Decoding Crypto Economic Data: Key Metrics for Evaluation

Cryptocurrency is an informational super-highway.

Always moving.

Always changing.

Price aside, there are so many different types of data we encounter in crypto that it quickly gets overwhelming & confusing.

What data do we look at?

What do we do with that data?

Is the data even real?

Answer: Who cares, just ignore it all & blindly buy every sh*tcoin trending on Twitter.

This is a joke, don’t do this.

Although, if you’re a savant trader, it might just work… (Never, FA)

🧠 Prerequisite Knowledge 🧠

Crypto is fraught with fraud... There are no heroes…

The lack of regulation & the nature of a pseudonymous ecosystem lends itself to bad behavior (meh). I’m not saying that this is true for every asset, but I am also not saying that it is not… DYOR.

There are three general categories of fraudsters in the crypto space:

1) Market Makers — Possibly the dirtiest job in all of finance; their JOB is to trick you out of your money.

2) Influencers — fake preachers that don’t give a shit about you. There are good people in space; odds are these people won’t ask you for anything, won’t try to sell you anything & most likely, won’t even try to fight for your attention.

3) Shitcoins — why do you think something called MOONelonDOGE is even created? Do you genuinely believe it is to “fix the financial world” & make you rich? If you are involved in something called MOONelonDOGE maybe it’s worth re-evaluating your thesis. (still NFA)

Above everything, if you fall victim to any of these things, it is not their fault; it is only your own fault for not thinking clearly or knowing how to operate around them.

Metrics can be (and usually are) manipulated.

The holy grail of market manipulation in crypto shines through in volume & botnets that promote garbage assets.

Metrics are lagging indicators.

Things that can be measured, usually are, and therefore are already priced in. (see manipulated above)

Metrics only tell 1 side of the story.

Cold hard data is great for painting a basic picture, but other factors must always be considered when conducting an analysis, including the general market state (bull/bear), the technicals (i.e. basic design/developer activity), & the fundamentals (news/updates).

On-Chain & Off-Chain

There are two general types of data that exist in the cryptoverse, On-Chain & Off-Chain.

→ Off-chain pertains to factors that are not native or directly important to the function of the underlying technology; such as the price/volume (Bitcoin does not know or care that is worth $25,000 or $100,000).

→ On-Chain data pertains to internal factors such as the amount of bitcoins existing in a wallet or the hash rate. (Bitcoin knows the state of all UTXOs & how many miners are online)

🎯 The Evaluation Metrics 🎯

This list is by no means exhaustive. The below metrics are the most commonly used & fundamental for conducting a base analysis. They will be a mixture of both on/off-chain.

So let’s go:

➡ Price - the how much.

This one is pretty straightforward— how much are people paying for one unit of value? Deceptively simple on the surface, price is actually an informationally dense piece of data that contains a lot of value (when used properly).

Price is the most common data point of all. What is not commonly understood, or not addressed in the regular conception of price, is that beyond just how much others are willing to pay is the question of what they are paying in.

In the case of BTC many people are used to denominating it in USD; however, Bitcoin trades against THOUSANDS of different crypto & Fiat assets, which themselves fluctuate in price against one another.

➡ Market Cap - the big tell.

The total value of the Asset Network. Calculated by taking the total amount of coins/tokens in circulation & multiplying them by the unit price. Underutilized for decision-making, the market cap can be very useful for detecting potentially undervalued projects much better than just price alone. Likewise, it can help signal overvalued projects.

➡ Circulating Supply - the count.

Not very useful on its own, circulating supply expresses the current number of a token that is available on the market at any given time.

Be advised, that most of the time this measurement will be slightly off as many tracking tools don’t know how to distinguish the token types & require manual input. Moreover, mature protocols have a delayed release function even after a token is mined.

The best example is Bitcoin. Even though every 10 minutes there is a block reward of (6.25BTC) earned by miners, the protocol does not allow the miners to move those new bitcoins for 100 blocks.

➡ Total/Max Supply - the inflation plan.

the final amount of a cryptocurrency that there will be at the end of the planned emission. Not always important for short-term decisions but very important for crafting a long-term investment strategy.

If an asset has a market cap of >$1,000,000,000 but only 10% of the supply is circulating, odds are that as new tokens are added into circulation they will dilute the price.

➡ Volatility - widow-maker of the untrained trader.

The severity of movement in price over short time frames. This is not a metric that is typically easily available to find; rather it must be extrapolated on its own.

As an example, take any token & measure the % change from the lowest price point to the highest price point on any timeframe (recommended Daily). So if Bitcoin on any given day hits a low of $22,500 & a high of $23,500; the volatility is ~4.34% (Price difference ($1000)/its average price ($23,000)

➡ *Volume - the sound of noobs getting rekt.

What volume shows is the amount of money that is traded through an asset. So, if the volume for Bitcoin on any day is $100,000,000 that is supposed to mean that people trade $100m that day… briefly mentioned earlier, volume is among the most unreliable of metrics because of how easy it is to fake. The reliability of volume is basically null. Alone, it does not explain anything; when used in conjunction with other metrics, it helps formulate an understanding of the consumer's behavior.

➡ Velocity - the truth of the volume.

the amount of time a single token trades hands. Very tricky to pin down exactly, velocity expresses two concepts very well:

1. It shows the difference between traders & holders. Which helps paint a picture of the kind of people that are attracted to the project. Traders are short-term thinkers that show high levels of velocity, meanwhile, investors are long-term thinkers that show low levels of velocity.

   
   

2. It is a great way to truly see what projects are involved in real market activity vs. those that are just washing tokens between themselves. If there are less than 100 wallets with the vast majority of tokens (>80%) it would be pretty safe to assume the project is faking it’s economic activity.

➡ Amount on Exchange - the real sensitivity.

this relates to circulating supply & volatility. The more of a given token there is on an exchange, the higher its liquidity, & the stronger its price. The less of a given token there is, the easier it is to impact the price.

➡ Ranking - nothing really.

means of organizing crypto assets by some arbitrary data point. The most common ranking methods are by market map size or by volume. Two points that are very neutral at best. Using the ranking of a digital asset to make a decision is very unsound; it should only be used for organizational purposes by service providers.

➡ Hash rate - the measure of security.

This is a Proof-Of-Work metric. The amount of resources that are being used to secure the network. This is almost irrelevant for short-term analysis & quintessential for gauging the overall health trend of a network. If over the course of time, the hash rate goes up, it means that more resources are being utilized to support the network, meaning that more people are placing their vote of confidence in its growth.

It might be worth noting, that an increased hash rate doesn’t always mean more machines; It could mean improved software or better machines.

➡ Total Addresses - the baseline.

The amount of “users” a network has. This is a measure that is similar to volume in the sense that it is extremely easy to fake it is & nearly impossible to find out the truth.

In the simplest of terms, this number must always be growing. Foremost, this number can never go down… Once an address is used, it’s added to the tally forever… If this number stays absolutely flat for a prolonged period of time… it basically means the project is dead.

➡ Active Addresses - the cover-up.

The amount of “real users” a network has. Typically deduced from a 7-day rolling average, a 30-day rolling average & a 180-day average. This number will fluctuate based on the measuring algorithm techniques.

As is with the Total Address count; this can be used to gauge the level of adoption. If you see the number of active addresses sharply drop or stay absolutely flat for a prolonged period of time… it basically means the project is dead.

➡ Emission Schedule - the inflation sensation.

The planned inflation/release of new tokens into the marketplace. This is one of those “priced in by the big players” kind of metrics. Keeping an eye on, or at least, being well aware of the rate of circulating inflation will give you a strong sense of the overall directional steps of a project.

How to use Metrics

The use of metrics will always boil down to reasoning. Traders will use different metrics to evaluate their options than investors will.

Ultimately, the only reason to use metrics is to find patterns.

There is no single way to use any single data in order to make a proper evaluation; so whenever conducting any evaluation you must use a combination of metrics that WORK BEST IN YOUR PERSONAL SITUATION.

First, identify your own use case (are you long-term or short-term).

Then, find an asset you like & dive deep into it. (always recommend Bitcoin) Evaluate all of the metrics one by one; don’t rush. Repeat this a few times with different assets until you have enough data. (Try 10 different assets)

Cross-reference the outcomes of each asset, study the results of your analysis & come up with a conclusion. Figure out which metrics you can trust, how you prefer to prioritize them & does that logic hold up consistently across different assets.

Look for patterns.

There are many more exotic metrics than the ones in this post.

Many new ones are being discovered constantly, while many older ones become obsolete as the landscape of the industry changes.

Be willing to be wrong.

The Faster you make mistakes, the faster you will find success.

Here is a huge list of resources to help you find all the necessary tools on your journey — “The 2023 Crypto & Defi Resource Megalist”.

Also published here.