Designing a Token Economy Model

Tokenize Your Business

We have already talked about tokenization and how almost everything can be represented on the blockchain as a token. Tokens can represent currencies, assets, collectibles, game characters, securities, voting rights, and many other concepts.  An increasing number of companies are taking advantage of this and designing on-chain token-based economies. Designing a model to support such a token-based economy is similar to creating a business model. However, whereas business models may adapt over time, it is not so easy to modify an already deployed token economy model. There are a number of issues that require careful attention.

Token Considerations

As in all economic models, one of the first steps is to define a list of stakeholders involved. Economies should somehow balance demand and supply and create a circular model, in which everyone who receives the token should have a way to spend it somehow, even if there may be some holding involved.

Initial Coin Offerings (ICOs) usually find themselves with the first conflict of interest when they come up with their list of stakeholders. Usually, investors buy the token because they believe the price will increase. Platform users, on the other hand, usually want the price to remain relatively stable. These conflicting expectations need to be managed. Some projects, such as Black Insurance, create two tokens, a utility token for platform use and a security token for investors.

This leads us to a related issue: the actual use of the token. A token often serves as a way to raise funds. Such a token risks being classed as a security by regulators like the Security and Exchange Commission (SEC) in the United States. In some jurisdictions, this means the token can only be sold to accredited investors. Recently, an increasing number of companies have started to accept this fact and embrace security tokens.

A token that has some use on the actual platform is a utility token, and, as mentioned above, stakeholder expectations are entirely different. Tokens may also provide holders with governance rights and allow them to vote on certain issues. Others are meant as incentives, encouraging holders to perform work for the community, such as Augur’s REP token.

Designers of a token model should think about the factors that may influence the future valuation of their token to come up with a price prediction. Often this is done in reverse. An idea of how the model designer wants pricing to develop leads to adjusting key parameters.

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ERC-20 coin volatility has caused headaches for those trying to use the network. Image credit: Wikimedia Commons.

 

Formula for Success

In any case, the parameters involved depend on the use of the token. Etheruem’s co-founder, Vitalik Buterin, has come up with a formula to describe the behavior of tokens used as a medium of exchange, i.e. a currency. In his model, the formula MC=TH describes a token’s behavior (M = total supply, C = price, T = transaction volume, H = hold time before transaction is made). Thus, the price can be calculated as follows: C = TH/M.

This simple model works quite well and confirms an intuitive affirmation: the longer people hold a token, the higher its price. This means that velocity is an important parameter. If the objective is price stability, the token must be kept in motion.

The other important factor is supply. It is therefore important to carefully define a token’s issuance model. Should there be predetermined total supply (deflationary model) or should new token be minted according to certain criteria (possibly inflationary depending on issuance rata)?

Designing a token economy model is not an exact science. As with all new disciplines, many questions remain unanswered. Moreover, no single model can cover the great variety of use cases in existence.

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Dr. Stefan Beyer
Dr. Stefan Beyer is editor-at-large at BlockTelegraph and a Blockchain consultant and smart contract auditor. He graduated from the University of Manchester in 2001 with a degree in Computer Science and obtained a Ph.D. in 2004 from the same university with the title “Dynamic Configuration of Embedded Operating Systems”. Since then he has worked in computer science research in distributed systems, fault tolerance, ubiquitous computing and cyber security. He is currently working as head of research and development for a medium-sized cyber security company in Spain.

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