General token managing mechanisms and token economy
The artificial economies of the blockchain differ from traditional economies in many aspects. They typically focus on one or a small number of products or services, making them more flexible and adaptable. However, 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 translate to token economies. Hence, they require new and innovative models to assess and manage them, making developing token economy models one of the most important aspects of a blockchain project. (Mougayar, 2017)
A good tokenomics model will ensure the 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’s value rise while users may want a low token price). (Kampakis, 2018)
Looking at token economics from a macroeconomic perspective, it is useful to have a basic understanding of the interaction between supply and demand. The Quantity Theory of Money, popularized by Milton Friedman (Friedman & Schwartz, 1971) provides a proficient framework. We can use Vitalik Buterin’s adaptation of the equation of exchange from monetary economics (Buterin, Vitalik Buterin's website, 2017). He expresses it as:
MV = PT
- 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 money supply will affect various and innumerable prices in the economy in many irregular ways, creating misinformation by disturbing the structure of relative prices and therefore resulting in the 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, we cannot compare them directly to money. They have some similarities with shares issued by companies. At IPO, the share price is determined by the company value and dividing it by the number of shares. Key factors to consider while forming a company’s valuation are (OnMarket, 2021):
- Comparable companies operating within the same or similar industries and providing similar services.
- 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.
Significant differences in market capitalization between stocks and cryptocurrency tokens prove that these markets are not directly comparable.
Firstly, tokens and cryptocurrencies tend to incorporate more potential or future project value into the market capitalization. Secondly, token economics can and will profoundly influence its 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 project’s control) in addition to economic conditions, regulations, and general market sentiment contributing to the token’s price.
Currently, no mathematical formula accurately evaluates a token’s price, 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 a model exists, price predictions will remain (educated) guesses.