General token managing mechanisms and token economy
The artificial economies of blockchain are different from traditional economies in many aspects. They are more narrowly focused on only a few or even only one product or service, they can be more flexible and faster adaptable, but they also face many new risks from regulation changes, speculative manipulations or hacking attacks.
This means that many of the tools, theories and methods that apply in economics do not apply in case of token economies. New and innovative models are therefore needed to assess and manage token economics, making designing of token economy one of the most important aspects of a blockchain project. (Mougayar, 2017)
A good tokenomics model will ensure long-term viability of a blockchain project, preventing volatility that could jeopardize the whole project.
A good tokenomics model will also ensure the growth and potential of a project.
Tokenomics are complicated and challenging as there are usually many conflicting interests within the token economy (investors want to see the token raising in value but users might potentially want a low token price). (Kampakis, 2018)
Looking at a token economics from a macroeconomic perspective it is useful to have a basic understanding or the supply and demand interaction. A good framework for this is The Quantity Theory of Money, popularized by Milton Friedman (Friedman & Schwartz, 1971). We can use the Vitalik Buterin’s adaptation of the equation of exchange from monetary economics (Buterin, Vitalik Buterin's website, 2017). He expresses it as:
- M is the supply of tokens,
- V is the velocity of tokens,
- P is the price level of the goods or services in terms of the token,
- T is the transaction volume per day.
This tells us that the token price will be dependent on:
- Total supply of tokens.
- The time the users hold the tokens.
- The total economic value spent with the tokens.
It needs to be noted that The Quantity Theory of Money has been challenged multiple times by J.M. Keynes (Keynes, 2016) and Friedrich Hayek in The Denationalization of Money (Hayek, 1990), stating that the main flaw is the failure to consider different kinds of concurrent currencies. He states that changes in the supply of money affect various and innumerable prices in the economy in different irregular ways, creating misinformation by disturbing the structure of relative prices and therefore resulting in misallocation of resources.
The main challenge in assessing the price of a token is capturing the chaotic process of price discovery, in particular the direct relationship between supply and price level.
Of course, as most tokens are not pure payment tokens, they cannot be directly compared to money either. They have some similarities with shares issues by a company. At IPO the share price is determined with valuating the company and dividing it by the number of shares. Key factors to consider at forming a company’s valuation are (OnMarket, 2021):
- Comparable companies operating within the same or similar industries and providing similar service.
- Financial track record of the Company and quantity management.
- The Company’s growth potential beyond the IPO and how the funds will be used after IPO.
Big differences in market capitalization between stocks and cryptocurrencies and tokens show us that those markets aren’t directly comparable. Firstly, tokens and cryptocurrencies seem to tend to incorporate more potential or future value of the project into the market capitalization and secondly token economics can and will profoundly influence it’s market capitalization. Comparing 2 similar projects with differences in token economics (for instance token holding mechanisms) will have distinctly different market capitalizations.
There are also general factors, out of the projects control, contributing to the token price not limited to economic conditions, regulations, and general market sentiment.
There is no mathematical formula today, that allows for evaluating a price of a token, whatever the legal shape and technical form. Price lookup happens in a highly complex system that has resisted modeling for hundreds of years. The intangible aspect is as important as the utility and should be priced into the model. Until such model exists, price predictions are but an (educated) guess.