The intelligent token investor: A beginner’s guide to token utility token valuations
With very the meteoric rise of crypto assets, the perennial question returns: are we in a cryptoasset bubble? With Warren Buffett famously arguing that the notion that bitcoin has any value “is just… a joke[.]” Even ECB’s vice-president warning that bitcoin is nothing more than a speculation. On the other hand many have argued that cryptoassets are the future. Peter Thiel arguing that these protocols can be very charismatic and often are undervalued.
Often the problem with this debates are people argue past each other and there being no clear framework to assess their arguments. Whether you are holding on to bitcoin for dear life or participating in ICOs. In this article we will explore some of the ways to assess the value of cryptoassets.
(Think of this more as a primer for understanding token valuations rather than a definitive guide to understanding valuations.)
Before we move on some definitions. There are three types of cryptoassets:
- Cryptocurrencies. e.g. BTC, Zcash & LTC
- Tokenized securities
- Utility Tokens e.g. Filecoin, Golem,
First, on cryptocurrencies are the most prominent forms of cryptoasset. These include currencies that like Bitcoin that functions mainly like cash and just like its fiat counterparts has little inherent value. Second type of cryptoassets are tokenized securities. These are very similar to investing in a share of very early stage startups.
The last type of cryptoassets are utility tokens. These represent a unit of goods/services that can be purchased within the network.
Given that this article will be a beginner’s guide, I will focus on utility tokens. As it is relatively simple to understand, as the value underpinning a cryptoasset is clearly defined. Once we have understood this model it will become easier to understand the rest.
Simple Quantitative analysis
As much as I love fundamental analysis in essay form, after trolling through many articles arguing for and against the legitimacy of a given cryptoasset price, there is the same recurring problem: so many people just argue past each other.
Due to the speculative nature of these analysis, there is no point in spending hours and hours in drilling down on the specific number. However, doing a simple quantitative analysis can really go a long way in making your assumptions explicit. Placing your arguments in a specific context. Helping you to stay calm in the face of wild price fluctuations.
For my quantitative mode, I borrowed heavily from Chris Burniske Utility Token model published here. Although the articles like these are great, too heavy for those of us don’t have economics/finance background, the underlying intuitions are really simple.
There are three critical intuitions:
1. There is a direct relationship between the quantity of token in the economy and the price of goods and services it covers. i.e.The price of a utility token must be directly proportional to the size of the market it covers.
Total value of Tokens = Total value of Addressable market size
For instance, let’s take the example of Filecoin and for the sake of argument with Filecoin tokens all you can buy is the storage services. If you assume this to be $75 billion and Filecoin takes 50% of the market (commonly referred to as Total Addressable Market), the total supply of Filecoin token should be worth $37.5 billion.
This seems to be a reasonable assumption given that all you can buy are storage services and nothing else. Imagine the valuations of Goldman Sachs exceeding that of the whole of the financial sector.
2. Value of an individual token must be influenced by number of token in circulation.
Total value of Tokens = Total supply x Velocity of circulation.
As I mentioned beforehand, the supply of the token is hugely influential in determining the price of the an individual token. Following the example of Filecoin, if there were only 100 token then each token would be worth $375 million. However if there were 1 billion token it would be worth only $ 37.5. A huge difference!
Another important factor in determining the price level is the velocity of circulation. If we assume that there are $100 in an economy that changes hands 10 times then there are $ 1,000 in the economy. The same can be applied to an utility token .
3. Technology adoption follows a S-curve pattern.
There are seemingly a clear pattern in breakthrough technologies; it comes out of nowhere to completely dominate the market and slows down. Take the example of smart phones. Since the inception of the iphone 10 years ago now it seem ubiquitous. This happens initially quite slowly then speeds up very quickly and then slows down.
So going back to the total addressable market size. An individual service won’t dominate the market overnight but it the most ideal case it is likely to follow a S-Curve.
However, even in this model there seem to a high degree of variability. Below is an example of several breakthrough technologies.
4. We need to think about the discount rate.
Let me start with a riddle. In 2013 Twitter went public, and was valued at $24 billion while making a loss. In the same year, New York Times company on the other hand, made $133 million in profit was valued at 12th of Twitter. How could this be the case?
The answer is Cash flow. A declining business might have a cash flow along the lines of this.
However, a fast growth business may look something like this.
Therefore, very often technology companies will be valued many times higher than its more traditional counterparts. Leading them often labelled as bubbles.
People can too often mislabel technology companies as a bubble however their fear can some times be justified. For instance, for Twitter’s case reality proved more challenge then expected. Twitter failed to live up to the hype/build on its momentum since its IPO. The Growth slowed and its valuation plummeted.
So in order to value fast growing tech projects we need to think about the discount rate.
The discount rate accounts for a)risk and b) impatience. Regarding risk, as we can see in the case of Twitter technology projects often fail but if they are successful the growth can be tremendous. In order to value these assets therefore we need to assign a probability to their success.
Current value of a crypto asset = Price of the project if successful x chance of success.
Second we need to think about impatience. Although this plays a big part in valuing more traditional assets such as government bonds, the speed at which the crypto asset grows this is far less applicable. Creating unecessary complexity for beginners.
To emphasize these Mathematical thought experiments. But these are essential for making your assumptions underlying your arguments explicit. When going through an analysis of a cryptoasset it can really be a helpful exercise.
Conclusion:
Gripped by the frenzy of the crypto-market, many seem to be blinded by greed or fear. An average of 1/3 whitepapers downloaded for every person who invested in a project (presumably even less who read it thoroughly). People seem to be investing blindly. However, I understand the frustrations of people who are busy and don’t have time to spend hours reading whitepapers, building financial models and doing the due diligence. As someone who really believe that the ICO model can democratise access to the investment in early stage projects and new model to decentralise ownership.There must be some simple way all of to do this. This was our small way to move the needle forward and bring more clarity to the market.
Sources:
https://medium.com/@cburniske/cryptoasset-valuations-ac83479ffca7
https://news.earn.com/thoughts-on-tokens-436109aabcbe
http://time.com/money/4942572/bitcoin-bubble-experts-warned/
https://www.ft.com/content/18507a26-9fb4-11e7-8cd4-932067fbf946
