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What Is Fundamental Analysis (FA)?

Fundamental analysis (FA) is to an investor what technical analysis is to a trader. Those focused on long-term value appreciation rather than short-term gains should look favorably to a system such as FA, as it teaches you to determine the fair value of a cryptocurrency.

In a market with more than 5,000 assets to choose from, picking the right one might look like a life-long quest. New tokens come and go, and there is never a way to tell which one can stand the test of time. One might think that investing in a cryptocurrency that is not Bitcoin or Ethereum is like betting on the lottery, but is that really the case?

Introduction

Trading assets as volatile as cryptocurrencies requires some skill. Selecting a strategy, understanding the vast world of trading, and mastering technical and fundamental analysis are practices that come with a learning curve.

When it comes to technical analysis, some expertise can be inherited from the legacy financial markets. Many crypto traders use the same technical indicators seen in Forex, stock, and commodities trading. Tools like RSI, MACD, and Bollinger Bands seek to predict market behavior irrespective of the asset being traded. As such, these technical analysis tools are also extremely popular in the cryptocurrency space.

In cryptocurrency fundamental analysis, though the approach is similar to that used in legacy markets, you can’t really use tried-and-tested tools to assess crypto assets. To conduct proper FA in cryptocurrencies, we need to understand where they derive value from.

In this article, we will attempt to identify metrics that can be used to craft your own indicators.

What is fundamental analysis?

Fundamental analysis is a method used by investors and traders to attempt to establish the intrinsic value of assets or businesses. To value these accurately, they’ll rigorously study internal and external factors to determine whether the asset or business in question is overvalued or undervalued. Their conclusions can then help to better formulate a strategy that will be more likely to yield good returns.

For instance, if you took an interest in a company, you might first study things like the company’s earnings, balance sheets, financial statements, and cash flow to get a feel for its financial health. You might then zoom out of the organization to look at the market or industry it’s operating in. Who are the competitors? What demographics is the company targeting? Is it expanding its reach? You could zoom out even further to take into account the economic considerations like interest rates and inflation, to name just a couple of factors.

The above is what’s known as a bottom-up approach: you start with a company you’re interested in and work your way up to understand its place in the broader economy. But you could equally adopt a top-down approach, where you narrow down your picks by first examining the bigger picture.

The end goal with this type of analysis is to generate an expected share price and to compare it with the current price. If the number is higher than the current price, you might conclude that it’s undervalued. If it’s lower than the market price, then you could assume that it’s presently overvalued. Armed with the data from your analysis, you can make informed decisions about whether to buy or sell that particular company’s stock.

Fundamental analysis (FA) vs. technical analysis (TA)

Traders and investors new to the cryptocurrency, forex, or stock markets are often confused over which approach to take. Fundamental analysis and technical analysis stand in stark contrast and rely on significantly different methodologies to analyze different things. And yet, both provide data relevant to trading. So which one is best?

In fact, it might make more sense to question what each brings to the table. In essence, fundamental analysts believe that stock price is not necessarily indicative of the stock’s true value – an ideology that underpins their investment decisions.

Conversely, technical analysts believe that future price movement can be somewhat predicted from past price action and volume data. They don’t concern themselves with studying external factors, preferring instead to focus on price charts, patterns, and trends in markets. They aim to identify ideal points for entering and exiting positions.

Proponents of the efficient market hypothesis (EMH) believe that it’s impossible to consistently outperform the market with technical analysis (TA). The theory suggests that financial markets represent all known information about assets (that they are “rational”) and that they already take into account historical data. “Weaker” versions of the EMH do not discredit fundamental analysis, but “stronger” forms argue that it’s impossible, even with rigorous research, to gain a competitive edge.

Understandably, there is no objectively better strategy out of the pair, as both can present valuable insights into different areas. Some may lend themselves better to certain trading styles, and, in practice, many traders use a combination of both to observe the bigger picture. This is true for short-term trades as it is for long-term investments.

The problem with crypto fundamental analysis

Cryptocurrency networks can’t really be assessed through the same lens as traditional businesses. If anything, the more decentralized offerings like Bitcoin (BTC) are closer to commodities. But even with the more centralized cryptocurrencies(such as those issued by organizations), traditional FA indicators can’t tell us much.

So, we need to turn our attention to different frameworks. The first step in that process is to identify strong metrics. By strong, we mean ones that can’t easily be gamed. Twitter followers or Telegram/Reddit users are probably not good metrics, for example, as it’s easy to create fake accounts or buy engagement on social media.

It’s important to note that there’s no single measure that can give us a full picture of the network we’re assessing. We could look at the number of active addresses on a blockchain and see that it has been sharply increasing. But that doesn’t tell us much by itself. For all we know, that could be a standalone actor transferring money back and forth to themselves with new addresses each time.

In the following sections, we’ll take a look at three categories of crypto FA metrics: on-chain metrics, project metrics, and financial metrics. This list will be non-exhaustive, but it should provide us with a decent foundation for the subsequent creation of indicators.

On-chain metrics

On-chain metrics are those that can be observed by looking at data provided by the blockchain. We could do this ourselves by running a node for the desired network and then exporting the data, but that can be time-consuming and expensive. Particularly if we’re only considering the investment, and don’t want to waste time or resources on the endeavor.

A more straightforward solution would be to pull the information from websites or APIs specifically designed for the purpose of informing investment decisions. For example, CoinMarketCap’s on-chain analysis of Bitcoin gives us a myriad of information. Additional sources include Coinmetrics’ Data Charts or Binance Research’s project reports.

Transaction count

Transaction count is a good measure of activity taking place on a network. By plotting the number for set periods (or by using moving averages), we can see how activity changes over time.

Note that this metric should be treated with caution. As with active addresses, we can’t be sure that there isn’t just one party transferring funds between their own wallets to inflate the on-chain activity.

Transaction value

Not to be confused with the transaction count, the transaction value tells us how much value has been transacted within a period. For instance, if a total of ten Ethereum transactions, worth $50 each, were sent on the same day, we would say that the daily transaction volume was $500. We could measure this in a fiat currency like USD, or we could measure it in the protocol’s native unit (ETH).

Active addresses

Active addresses are the blockchain addresses that are active in a given period. Approaches to calculating this vary, but a popular method is to count both the sender and receivers of each transaction over set periods (e.g., days, weeks, or months). Some also examine the number of unique addresses cumulatively, meaning that they track the total over time.

Fees paid

Perhaps more important for some crypto assets than others, the fees paid can tell us about the demand for block space. We could think of them as bids at an auction: users compete with each other to have their transactions included in a timely manner. Those bidding higher will see their transactions confirmed (mined) sooner, while those bidding lower will need to wait longer.

For cryptocurrencies with decreasing emission schedules, this is an interesting metric to study. The major Proof of Work (PoW) blockchains provide a block reward. In some, it’s made up of a block subsidy and transaction fees. The block subsidy decreases periodically (in events such as the Bitcoin halving).

Because the cost to mine tends to increase over time, but the block subsidy is slowly reduced, it makes sense that transaction fees would need to rise. Otherwise, miners would operate at a loss and begin to drop off the network. This has a knock-on effect on the security of the chain.

Binance 10 - What is Fundamental Analysis (FA)?

Hash rate and the amount staked

Blockchains today use many different consensus algorithms, each with its own mechanisms. Given that these play such an integral role in securing the network, diving into the data surrounding them could prove valuable for fundamental analysis.

Hash rate is often used as a measure of network health in Proof of Work cryptocurrencies. The higher the hash rate, the more difficult it is to successfully mount a 51% attack. But an increase over time can also point to growing interest in mining, likely as a result of cheap overheads and higher profits. Conversely, a decrease in hash rate points to miners going offline (“miner capitulation”) as it’s no longer profitable for them to secure the network.

Factors that can influence the overall costs of mining include the current price of the asset, the number of transactions processed, and fees being paid, to name a few. Of course, the direct costs of mining (electricity, computing power) are also important considerations.

Staking (in Proof of Stake, for example) is another related concept with similar game theory to PoW mining. Insofar as the mechanisms, though, it works differently. The basic idea is that users stake their own holdings to participate in block validation. As such, we could look to the amount staked at a given time to gauge interest (or lack of it).

Project Metrics

Where on-chain metrics are concerned with observable blockchain data, project metrics involve a qualitative approach, which looks to factors like the performance of the team (if any exists), the whitepaper, and the upcoming roadmap.

The whitepaper

It’s highly recommended that you read the whitepaper of any project before investing. This is a technical document that gives us an overview of the cryptocurrency project. A good whitepaper should define the goals of the network, and ideally give us an insight into:

The technology used (is it open source?)
The use case(s) it aims to cater to
The roadmap for upgrades and new features
The supply and distribution scheme for coins or tokens

It’s wise to cross-reference this information with discussions of the project. What are other people saying about it? Are there any red flags raised? Do the goals seem realistic?

The team

If there’s a specific team behind the cryptocurrency network, its members’ track records can reveal whether the team has the required skills to bring the project to fruition. Have members undertaken successful ventures in this industry previously? Is their expertise sufficient to reach their projected milestones? Have they been involved in any questionable projects or scams?

If there is no team, what does the developer community look like? If the project has a public GitHub, check to see how many contributors there are and how much activity there is. A coin whose development has been constant may be more appealing than one whose repository hasn’t been updated in two years.

Competitors

A strong whitepaper should give us an idea of the use case the crypto asset is targeting. At this stage, it’s important to identify the projects it’s competing with, as well as the legacy infrastructure it seeks to replace.

Ideally, fundamental analysis of these should be just as rigorous. An asset may look appealing by itself, but the same indicators applied to similar crypto assets could reveal ours to be weaker than the others.

Tokenomics and initial distribution

Some projects create tokens as a solution looking for a problem. Not to say that the project itself isn’t viable, but its associated token may not be particularly useful in this context. As such, it’s important to determine whether the token has real utility. And, by extension, whether that utility is something that the wider market will recognize, and how much it would likely value the utility at.

Another important factor to consider on this front is how the funds were initially distributed. Was it via an ICO or IEO, or could users earn it by mining? In the case of the former, the whitepaper should outline how much is kept for the founders and team, and how much will be available to investors. In the case of the latter, we could look to evidence of the asset’s creator premining (mining on the network before it’s announced).

Focusing on the distribution might give us an idea of any risk that exists. For instance, if the vast majority of the supply was owned by only a few parties, we might reach the conclusion that this is a risky investment, as those parties could eventually manipulate the market.

Financial metrics

Information about how the asset currently trades, what it traded at previously, liquidity, etc. can all come in handy in fundamental analysis. However, other interesting metrics that might fall under this category are those that concern the economics and incentives of the crypto asset’s protocol.

Market capitalization

Market capitalization (or network value) is calculated by multiplying the circulating supply with the current price. Essentially, it represents the hypothetical cost to buy every single available unit of the crypto asset (assuming no slippage).

By itself, market capitalization can be misleading. In theory, it would be easy to issue a useless token with a supply of ten million units. If just one of those tokens was traded for $1, then the market cap would be $10 million. This valuation is obviously distorted – without a strong value proposition, it’s unlikely that the wider market would be interested in the token.

On a related note, it’s impossible to truly determine how many units are in circulation for a given cryptocurrency or token. Coins can be burned, keys can be lost, and funds can simply be forgotten about. What we see instead are approximations that attempt to filter out coins that are no longer in circulation.

Nonetheless, market capitalization is used extensively to figure out the growth potential of networks. Some crypto investors view “small-cap” coins to be more likely to grow compared to “large-cap” ones. Others believe large-caps to have stronger network effects, and, therefore, stand a better chance than unestablished small-caps.

Liquidity and volume

Liquidity is a measure of how easily an asset can be bought or sold. A liquid asset is one that we’d have no problem selling at its trading price. A related concept is that of a liquid market, which is a competitive market flooded with asks and bids (leading to a tighter bid-ask spread).

A problem we might encounter with an illiquid market is that we’re unable to sell our assets at a “fair” price. This tells us there are no buyers willing to make the trade, leaving us with two options: lower the ask or wait for liquidity to increase.

Trading volume is an indicator that can help us determine liquidity. It can be measured in a few ways and serves to show how much value has been traded within a given time period. Typically, charts display the daily trading volume (denominated in native units or in dollars).

Being familiar with liquidity can be helpful in the context of fundamental analysis. Ultimately, it acts as an indicator of the market’s interest in a prospective investment.

Supply mechanisms

To some, the supply mechanisms of a coin or token are some of the most interesting properties from an investment standpoint. Indeed, models like the Stock-to-Flow (S2F) ratio are growing in popularity amongst Bitcoin proponents.

Maximum supply, circulating supply, and rate of inflation can inform decisions. Some coins reduce the number of new units they produce over time, making them attractive to investors that believe the demand for new units will outstrip their availability.

On the other hand, different investors might see a rigidly enforced cap as damaging in the long run. Such concerns may be that it disincentivizes the use of the coins/tokens as users opt instead to hoard them. Another criticism is that it disproportionately rewards early adopters, whereas a steady inflationary policy would be fairer for newcomers.

Closing thoughts

Done correctly, fundamental analysis can provide invaluable insights into cryptocurrencies in a way that technical analysis cannot. Being able to separate the market price from the “true” value of a network is an excellent skill to have when trading. Of course, there are things that TA can tell us that can’t be predicted with FA. That’s why many traders use a combination of both these days.

As with many strategies, there’s no one-size-fits-all FA playbook.