What Makes a Layer 1 Asset Valuable?

I have seen a lot of discussions on Twitter and in my own circle pertaining to the confusion surrounding where Layer 1 native assets get their value. People often speak as though the value is derived only because users need the token to pay gas fees for their transactions. But it’s becoming clearer the utility and value goes beyond the need for transaction fees, if this was the case SOL and AVAX would have very little intrinsic value. Here I do my best to explain where native assets get their value and why emerging smart contract platforms have seen their native assets spur large growth in the recent months.

People from traditional backgrounds are used to plugging into widely known and understood mathematical models to fairly value an asset, such as discounted cash flows or P/E ratios, but in this emerging market we have yet to see any robust and widely accepted models with which to gauge the expected price of a given asset. Even projecting into the future, it is unlikely there will be any universal models, given the increasing complexity in specific token utility, value capture, and tokenomics. What I’m proposing here isn’t a specific mathematical model with which to price these assets, but rather a framework with which to understand the components that contribute to their market value.

Let’s assume an assets value is based on it’s “fair value” market price. Price can obviously go up or down based on speculative activity, overall market sentiment, and other external factors, but in this case we will assume we are operating in a perfectly efficient market. Let’s bring things back to Economics 101, and understand price as a function of supply and demand:

An asset’s “equilibrium price” is point in which both buyers and sellers of a given asset are satisfied. This price changes depending on the shifting of either curve. Increasing the demand, and thus shifting the curve to the right, will result in an increase in the equilibrium price. The same is true for reducing the supply, which shifts the supply curve to the left. So we can assume a token obtains its value from a function of changing supply and demand.

Taking this framework into consideration, we can first take a look at how different Layer 1 assets derive demand for their native token.


The most important aspect to an assets value is its demand, because it represents the prices of which a market participant is willing to buy a particular asset. Without buyers, a token would be worthless, and tokens who are able capture the most amount of demand through utility will see steep appreciation in value, as it shifts the demand curve to the right.

Let’s go over some of the main sources of sources of demand for native Layer 1 assets.

Pay for transaction fees

We’ll get the obvious one out of the way first: the native asset is often the way in which users pay transaction fees to use the network. This demand is obviously heightened with respect to the average fee for a given network. For example, ETH as an asset is going to derive more demand for network transaction fees than SOL or AVAX.


Native assets can also be used as payment within its own ecosystem, and in some cases beyond its own blockchain. NFT’s are often priced in the native asset, and it often serves as a popular liquidity pair for newly created ecosystem tokens. Therefore, users who want to interact in the underlying economy will likely need to buy the native asset to participate. But some native assets are better and more widely accepted forms of payment than others. For example, BTC is accepted as legal tender for El Salvador and accepted by any merchant in the country. ETH is a much more widely regarded form of payment, as a large amount of digital purchases are using ETH, and even some traditional art auctions have begun auctioning off NFT pieces with a denomination in ETH. Therefore, some assets obtain far more demand for a means of payment than others, and it can often be directly tied to the number of ways and instances the asset can be used as a medium-of-exchange.

Borrowing Collateral and Lending

Lending DeFi platforms give users an opportunity to borrow funds posting their assets as collateral, and given the potential long-term appreciation of many of the Layer 1 native assets they become a main source of collateral for these platforms. There will always be demand for borrowing against appreciating assets, because it allows users to pursue other ventures while still being exposed to the upside of the asset, all without having to sell and incur potential capital gains taxes depending in the user’s jurisdiction.

Staking yield

For Proof of Stake blockchains or those with a similar consensus mechanism, owners of the native asset are to provide their token to be staked on the network, and are then compensated with issuance and/or transaction fees for correctly validating transactions. This can be anywhere from 4–14% per year, which can be very attractive for potential investors (more information on staking yields can be found here).


While all these things contribute to the overall “fair value” of a given Layer 1 token, we must not forget the primary reason these assets even exist in the first place: to provide the underlying security to their respective blockchain. They contribute the needed incentive structure to make sure network transactions are correctly validated and remain safely guarded from potential bad actors. In Proof of Work, the native token is designed to reward miners for correctly validating transactions. As demand for the asset grows, so does the profitability of mining, which causes more miners to join the network and increases the hash difficulty, both of which contribute to the security of the network because it now takes more capital for a bad actor to attack the system. For Proof of Stake, not only is the native token given to validators, but a stake of tokens are required in order to spin up your own node. Therefore, in a similar vein, as demand for the asset grows, so does the capital required for a bad actor to gain enough influence to attack the network.

Therefore, as the Layer 1 token becomes more valuable, so does the security of the underlying blockchain. This flywheel becomes extremely important and actually contributes to the overall demand for a blockchain as the underlying economy grows. For example, let’s say you are company looking to build a high-speed application on Solana. Now that you’ve made this choice, you are economically incentivized to contribute to the overall security of the blockchain. So, it is in your best interest to buy SOL on the open market and spin up your own validator node, which in turn increases the value of SOL and contributes to the decentralization and security of the network. Therefore, the demand for the token is inherently linked with the economies and network effects that underly that blockchain, because as the scale of that economy grows so does the interest in increasing the blockchain’s reliability and security, and therefore the value of the native asset.

We must also understand the demand for each of the other use cases also become exceptionally heightened if theres a larger economy underneath. Alternative smart contract platforms such as Solana, Avalanche, and Terra have seen their native assets skyrocket in value over the past few months, and this is due to the current and expected future economic activity on the blockchain. This rise in activity gives users of the platform more incentive to use it in the many ways outlined above, such as pay for NFT’s, borrow against the asset in lending protocols, and begin running their own validators if they so choose. Therefore, the economic activity of a given blockchain can be seen as the best indicator for a native asset’s current value.

Now that we’ve understood some of the dimensions that lead to increased demand for a native asset, we can now explore how each asset handles its own token supply.


The beautiful thing about cryptocurrencies are the supplies are almost always obtainable and mathematically precise at any point in time. Therefore, the supply side of the equation can often be strictly quantified in the present and can be roughly estimated in the future. Because supply schedules and changes can be defined through the blockchain’s code, and are often used as a way to incentivize behavior of an entire ecosystem, a term known as “tokenomics” has emerged to describe this phenomena. It is important to understand how the tokenomics model changes from blockchain to blockchain in order to better understand how each asset retains its value through scarcity and game theory incentives. The reason scarcity is important is something most humans naturally understand and is once again explained by the simple supply and demand framework. The lower the supply, the higher the equilibrium price for an asset.

Game theory incentives is also another important piece, because how a blockchain manipulates its tokenomics with respect to issuance and burn can provide incentives for certain behaviors on the network. Let’s take a look at some examples for how different blockchains prioritize these elements.


Bitcoin follows a disinflationary supply schedule with a halving every 210,000 blocks or roughly 4 years time. It started with issuing 50 BTC per block and this will continuously half until it cannot anymore, meaning only 21 million can ever be mined throughout its existence. Because of this strict supply schedule and cap on the total amount that can ever exist, people look at BTC as a long-term store of value asset.

Ether on the other hand has a much more complex supply history. It started out as strictly inflationary, with the issuance beginning with 5 ETH per 15 second block, before being cut down to 3 ETH during the Byzantine hard fork in 2017 and then to 2 ETH during the Constantinople hard fork in 2019. With the London hard fork and EIP-1559 upgrade in August of 2021, the gas fee and supply structure was changed, as a base fee was now burned from existence in each transaction, adding an element of potential deflation to the supply. This means with respect to Bitcoin, Ether’s supply is much more variable and can not be known with certainty in future projections. But the idea behind such a proposal comes from the value of scarcity. By reducing the overall supply, the network is able to reward long-term holders and stakers by making their positions more valuable. And ETH now becomes a bet on the overall network activity of Ethereum, as the deflationary pressure is tied to the transaction fees paid.

Other PoS blockchains such as Solana and Polkadot have a defined inflation schedule. For Solana, that is 8% in the first year followed by 15% decreases until a minimum inflation of 1.5%. Polkadot aims at always achieving 10% inflation, with built in changes based on an optimum number of DOT staked on the network. While these assets are not optimizing for scarcity in the way BTC and ETH are, they are instead using inflation as incentives to stake on the network, because failing to do so would dilute the holders token supply. While each individual token may not retain as much value in the long-run due to inflation, a higher amount of tokens will be locked up, which lowers available supply on the market and contributes to the security of the network.

One Layer 1 asset with a unique set of tokenomics is LUNA, the native asset of the Terra blockchain, as its supply isn’t diluted with inflation (all staking rewards come from fees) and the supply actually expands and contracts with respect to minting of the blockchain’s native stablecoins. UST, the dollar denominated stablecoin on the network, has seen immense growth as of recent and has therefore contributed a large amount of deflationary pressure to LUNA’s tokenomics. What’s also interesting is that these stablecoins aren’t restricted to the Terra blockchain, as Terra is easily connected to many other blockchains through Wormhole and Cosmos’ IBC and many applications on other chains have shown expressed interest in using UST in one form or another. Therefore, LUNA’s supply is not just correlated to the economic activity of its own blockchain, but wherever UST is used.

While there are many more potential models to choose from, each of these assets finds their own unique way of dealing with token supply, often trying to produce as much scarcity as possible while also maintaining blockchain robustness and security. The more scarcity is introduced, the more value each individual token holds, but inflation can be fine as long as it is controlled and incentivizes good network behavior.


Since the supply can be known at any point in time, many of the models we have seen are created using supply as a given metric. The largest example of this being the Bitcoin Stock-to-flow model by Plan B. Using Bitcoin’s known supply, it calculates the ratio of new coins coming into the circulating supply per year with respect to the supply already circulating, and uses this to gauge the potential price of Bitcoin.

On-chain metrics have also become an extremely popular way to gauge how the supply changes hands over time and how these changes contribute to price changes. Some in the Ethereum community have tried to explain ETH’s rise in value as a result of newly issued supply shocks in the system, one article being “Ethereum, The Triple Halvening” (Link). Even I tried to model LUNA’s price based on potential UST adoption and therefore token deflation (Link). While these models can be useful, they assume that demand is a function of supply, while we have seen it can be completely separate based on token utility and the underlying blockchain economy. A token can burn 10% of its supply per day, making it more scarce, but if no one is using the underlying blockchain, the supply does not matter because the token will not accrue value. Once these demand functions become quantifiable we will likely see more precise models come about in order to more appropriately price these assets.


While supply and demand are the key ways in which an asset can accrue tangible value, there are often intangible elements that can contribute to value as well. Often people price assets is not defined by obtainable metrics but rather the narratives that underpin. Even in traditional equities, stocks can get priced based narrative alone. Why is Tesla valued at over a trillion dollars despite limited profitability? It’s because there is a narrative that electric vehicles are the future of transportation and will likely lead to immense future profitability. Is this to say that Tesla isn’t overvalued? It certainly might be, but the market is currently pricing in this narrative. There are many examples in the crypto market where narratives shape how the market values a specific asset.

Bitcoin is a perfect example of the power of narrative. BTC as an asset and blockchain has a lot less utility and economic activity with respect to the most popular smart contract platforms. And you could argue tokens that are potentially deflationary like ETH and LUNA may have better value accrual from a supply standpoint. But what is fundamentally driving BTC’s price appreciation is its narrative as a long-term store of value and sound money, and its ability to stay completely secure and resilient throughout its lifespan. This narrative has proven itself to be extremely valuable, as people look at BTC not only through the lens of its direct utility, but moreso as an escape from the manipulated fiat system and a direct competitor to gold.

Smart contract platforms other than Ethereum have seen a recent rise not only through increased economic activity, but also a shift in market narrative. Where previously it was widely accepted that blockchains should prioritize for decentralization, and therefore security and censorship resistance, a new narrative for blockchains with faster settlement time and easier developer experience had begun to emerge. The intangibles that the market prioritized had shifted, and therefore so did the value of the assets underlying those narratives.

Narratives can also create an assets floor, as there can be excitement around a given blockchain’s technology or economic potential. Let’s take Polkadot for example, who doesn’t yet have any live parachains and therefore no one is yet using the platform. Without any economic activity does that mean DOT as a token should be worth $0? Certainly not, the parachain model as well as the community excitement around the launching products should be evident of some value. But also taking EOS as an opposite example, which had immense amount of funding for new projects and developers but very little excitement from a technological perspective. Once the money ran out, so did the developers and ecosystem participants, and has since become virtually a ghost chain. There is clearly value in where people find excitement and potential for future development, and this should be factored in when trying to value a given Layer 1 asset.


The value of Layer 1 assets clearly goes way beyond just the use for transaction fees on a given platform. The demand can stem from using these assets in many different ways, all of which are fundamentally driven by the underlying economic activity and network effects. The supply of an asset also contributes value, as tokenomics allow for increased scarcity or positive network behavior through game theory incentives. In addition, powerful narratives can also contribute, as intangible things can often drive how the broader market values a certain asset above others. Layer 1 assets will continue to be a driving force in the market’ s success and it’s important that we value them as correctly as possible.


If you enjoyed the content, consider following my Twitter @WestieCapital, and if you have any questions my DM’s are always open. Cheers.



Crypto currency investor and researcher. Focus on DeFi, Layer 1s, and the Terra ecosystem

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Crypto currency investor and researcher. Focus on DeFi, Layer 1s, and the Terra ecosystem