Understanding the Dangers of Token Velocityby@itraynis
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1,935 reads

Understanding the Dangers of Token Velocity

by Isaac TraynisOctober 12th, 2018
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<span>A</span> large number of crypto enthusiasts seem to overlook a tiny-little beast known as “<a href="" target="_blank">token velocity</a>.” They have their reasons. Some have never heard of the variable; others are discouraged by its superficial complexity.
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A large number of crypto enthusiasts seem to overlook a tiny-little beast known as “token velocity.” They have their reasons. Some have never heard of the variable; others are discouraged by its superficial complexity.

Serious investors, however, understand the danger that lurks behind variable (V) especially for those projects that use a single token as a medium-of-exchange for some single resource (e.g. Golem Project, Basic Attention Token, etc.).

For such projects, V represents the misalignment of incentives.

So let’s try and understand the nature of velocity. We’ll explore the variable’s history and frame the problem using simple analogy. By the end of this article, you’ll understand the concept and be able to easily reference the fundamental (cryptoeconomic) framework that’s being challenged.

Velocity | Traditional Economies

The crypto-ecosystem is so naïve that there’s still no standard measure for determining network value. Investors are combining traditional economic approaches with qualitative analysis (i.e. behavioral economics) in order to arrive at some reasonable guess.

At the moment, a handful of valuation frameworks are being tested. A few of these frameworks recycle the same formula from traditional macroeconomics. This useful little formula is known as the “equation of exchange,” refined by economists Irving Fisher and Milton Friedman:

Irving Fisher and the equation of exchange.

M = Total money circulating in given economy (i.e. “buying power”)V = Number of times money changes handsP = Average price level for goods & servicesQ = Production output of goods & services

Note: MV = country’s nominal GDP

Economists can calculate every variable in this equation with much greater ease than velocity. This is because velocity cannot be measured directly from some standard economic dataset. Instead, velocity is usually solved directly from the equation once all 3 variables are known.

For reference, the United States has a velocity of 5.581. This means that on average, the same dollar is spent by roughly 6 different people per year. It’s easy to imagine how this all might work: Moses buys bread from Jesus for $1, Jesus then uses that same $1 to buy a popsicle from Mohammed, etc.

Jesus receives dollar from Moses.

At times velocity might increase — releasing more dollars into the economy — thereby reducing each dollar’s “buying power.” Interestingly, as buying power falls, the country’s nominal GDP usually rises. This is because our equation of exchange also serves as an equality: M ×⇡V = ⇡GDP.

The main takeaway here is that despite such changes in your typical economy, there’s always someone ready to offer a good or service and someone with a widely accepted medium-of-exchange (i.e. the dollar) willing to pay.

Velocity | Utility Token Economies

Burniske’s Version

Back in September of 2017, Chris Burniske published an awesome book that detailed a way this formula can be adapted to measure token network value. Specifically, the relationship between each variable is maintained but the definitions are adjusted for this new token ecosystem:

M = Size of token asset base (i.e. marketcap)V = Number of times a token changes handsP = Price of digital resource in terms of tokens (i.e. dollar price level)Q = Quantity of digital resource such as computation, storage, attention, etc.

If we further rearrange the original equation, we can better see the relationship between marketcap and velocity:

Understanding the relationship between M & V.

If this formula holds true for token networks, the problem becomes apparent. As token velocity grows — say from an increase in network usage — the value of the network (marketcap) begins to drop. So the more popular a network becomes, the lower its overall value? That doesn’t make much sense!

Another way of framing the problem is to look at the formula for token value. Since PQ is priced in dollars and MV is priced in tokens, the equality can be used to solve for token value. In other words:

Understanding the relationship between Token Value & V.

As we can see, an increase in velocity — say from improvements in token transactions — results in lower token value. Indeed, we’ve got a serious problem here.

Buterin’s Version

About a month after Burniske’s book, Vitalik Buterin (who is not an alien), put his own spin on this equation to illustrate the issue. The end result is an equation that frames the same problem in a different light:

Understanding the relationship between M & TH.

M = Total number of tokensC = Actual price of token (i.e. cost)T = Economic value of transaction (i.e. transaction volume)H = Average token holding time by network participants (i.e. inverse of velocity)

Note: MC = marketcap

Vitalik’s equation is useful because it clearly illustrates the relationship between network value (marketcap) vs two network usage components: transaction volume (T) and holding time (H).

Intuitively, we understand that as network usage grows so should marketcap. This makes sense in terms of T. As transaction volume grows, more value is fed into the network, resulting in greater network value (marketcap).

However, the incentive structure fails for H. As token holding time increases, network usage begins to drop — since more people are holding onto tokens — yet network value (marketcap) grows? Again, this doesn’t make much sense!

Samani’s Version

A couple month’s after Vitalik’s post, Kyle Samani of Multicoin Capital used a formula derivative to illustrate the most meaningful relationship for velocity. We’ll be referencing this version for the rest of the discussion:

Recall that network value is the monetary value of the entire token ecosystem (i.e. monetary base). Transaction volume, on the other hand, is best thought of as the actual utility that users get from using the network (i.e. network GDP).

Let’s now explore this velocity problem through the lens of simple allegory and review some solutions that have started to come online…

Where Incentives Fall Apart

In traditional economies the dollar keeps on moving through the ecosystem. In our token economy, however, things begin to fall apart because tokens do not move through this ecosystem unimpeded.

The cycle is basically broken. Referencing our original example (see above), we can draw a corollary between a traditional economy and this emerging token economy. Imagine now a world where Jesus, the proprietor of bread, decides to only accept a special token for the sale of his bread.

Whereas in a traditional economy, Jesus could use dollars to cover his bread-making expenses and use profits from the sale to invest back into his business and even make a donation to some synagogue, he is now left holding a token. This places pointless friction on everyone and leaves him with few options:

  1. Sell token to another proprietor of bread — in exchange for bread.
  2. Sell token to person who wants to buy bread — in exchange for dollar.
  3. Sell token to a money changer (i.e. exchange) — in exchange for dollar.

Jesus considering his token options.

So what would Jesus do? Certainly Jesus wouldn’t choose the first option since he himself is already the proprietor of bread. The last two options seem like much more reasonable alternatives.

Option 2

Jesus would have to find a person in need of bread and then exchange his token for their dollar. Once the person has this token, they are then able to purchase more bread from Jesus. Jesus can then use the dollar to cover his expenses and hopefully have a little profit left (to give to charity of course).

The process here is quite cumbersome. Jesus has to find every person in need of bread and then go through the motion of exchanging his tokens for dollars. Oh lord, a money changer might come in real handy right now.

Option 3

Rather than deal with the complexities of the second option, Jesus might actually befriend a money changer (i.e. exchange). The money changer is more than happy to assist with the exchange process but for a price!

Initially, things are good. A bunch of people (i.e. speculators) are attracted to the business because unlike their local baker, Jesus’ business sells bread using a decentralized token network! It’s all the rage on Nazareth right now.

Jesus bread.

Some even flock to the money changer to buy more tokens than they actually need for bread! These potential customers have clearly become full-blown speculators. They hold a simple assumption: sell excess tokens for profit or just breakeven. What could go wrong?

For a brief moment, Jesus (along with his money changer) is swimming in dollars before having to bake any bread! Eventually people begin redeeming their tokens for bread and Jesus gets back to baking bread.

As long as people continue exchanging their dollars for tokens, the business will grow in value. This is restated very precisely: when transaction volume outpaces velocity, overall network value will continue to increase. Here’s Samani’s version again for reference:

Now imagine a situation where advances in cryptoeconomic infrastructure reduce a list of high-friction processes: transaction costs, cognitive burdens, liquidity problems, etc. Since friction is inversely correlated with velocity, these developments lead to a rapid increase in velocity.

As long as the transaction volume grows linearly with velocity, no change will happen for network value. Superficially everything might seem to be kosher. In reality, more people are participating in the network but no real change is reflected in marketcap. What is happening here now is the slow but certain disentanglement of the network’s incentive structure.

The Velocity Thesis

At the heart of this serious issue, called by many now as the “velocity thesis,” is the gradual decoupling of the token’s utility value (e.g. to purchase bread) from network value. The thesis predicts the following eventual result:

⇣(Friction) → Rate( MV > PQ) → ⇣(Token Value) → Network Collapse

In traditional economies velocity isn’t a major issue since equilibria between friction and velocity is firmly in place. This problem also isn’t a huge issue for store-of-value cryptocurrrencies (e.g. bitcoin, ether, etc.) since the purpose of the transaction is the token itself rather than some token-exchangeable end-product like bread.

The Jesus allegory is designed to serve as a handy paradigm for the many proprietary payment token networks out there — too many to list. The moral of the story is simple. If you’ve decidedly chosen to buy a token from any of these projects (other than to immediately spend), you should reflect upon your actions and “just call it.”

Just call it what it is…speculation.

And now as a self-avowed speculator, you need to ask 3 important questions:

1. My investment thesis is based on fundamental value or holding desirability?2. What portion of network value is the product of pure speculation?3. When might velocity begin to overtake transaction volume?

These are very difficult questions to answer. Luckily some very smart people have begun to systematically address such questions. We’ll review this new discussion and explore solutions currently being tested in future writing. Thanks for reading and stay tuned 😉

For Further Reading