Fundamental analysis is popular in traditional finance, but it can also be used in cryptocurrency markets. The idea of this type of analysis is to use all the publicly available information about an asset to help to determine the “fair” or real value. Market prices generally diverge from the true underlying value from time to time, but they will eventually return to their real value.
The aim of fundamental analysis is to find assets that are undervalued or overvalued by using a variety of techniques, which will be covered in this article. There are a wealth of options for gathering fundamental data. You can use blockchain data and create these metrics yourself, or you can use dedicated websites like CoinMetrics, CryptoQuant, Glassnode, Santiment, among others.
In the following sections, we’ll cover some areas of interest for conducting fundamental analysis: some are quantitative and we can place a number on these metrics, but others are qualitative and harder to quantify, requiring some of your own assumptions and judgements.
Overview
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Estimating Network Effects with Metcalfe’s Law
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The NTV Ratio: A P/E Ratio for Crypto-assets
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Assessing Fair Value with the MVRV ratio
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Earnings, Revenue, Price-to-Sales, and Price-to-Fees
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Tokenomic model
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Team
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Pros and Cons of Fundamental Analysis
Estimating Network Effects with Metcalfe’s Law
Metcalfe’s law tells us that the value of a communications network is proportional to the number of connected users squared and this approach has been applied to the valuation of social networks. One fundamental metric of interest is the number of active addresses, where periods of high growth in new users usually coincides with periods of sustained price appreciation.
Below we show an example of Ethereum using the 7-day moving average of active addresses from the 2017 bull market and subsequent bear market, where you’ll notice that the price of ETH and active addresses move in tandem. After the peak in both active addresses and prices in January 2018, both metrics moved lower together and entered a downtrend.
Source: CoinMetrics
We can also look further than the number of active addresses to approach valuation of crypto-assets. For example, the Price-to-Metcalfe Ratio (PMR) was introduced by Jacob Franek in 2018.
Source: Medium
As shown in Franek’s article, the PMR helps to predict market corrections and buying opportunities for ETH. Whenever the PMR has moved above 1, it has coincided with major tops while PMR values below -0.25 have highlighted good areas to buy.
Source: Medium
Other work on utilizing Metclafe’s law as an approach to crypto-asset valuation has been done by Dimitry Kalichkin to use different variations of the Metcalfe equation to find lower and upper bounds of the true value of crypto-assets like Bitcoin.
The NVT Ratio: A P/E Ratio for Crypto-assets
Much of the fundamental analysis for crypto-assets has been influenced by metrics used in traditional finance. One such example is the Price-to-Earnings ratio (or P/E ratio), which is used in the fundamental analysis of equities to attempt to determine the fair value of a company’s stock price.
The crypto-asset equivalent of the P/E ratio is the Network Value to Transaction (NVT) ratio, which was first created by Willy Woo and is calculated by dividing the market capitalization of a blockchain network by the volume transacted on-chain in USD.
The idea is that a crypto-asset with an unusually high NVT ratio is likely to be overvalued, since the network value is outpacing the volume transacted through the network.
High NVT ratios usually indicate price bubbles, since there’s a divergence between how much the network is worth and the transaction volume it is facilitating. On the other hand, with a historically low NVT ratio suggests the asset may be undervalued, since the transaction volumes may justify a higher network value.
One issue with the NVT ratio is that it is very noisy. But there is one variant that improves upon the original model: the NVT signal created by Dimitry Kalichkin, which is more responsive than the standard NVT ratio.
Instead of dividing by the volume transacted on-chain, the NVT signal uses a 90-day moving average of the daily transaction volume, which gives a better descriptive metric of price bubbles. As shown below, peaks in the NVT signal have corresponded with market tops in ETH.
Source: CoinMetrics
Assessing Fair Value with the MVRV
Created by Murad Mahmudov and David Puell, the Market Value to Realized Value (MVRV) ratio utilizes the realized cap metric created by the CoinMetrics team.
Realized Capitalization*: an alternative approach to valuing a blockchain network, which approximates the value paid for all coins in existence by summing the market value of coins at the time they last moved on the blockchain. Therefore, realized cap can be thought of as an estimate of the aggregate cost basis for a cryptocurrency. Because the realized cap incorporates the market value of coins the last time they were moved on-chain, this metric accounts for lost coins better than the market cap. *
The MVRV ratio compares the network value in terms of market capitalization and realized capitalization to understand when the price of a cryptocurrency is trading below its “fair value”. We can think of market cap as the speculator valuation of a cryptocurrency, while realized cap gauges holder valuation.
So whenever the MVRV ratio is below one, then it tells us that holders have a higher market valuation than current speculators. On the other hand, when the ratio is above one, then it suggests that speculators have a higher average market valuation than holders.
A reading of below one has historically been a good buy signal for BTC and ETH, as shown by the chart below. We can also see the ratio has highlighted tops with historically high values and bottoms when the ratio has dipped below one.
Source: CoinMetrics
While the MVRV ratio has only infrequently provided signals to act upon, it is best used to Dollar Cost Average into a position or execute long-term buy when the ratio is below one. On the other hand, the ratio can be used to sell a chunk of your holdings or go short using derivatives once it is above a historically high threshold (e.g., above 3.2 for BTC or above 2 for ETH).
It’s important to remember that crypto-assets can be undervalued or overvalued for significant periods of time. For example, during the 2018-2019 bear market, BTC remained in the buy zone (MVRV below one) for 133 days! ETH remained in the buy zone for an even longer period, 283 days! Therefore, another strategy is to enter long positions once the ratio has moved above the value of one.
A standardized version of the MVRV ratio, the MVRV z-score, measures the deviation between realized value and market value to provide another perspective.
Earnings, Revenue, Price-to-Sales and Price-to-Fees
Token Terminal is a very useful resource for analyzing metrics such as earnings, revenue, price-to-sales and price-to-fees.
Protocols with growing revenue going to tokenholders and the project’s treasury are in a better position to weather bear markets and it is also an indicator of increased usage, which often translates into a higher token price. In traditional finance, earnings and stock prices are positively correlated, and we are starting to see the same in crypto.
Source: Token Terminal
Other than earnings and revenue, there are two more metrics worth considering:
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Price-to-sales: the project’s valuation in relation to its revenues, calculated as the fully diluted market cap divided by the annualized revenue.
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Price-to-fees: the project’s valuation in relation to the fees generated, calculated as the fully diluted market cap divided by the annualized fees.
Source: Token Terminal
Token Terminal provides a useful dashboard that shows the weekly gainers and losers across different metrics, which can help you to spot opportunities. For example, if a project is consistently in the top gainers for revenue, then it deserves further attention and you can look at the other fundamental metrics mentioned in this article.
Tokenomic Model
A key fundamental factor for crypto-assets is how well the tokenomic model is designed, which includes:
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The circulating supply relative to the total supply: if the circulating supply is very low compared to the total supply, then it could be bearish for the price as more tokens enter the circulating supply in the future. Unlocks (which can be tracked here) are another factor where token unlocks may negatively affect the price.
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The supply schedule and the rate of inflation: what is the mechanism for emissions and how will inflation evolve over time? Coins with a declining inflation rate should perform better than coins with an inflationary model, given they both have the same demand.
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The staking ratio: how many coins are locked up? If more are locked, then there is less sell pressure and increases in demand should benefit the price.
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The initial token distribution: how fair was it? How widely distributed are the tokens? A fairer and wider distribution generally leads to better performance over time, as the supply is not concentrated amongst a few holders.
Team
An important qualitative factor to consider when doing fundamental analysis is the protocol’s team. Big brains are positive, while anonymous developers may be a red flag (although not always true!).
Teams that are experienced, have a verifiable track record and have had previous success in other ventures are the signs to look out for, as you can be more confident in your investment if the team is top-class.
One related quantitative metric is developer activity. While the value of each code commit is not necessarily equal, a codebase that is frequently maintained and updated is a good sign that the protocol will still be here in five or ten years’ time. Monitoring a project’s GitHub can also be a source of alpha sometimes, as you’ll be able to see new features being implemented before they are announced and before the public is aware of them.
While we have provided some of the main factors to judge a crypto-asset’s fundamentals, this is not an exhaustive list. Hopefully, you should now be well equipped with the tools mentioned here to conduct analyses and see if a crypto-asset is trading at, below or above the fair market value.
However, it should be noted that fundamental analysis for crypto-assets is still a relatively new field and ever evolving, leaving the door open for future discoveries. In the next section, we highlight some advantages and disadvantages of the fundamentals approach.
Pros and Cons of Fundamental Analysis
Pros
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Fundamental analysis helps you to identify long-term trends and spot opportunities that will help you generate a return over an extended period.
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Enables you to identify undervalued or overvalued crypto-assets, eliminating bias from the investment process.
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You’ll gain a deep understanding of a blockchain network by studying the various fundamentals and digging into the metrics. Because a lot of time is spent on various metrics, fundamental traders may also spot red flags that may not be noticed by other traders who focus on a purely technical approach or those who just read the news and don’t do any further research.
Cons
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Patience is required, as fundamental trends take a long time to play out and doing the analysis can be time-consuming. Also, if you’re tracking fundamentals on a day-to-day basis to find signals and take actions based on those signals. For example, you could wait months for an indicator to suggest an asset is undervalued, but you’ll still have to monitor it daily to make sure you don’t miss the signal. Fundamental analysis has little to no use for understanding what the price is going to do over the short-term (which is where technical or sentiment analysis is more useful).
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Fundamental analysis requires you to make some assumptions and objectivity is not clear cut. A lot of the data used in the metrics are only estimates. For example, active addresses are not equivalent to the number of different users, so being able to interpret these metrics correctly is also important and being aware of the wider landscape. For example, a spam attack may show greater transaction count, but if you’re unaware of the spam attack, you may mistakenly take it as an encouraging fundamental development.
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Fundamentals are not standardized across different crypto-assets. For example, what is considered a buy zone for BTC may not be the same for ETH. The NVT signal indicator is a good example, as different cryptocurrencies will vary in the values that suggest undervaluation or overvaluation.