Token Utility: Balancing Supply, Demand, and Velocity

Kajetan Olas

14 Mar 2024
Token Utility: Balancing Supply, Demand, and Velocity

This article embarks on a journey through the multifaceted landscape of token utility. It dissects the influence of supply, demand, and velocity. We include practical information that can be utilized during the process of crypto assets valuation.

The Supply Side: Scarcity and Abundance

The concept of scarcity as a value driver is deeply rooted in human psychology; it's what transforms simple metals into precious commodities. In the realm of cryptocurrencies, this principle has been adopted with fervor, giving rise to the "digital gold" narrative. Let's delve into how supply shapes the world of token utility and the broader implications it holds.

Fixed Supply and Deflationary Models

  • The Allure of Limitation: Crypto-architects often imbue their tokens with a fixed supply, aiming to mimic the scarcity of resources like gold. This artificial scarcity is designed to create a deflationary environment. It holds the premise that as demand escalates, so too will the value for the lucky holders.
  • Scarcity and Value: The perceived value of supply-limited tokens is based on a simple market principle. When an item is rare, and demand outstrips supply, prices should theoretically rise. This underpins the investment cases for many cryptocurrencies.

Token Sinks and Their Limitations

  • Combatting Inflation: Token sinks, such as burning and staking, are strategic maneuvers employed to curtail supply actively. The logic is straightforward: decrease supply to bolster value.
  • A Closer Inspection: While reducing the token count through sinks may initially drive up value, it's not a panacea. Such tactics provide only temporary relief in the face of absent or low token utility.
  • Sustainable Scarcity: Tokens should have intrinsic value. There must be a reason for users to hold it beyond the mere expectation of appreciation due to scarcity. Without real-world utility or a compelling use case, scarcity alone may not sustain the long-term value of a token.

In the still-maturing world of blockchain economies, the supply of tokens is but one piece of the puzzle. In the subsequent sections, we'll explore how demand and velocity interact to form the complete picture of tokenomics.

Creating and Sustaining Demand

The true test for any cryptocurrency is not just its scarcity but the demand for it in the market. Demand is the engine that drives the token's acceptance and value.

Utility-Driven Demand

  • Beyond Speculation: While speculative trading can inflate prices temporarily, lasting demand is fueled by a token's utility. This includes its use in transactions, its role in governance, or its ability to grant access to certain services or rewards within its ecosystem.
  • Real-World Applications: The more a token can be used for real-world purposes, the more essential it becomes. Tokens that solve genuine problems or enhance the user experience in noticeable ways tend to cultivate more sustainable demand.

Understanding Velocity in the Token Economy

The concept of velocity in token economics often remains underappreciated, yet it is a vital factor in the valuation and stability of a cryptocurrency.

The Relationship Between Velocity and Value

  • Defining Velocity: Velocity is the rate at which a token changes hands in an economy. A high velocity means the token is frequently traded, which can suggest a thriving economy or, conversely, indicate a lack of incentive to hold the token long-term.
  • Impact on Token Value: While traditional economies aim for a balanced velocity of money, the crypto economy faces unique challenges that can make high velocity a sign of instability.

The Misapplication of MV = PQ in Crypto Valuations

  • Classical Economics Meets Crypto: The MV = PQ equation, while a mainstay in traditional economics, doesn't neatly apply to the decentralized and often speculative nature of cryptocurrencies.

When velocity is too high, it indicates that tokens are not held onto, which can suggest a lack of compelling reasons to keep the token for long-term value. On the other hand, extremely low velocity can signal a stagnant market or hoarding behavior, where tokens are not being used for their intended purpose, thus hindering the ecosystem's activity and growth.

To manage velocity effectively, developers can introduce features like time-locked contracts to reward longer holds or implement burn-and-mint mechanisms that adjust the token supply relative to its use in transactions. Also, by aligning token utility with the platform's growth—such as through loyalty programs or tiered services—users are encouraged to engage with the token economically, increasing its velocity in a controlled and beneficial manner.

Balancing the Three Pillars

Creating a successful token requires more than just technical prowess; it necessitates a nuanced understanding of economic principles and market behavior. Achieving an equilibrium between supply, demand, and velocity is akin to finding the perfect pitch in a complex symphony.

Designing for Sustainability

Strategic planning is the bedrock of sustainable token design. It involves implementing adaptive supply mechanisms that respond to the natural ebb and flow of the market. These mechanisms must discourage harmful practices like hoarding during bull runs or panic selling during downturns, which can create swings in token velocity. A great example of a blockchain with adaptive governance is Ethereum.

Utility must be at the forefront of a token's design — it must offer something of real value. Whether it's through enabling seamless transactions, allowing holders to participate in governance, or providing access to exclusive services, utility ensures that a token remains in demand.

A supportive and engaged community is also a hallmark of a balanced token economy. When token holders feel they are part of the project's journey, they're more likely to use the token as intended rather than speculate on its price. This sentiment can help stabilize the velocity, as the community-driven use of the token creates a steady stream of transactions.

Conclusion

Token utility is not just a buzzword; it's the heartbeat of any cryptocurrency's value proposition. It stands as the crucial element in balancing the triad of supply, demand, and velocity. In this exploration, we've uncovered that while scarcity can bolster value, it is the token's real-world use and the economic incentives it creates that sustain demand and manage velocity. 

Cryptocurrency is not a static field; it's an ever-shifting landscape that requires agility and foresight. As we continue to push the boundaries of what blockchain can achieve, we also continue to learn, adapt, and grow. Token utility, when deeply integrated and thoughtfully executed, remains the linchpin of this vibrant and burgeoning economy.

FAQ

How to manage token supply?

  • Employ scarcity tactics like burning tokens to reduce supply and staking mechanisms to lock tokens temporarily, balancing the supply to increase value.

How to address velocity's impact?

  • Mitigate high velocity's potential to decrease value by incentivizing longer holding periods or creating utilities that encourage users to circulate tokens more slowly.

What's the most important pillar?

  • All are important, but in our opinion, the demand has the biggest influence over the project's success.

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Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024
Applying Game Theory in Token Design

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

  1. Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
  2. Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
  3. Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

Stakeholders in blockchain development for systems engineering

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Artonomus, Github

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Artonomus, Github

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Artonomus, Github

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

The Death Spiral: How Terra's Algorithmic Stablecoin Came Crashing Down
the-death-spiral-how-terras-algorithmic-stablecoin-came-crashing-down/, Forbes

Conclusion

The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.

FAQ

  1. What does game theory contribute to blockchain token design?
    • Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
  2. How do bonding curves apply game theory to improve token economics?
    • Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
  3. What benefits do Layer 2 solutions provide in the context of game theory?
    • Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

Token Engineering Process

Kajetan Olas

13 Apr 2024
Token Engineering Process

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that. 

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.

source: https://www.canva.com/design/DAFDTNKsIJs/8Ky9EoJJI7p98qKLIu2XNw/view#7

Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase. 

Token Engineering Artonomous Design Diagram
Artonomous design diagram, source: Artonomous GitHub

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling 

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

  • Systems Engineering
  • Machine Learning
  • Market Research
  • Capital Markets
  • Current trends in Web3
  • Blockchain Engineering
  • Statistics

Summary

The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.

FAQ

What does token engineering process look like?

  • Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

  • We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

  • It depends on the project and may range from 2 weeks to 5 months.