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Cryptoeconomics: Three Real World Examples

14 December 2018 20:17, UTC
Cryptoeconomics: Three Real World Examples
By Charles Voltron

As blockchain-based ecosystems continue to propagate a new, hybrid discipline is beginning to take shape. This discipline is being referred to as tokenomics/tokenization or cryptoeconomics.

Personally, I like to use the term, cryptoeconomic incentive engineering. That seems like a more accurate description but for brevity in this and forthcoming articles I'll stick to the shorter and more popular terms, tokenomics and cryptoeconomics.

Cryptoeconomics as a nascent field of practice, isn’t really a new science in and of itself. It’s a mashup of several existing disciplines such as:

  • Cybernetics

  • Economics

  • Game Theory

  • Public Policy Design

  • Mechanism design

  • Behavioral Psychology

  • Evolutionary Algorithm Design

  • Optimization Design

These and other disciplines are combined and augmented to achieve optimal outcomes in a blockchain network making use of a digital token. Polymaths rejoice! As a polymath I can’t think of a more exciting space to be in right now. Blockchain technology allows us to do things with economics that you just can’t do with traditional monetary instruments by way of programmable rules and incentives built directly into the network, the currency and within the transactions themselves.

Traditional economic theory doesn’t scale to programmable currency hence the emergence of this new and novel field of study. In this 3 part series I will present a general overview and popular thinking around the current state of tokenomics and provide various resources for further investigation. Understanding tokenomics is important for both designers of blockchain ecosystems as well as the investors who fund and buy into those ecosystems.

Part 1 - Understanding Token Velocity

Token velocity is one of the most important factors in the success or failure of a token ecosystem that doesn’t get as much attention as it deserves.

We see a lot of focus on supply and demand in token economies but depending on the mechanics of the ecosystem, if token velocity is too high then no matter how much demand you have for a given token, realizing the overall value of the network will be difficult.

So what is Token Velocity? In simple terms it is the rate at which a token is exchanged for something else of value.

The higher the token velocity the shorter the amount of time participants in a token economy hold on to the native token within that economy. For this primer we will focus on two popular equations relevant to token velocity as an intro on how to approach the topic for the first time.

There are other ideas around how to calculate token velocity and I invite you to check out the resource links below to get a broader scope.

Most token velocity theories are based on the existing Quantity Theory of Money.

This is the equation:


M - Money Supply

V - Velocity of Money

P - Average Price of Goods

T - Index of Expenditures

From this starting point, the first well received theory of token velocity was put forward by Chris Burniske who was the first public fund manager to invest in Bitcoin and is the author of the book, Cryptoassets.

Burniske suggests a token valuation formula in this format:


M - Market Cap

V - Token Velocity

P - Price of Goods

Q - Quantity of Resources

To solve for overall value you would arrange in this fashion:

M (Market Cap) = PQ/V

The takeaway here is that division by V (Velocity). If token velocity increases it directly impacts the value of the entire project.

The second popular token velocity theory was put forward by Vitalik Buterin who, as you probably know, is the co-founder of Ethereum.

The proposed formula is as follows:

MC (Market Cap) = TH

M - Total Number of Coins

C - Price Per Coin

T - Transaction Volume

H - 1/Token Velocity

If we multiply M * C we get our Market Cap and to solve for value we would use:

MC (Market Cap) = T/V

Here again we see the prominent divisor of V. The lower the token velocity the higher the value.

Doodat - An Example of a High Velocity Token

Let’s imagine we have a blockchain-based task running application called Doodat. If you have errands that you don't have time to run then you can hire someone on Doodat to get your stuff done. If you want to earn extra cash you sign up to be a runner on Doodat.

Since our app is on the blockchain we can have a native cryptocurrency called Datcoin which is what you would use to pay a task runner to do your stuff with. (I'd say this is also an example of an app that never needed to be on the blockchain to begin with but more on that later...)

In this example the native token acts inadvertently as a conduit of value because you would only ever purchase Datcoins to hire a runner and runners will cash out of Datcoin into fiat as quickly as possible in order to pay their bills.

In other words, there is no incentive to hold Datcoins over a longer period of time which translates to a high token velocity.

Even if Doodat became immensely popular and did hundreds of thousands of transactions a day, the token will struggle to capture value.If I was an early-stage investor reviewing Doodat's deck, I'd be interested to know how they were planning on mitigating the obvious potential for high token velocity.

Ways to Manage Token Velocity

There are several ways that token ecosystem designers manage utility token velocity.

The methods below are by no means the only ways to control velocity and are often combined together to create custom hybrid solutions depending on the use case.

  • Staking - Staking tokens can be used in a variety of ways. It's used as a the core mechanism in the Proof of Stake consensus algorithm and provides a "skin-in-the-game" component to incentivize users to follow network rules.

It typically involves locking up a certain amount of tokens for a certain amount of time. Beyond being used in a consensus mechanism it’s a way to take a certain amount of tokens out of circulation for a specified amount of time in order to reduce velocity.

  • Rebate Staking - In this approach users are incentivized to hold a certain amount of tokens for a certain amount of time (longer than the average global token velocity) in order to get discounts on goods and services offered by the platform.

  • Revshare Staking - This method involves users staking tokens, usually in an aggregate liquidity pool in order to gain share in global revenues generated by the platform. As CTO of I got a first-hand look at how a strategy like this is put together. It’s a solid approach to reducing token velocity and it adds value to network participants.

  • Burning or (Burn & Mint) - Factom uses a very well designed Burn and Mint algorithm that is designed to manage the supply and demand equation of their network. A certain number of tokens are destroyed according to certain rules and a certain amount of new tokens are created according to other rules.

Simply Burning tokens is another popular strategy which is designed to reduce supply.

Burn & Stake - a Real World Example

In my role as Chief Architect of we recently devised a new strategy to reduce token velocity in the form of a combination of burn and stake.During the initial conceptualization of the Platio ecosystem a token burn mechanism was put in place to tweak the supply and demand balance. The Binance cryptocurrency exchange employs a similar burn technique with their native BNB token.

As the architecture of the ecosystem evolved, we noticed that since the Platio token was being used primarily as a conduit of value between other assets that it would naturally incur a high token velocity that burning might not entirely address.

Remember, high token velocity will dampen any increase in value deriving from a supply and demand mechanism. To solve the problem we introduced levels of staking. New users can join the platform at a basic level without the need to stake coins which incurs normal market rates for fees.

Above the basic level we then replaced a subscription model and created 2 levels of staking where users could stake a certain number of Platio coins for 30 days and be rewarded with access to more services beyond what the basic level provides as well reduced rates on fees.

At the end of the 30-day period we incentivize users to continue staking by issuing credits that can then be used to receive some services for free.

Combined with a reduction in supply over time via the burn mechanism we now have greater leverage over token velocity with 2 levels of 30-day staking periods that remove a predictable number of coins per user from circulation for a specific amount of time. Obviously we want users to continue staking over as long a period of time as possible (essentially reduce churn) which is why we incentivize them to do so by rewarding them with credits that can be used to further reduce their costs.

The margins we give up in the short term are worth the long term value driver of controlling token velocity which will benefit users and investors alike.

Stay tuned for part 2 in this series where we'll take a closer look at the tools, theories and thought leaders defining the exciting new field of Cryptoeconomics.

Charles Voltron is a blockchain technologist with 17 years of experience in software development, technical leadership and entrepreneurship.

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