with speculation. Furthermore, there are many unsophisticated investors in the crypto space, which can be a good thing as they bring additional liquidity but can also lead to increased irrational behaviour and market inefficiencies. The function of investing is capital allocation, and I believe that a lot of capital is currently being misallocated and that there will be little or no added value delivered in many cases where we are mostly seeing redistribution of capital from gamblers to promoters. But that’s another topic.