A confession: I’m not a cryptocurrency trader. You’re far more likely to find me hacking on low-level blockchain protocols than staring at cryptocurrency charts trying to predict price movements.
I’m not really a trader at all — I’ve always been more of a long-term investor with an eye towards assessing whether I think an asset is under or over-valued given fundamental analysis and prospects for future growth. In between computer science technical references and cyberpunk novels, you’ll find Graham, Malkiel, and Boggle on my bookshelves. So if you’re looking for guidance on the next hot alt-coin or where the price of BTC is headed in the short-term, take what I have to say with a grain of salt.
But if you’d like to better understand the fundamental differences between various categories of cryptocurrencies and — more importantly — a way to evaluate their underlying value and long-term potential, maybe I can help.
So without further ado, a categorization and analysis of various cryptocurrency types and how to evaluate their long-term value, kept short enough to read over your morning coffee (or evening cocktail).
Store Of Value Networks — Ex: BTC, LTC, ZEC, XMR, DOGE. These are all cryptocurrencies that focus on transacting themselves; e.g., the main functionality of Bitcoin is to record and transfer BTC. Most are native cryptocurrencies to a blockchain (native = part of the underlying protocol), or in the case of DogeCoin (originally created as a joke), operating as a smart contract hosted on a parent blockchain — in this case, Ethereum.
Some are focused on transparency, some on privacy, but all have in common (1) a fluctuating market value, and (2) little economic utility beyond their ability to hold value over time (think digital equivalent to gold).
This is the category most well-suited to technical analysis, as they are only valuable so long as a sufficient number of people say they are valuable, and they have little fundamental value beyond their market demand.
Payment Networks — Ex: BTC, LTC, ZEC, USDT, XRP. Notice the overlap with the previous category. That is because most cryptocurrencies that have become stores of value started with the intention of being payment networks — e.g., Bitcoin’s initial vision was being a digital currency that offered a solution to the double-spend problem, not as a crypto asset that would skyrocket in market price and transfer wealth.
Many of the communities surrounding these coins still see them as payment networks, but wildly fluctuating values of any currency leads to poor suitability as money. And while stablecoins (cryptocurrencies fixed to a fiat currency via fluctuating supply) offer an interesting solution by holding values steady, you can’t really invest in them (except perhaps as some sort of forex play) since their value will never increase or decrease.
However, for payment protocols that offer a cryptocurrency with a fluctuating price, we can evaluate potential value based on the convenience, usability, and partnerships/acceptance of the payment network — the same as we might evaluate any other payment technology — coupled with an assessment of the role that the crypto asset plays in the system and whether or not its demand should be directly impacted by the volume of payment transactions.
Compute Networks — Ex: ETH, EOS, QTUM. This is where things get interesting, because these aren’t cryptocurrencies in the same sense as the previous two categories. Instead they are blockchain compute networks capable of running scripts (smart contracts) that form the backend for client applications (dApps). Think AWS but running P2P instead of in a centralized data center. Here the native cryptocurrency serves simply to determine how you allocate scarce computing resources, e.g., if you want to access a smart contract/dApp on Ethereum, even a transaction involving another hosted token, you have to pay your transaction fees in ETH. That is to say, if you want to use Ethereum dApps, you must purchase ETH, creating demand against a (largely) fixed supply.
That also means that we can evaluate the value of each compute network primarily based on: (1) the number (or future number) of smart contracts/dApps hosted on each blockchain network, along with the transaction volume each generates (or is likely to generate); (2) the total transaction volume that the network is capable of processing; and (3) the attractiveness of the platform to dApp developers along with the costs of switching networks. In other words, assuming a cryptocurrency is used to pay transaction fees, we can evaluate its value much in the same way we might evaluate any other infrastructure or platform technology.
Utility Networks — Ex: PowerLedger, Waves, Filecoin, XYO. These are similar to compute networks, but usually have a more narrow focus/optimizations and are often hybrid networks that connect blockchain technology to some external resource/technology/asset, or occasionally bridge between various blockchains. These may be implemented as special-purpose blockchains, but also may be hosted on compute network blockchains in the form of smart contract protocols.
We can evaluate these cryptocurrencies in a similar fashion to compute networks, with a few additional considerations: (1) how central a native cryptocurrency and/or token is to the utility of the network/protocol; (2) how much demand there is (or will be) for the given utility/protocol; (3) how much of a benefit decentralization provides to the utility/protocol; and (4) how much of a benefit a special-purpose blockchain provides over a more general compute network blockchain, or how much of a benefit a protocol token provides over a smart contract making use of the native cryptocurrency of the host blockchain.
Voting/Security/Misc Tokens—Ex: DOA, CryptoKitties, EOS ICO on Ethereum. Almost always implemented as smart contracts on a general compute network blockchain, the gist of these tokens is that they provide a form of decentralized crowdfunding for a given project. They may represent voting rights, or shares of profits, or nothing at all other than the goodwill of project funders. They might represent reward networks, prepaid purchases, or in-game items. Where these tokens represent a distributed ledger for an otherwise traditional investment asset class (revenue share, equity, debt), the token value can largely be evaluated based on the underlying asset it represents. Where they represent items that would not traditionally be considered an investment, the argument for any investment value in the tokenized version is hard to justify.
The important takeaway is that you can’t use the same set of metrics to evaluate the potential future values of BTC, ETH, XRC, XYO, and the latest random ICO, any more than you can evaluate stocks, bonds, and gold using the same set of metrics. The factors that influence demand, not to mention differences in how supply is controlled, are simply too different. Looking at the problem purely in terms of current mindshare or market cap ignores those fundamental differences — and the rather nascent state of cryptocurrency markets and analysis — at the risk of making long-term investment mistakes.
I own small amounts of BTC and ETH, and I am part of a team that has been working (in stealth mode) on an open-source utility blockchain in the financial markets space for the last year.
Original artcle can be found here