How do we rationally invest in a smart contract chain? Are TVL and DeFi the ‘whole gamut’? Covered: TVL: The Only Game in Town How TVL Can Be Gamed Valuation Constraints Beyond DeFi So, What to Make of This? TVL: The Only Game in Town How can we measure the value of a layer-1 blockchain? […] The post How Do We Measure the Value of a Smart Contract Chain? appeared first on CryptosRus.

How Do We Measure the Value of a Smart Contract Chain?

How do we rationally invest in a smart contract chain? Are TVL and DeFi the ‘whole gamut’?

Covered:

  • TVL: The Only Game in Town
  • How TVL Can Be Gamed
  • Valuation Constraints
  • Beyond DeFi
  • So, What to Make of This?

TVL: The Only Game in Town

How can we measure the value of a layer-1 blockchain? What metrics do we need to define and analyze? Unlike the classics for stocks: revenues, cash flows and price-to-earnings ratios; blockchains contain none of these to quantify and gauge their value. For crypto, we have been left with mere TVL (Total-Value-Locked) to answer the valuation question. While TVL is a good indicator of the trust users have in adding their liquidity to these various protocols, it leaves a lot be desired.

TVL is nearly 100% derived from two data inputs: liquidity providers on a DEX and the supply of capital on money markets; lending and borrowing protocols. The one other input is staking, which is when holders supply their coins to a protocol to earn a yield. An example of this is Lido Finance, which is a protocol that allows users to stake to the Ethereum (2.0) beacon chain. The reason they have a TVL of $17 billion is that they allow for liquid staking. Meaning, users receive a synthetic, liquid representation of their staked ETH to use in DeFi, which is highly incentivizing.

There is a lot to be said about total-value-locked, its shortcomings, and why it is reductive. There are also tricks and schemes that can be used to boost TVL. Recently, Avalanche’s founder Emin Gun Sirer took to Twitter and bragged about the recent success of an Avalanche subnet. Mostly, his point was to highlight that in “only two days” since launch, the subnet had higher TVL than Cardano. In short, subnets allow projects to stake $AVAX to create L1 or L2 smart contract chains.

How TVL Can Be Gamed

On its face this sounds like a victory for Avalanche. Even their Layer-2’s can dunk on Cardano TVL in a matter of days. Charles Hoskinson wasn’t having it, though. The founder of Cardano clapped back at Emin, espousing that the result of this TVL was a massive pre-mine of the new token native to the subnet. The subnet, which is a Defi Kingdom’s iteration on Avalanche, is called Crystalvale, and has its own token, CRYSTAL. Charles was clowning Emin for “printing”, or, pre-mining the CRYSTAL tokens out of thin air to boost TVL.

There are other ways TVL can be gamed, manipulated, and boosted. You can read a great article that breaks it down, here. To their credit, DefiLlama.com, the pre-eminent site that tracks TVL has tried to stay ahead of the curve by enabling many toggle filters that attempt to address the very nuanced concept of blockchain TVL. However, it raises a broader question larger than TVL. Is DeFi the only way to gauge a chain’s value? Further, it’s important to understand that even tracking DeFi is difficult, and broader valuation constraints exist outside TVL entirely.

Tokens fluctuate for reasons unbeknownst to anyone, supply and demand is the reductive response to “valuing a smart contract chain“. There are, of course, tokenomics. Which is, more or less, “how is the supply of the token distributed and by what mechanisms?” Is the token being dumped on the market? Is there a vesting period which unlocks for early investors? Is there token burning? How many wallets controls how much supply? These are a few empirical tokenomic questions. Trust me, there’s more.

Recommended: Charles Hoskinson Tweets Offer At Elon Musk

Valuation Constraints

For example, does the chain’s consensus mechanism require native token exposure? Can you delegate your stake to a full node? One can see how this becomes very complicated. While important, the overtly dubious “flywheel tokenomics” of a given chain currently aren’t juxtaposed against other chains when determining value, at least collectively. Sadly, much of these “tokenomic” designs revolve around “number go up” VC ownership concentrations, see here. Alas, DeFi is currently the #1 quantifiable metric that can display the success of a chain relative to other chains.

There are also wallet addresses, transactions per day, long-term holder metrics, and the like. These are all on chain data that are important, but don’t really move the needle. After all, this is all about comparison. Collecting this data for comparison is not easy to begin with. Aggregating on-chain data is difficult depending on the chain. The Graph Protocol is used heavily by DeFi Llama. This caters to EVM chains. The Graph ($GRT) allows projects like Defi Llama to easily query vast swaths of data on chains supported by Graph.

Just as Google indexes website data, Graph indexes blockchain data. All this is to say: there are bottlenecks for even querying TVL data. So it’s not an even playing field even for TVL. Without the Graph, it takes Github pull requests, and generally more burdensome leg work for Defi Llama to even get your TVL tracked properly on their application. Per their methodology for Anchor: “We use the Anchor subgraph (The Graph) to get the amount of bLUNA and bETH used as collateral on anchor and the UST that is on anchor but has not been lent, we then use Coingecko to price the tokens in USD.”

Beyond DeFi

The question remains: is there more to smart contract chains than staking, borrowing, lending, and providing liquidity? As we have discussed, valuation is at its root supply and demand. However, the mechanisms behind that are what on-chain analysts and TA experts painstakingly analyze. This highlights that valuing future price and worth is an ambiguous and idiosyncratic endeavor. Recently, a bullish article went viral detailing that “a total of 31,130 bitcoin left Coinbase, the highest single-week outflow since 2017.” (Outflow metrics indicate bullishness due to coins coming off exchanges to be stashed away in wallets).

Bitcoin was at ~$40k when that article was published March 15th. Just two weeks later, Bitcoin jumped to $48k. Only to plummet days later to $40k, (where it trades at press time). These on-chain data are “blink-of-the-eye” metrics, not generally relevant for investors seeking long-term indicators. Bitcoin, other than Lightning, has no discernible DeFi TVL. Still, the above chronology highlights the impermanent relevance any of these on-chain valuations provide. Actionable investing cannot function as a result of on chain metrics. If so, every on chain expert wouldn’t need to shill you their ‘exclusive’ services.

So is there any other way to gauge lasting “value” from chains, other than TVL and on-chain data? Cointelegraph recently published a research report which contained valuation metrics not seen hitherto. The report compared Bitcoin, Ethereum, Solana, Polkadot, and Algorand. Of course, TVL was one of the metrics used for comparison. There are others, like active addresses, which we touched on above. Once again, something like active addresses is quantified based on an arbitrary set of metrics which is not made clear in the report. (E.g., x amount of addresses moving x amount of funds in x amount of days.)

Protocol Revenue: The New TVL?

What is interesting is the inclusion of “Protocol Revenue” in the report. Here we recognize a word quite familiar to equity valuation: Revenue. Interestingly, the lowest ranked chain in this comparison, Algorand, registered protocol revenue higher than Bitcoin ($450 million), Solana ($2.2 million) and Polkadot ($7 million), at $498 million (Page 4). All coming in far behind Ethereum, which registered $2.2 billion. For BTC and ETH, this metric was specifically derived from “transaction fees”, or, gas. It makes sense then that Ethereum would come out on top.

It didn’t specify if this metric was derived from transaction fees for Polkadot, Solana, and Algorand. The “Protocol Revenue” metric in the report is sourced from Numbrs.com. However, the linked page of the website simply states: “This metric captures the change in the underlying revenue of the protocol, which often accelerates with the advent of liquidity-mining programs.” Normally, protocol revenue from fees would put proof-of-stake chains at a disadvantage because it costs so little to execute a smart contract (transact). Then again, their throughput (speed) is much higher which means more transactions, more swiftly.

This begs the question: how could Solana, with a TVL of ~$7 billion, have less “protocol revenue” than Algorand, which has a TVL of merely $278 million? They both have very nominal transactions fees. Firstly, very few even know of this metric. Akin to electron’s behaving differently when observed, collective awareness of a metric, which causes the market to act, are known as market forces. Secondly, the methodology behind “protocol revenue” is unclear, and isn’t fleshed out by Cointelegraph. Is it a matter of transaction count? According to Grayscale’s metrics, no. So, what can we make of this?

So, What to Make of This?

Well, as the above link shows, transaction counts show Solana blowing everyone else out of the water, but their “protocol revenue” is not nearly that of Ethereum or Algorand. Why? Because their “consensus messages” display “votes” as transactions. Why is this significant? Because chains can “count” metrics differently, leading to skewed comparisons. If you can’t tell by now, quantifying the value on-chain is contingent on many different “nitty-gritty” nuances, like transaction count. There is the simple rebuttal: “Metcalfe’s Law solves this.” In short, Metcalfe’s law posits: A larger network (growth) means more value.

This is just theory, though. As we have noted: observability = value change. Because Metcalfe’s law is conjecture (which few understand or observe) to postulate causal effects of a large network, it currently has no relevance to Layer-1 valuations. How can this be? Well, Layer-1 network “size” have no settled determinants. Look at Algorand, detailed in the report. Exodus Wallet, a competitor to Coinbase, is similar to $COIN; a publicly traded company. However, all Exodus ($EXIT) shares live on Algorand. In fact, 2,733,229 $EXIT shares worth $75 million have been tokenized on the Algorand chain. So what?

In other words, Exodus allows $EXIT holders “to sell their stock in the company using blockchain infrastructure.” This is actually happening, today, on Algorand. Is this quantified into TVL? No. So, a use case of recording, storing and acting as the de facto custodian and broker (tangentially) of tokenized stock shares is not currently calculated in the “value” as it pertains to TVL, which is absurd. After all, these smart contract chains were meant to function as alternatives to such centralized TradFi systems. This reductive gauge of TVL is abundantly clear. We need to adopt a holistic, broad-based guide to true TVL, now.

Recommended: Cardano’s Recent TVL Surge Is Just The Beginning

The post How Do We Measure the Value of a Smart Contract Chain? appeared first on CryptosRus.