Key takeaways
- Technical analysis describes price behaviour and positioning; it does not explain causes and cannot tell you what anything is worth.
- Fundamental analysis describes issuance, usage and security spending; it says little about timing and nothing reliable about the next week.
- Mining is where the two overlap: miners owe electricity bills in fiat, which makes them structural sellers regardless of what a chart looks like.
- Both disciplines are frameworks for organising uncertainty, not machines for producing forecasts. Neither is a strategy on its own.
Ask two people why a crypto asset moved and you will often get two completely different kinds of answer. One will talk about trend, support, volume and momentum. The other will talk about issuance schedules, network usage, security spending and who is obliged to sell no matter what. These are the two broad traditions in market analysis, and a great deal of the confusion around them comes from treating them as rival prediction machines rather than as two different kinds of description.
What follows is educational. It is not a strategy to copy and it is not financial advice. The aim is narrower and more useful: to set out what each discipline is actually measuring, what it is structurally capable of telling you, and the point at which each one quietly stops working.
What technical analysis actually is
Technical analysis is the study of price and the data that travels alongside it: volume, volatility, order book depth, open interest, funding rates. It makes no claim about what a network is worth. Its working assumption is much narrower than that. It assumes that the record of what participants have already done carries information about how they are positioned now, and that positioning shapes what tends to happen next.
Most of the familiar apparatus follows from that single assumption. A moving average is a smoothing device that makes the direction of recent prices legible by stripping out noise. A support or resistance level marks a price where a lot of transacting previously happened, on the reasoning that people who bought or sold there have unfinished business. An oscillator compares recent movement against its own recent range to describe whether a move has been unusually fast. None of these are forecasts. They are compressions of history, and every compression discards something.
What it can genuinely tell you
Used carefully, technical analysis is good at description. It can tell you whether an asset is currently trending or chopping sideways, whether volatility has expanded or collapsed, and where the market has previously found enough opposing interest to stall. It can tell you how one asset is behaving relative to another over the same window, which is often more informative than either in isolation. Our markets overview and individual coin pages exist mainly to make that kind of comparison possible.
Its most underrated contribution is not signal generation at all. It is that a chart gives you natural places to define being wrong. If your reasoning rests on a level holding, the level breaking is a concrete, observable event. That is a discipline benefit, not a predictive one.
What it cannot tell you
Technical analysis cannot tell you why anything happened. A large candle looks identical whether it was caused by a policy announcement, a forced liquidation cascade, or a single participant rebalancing. It cannot tell you what an asset is worth, because it contains no information about the asset at all beyond its price history.
It also cannot make an ambiguous chart unambiguous. Patterns are far easier to identify after the outcome is known, and the same price series will support several contradictory readings depending on the timeframe and the parameters you choose. Because indicators are mathematical transformations of price rather than new information, stacking five of them does not give you five independent opinions. It gives you one opinion, restated five times, which feels considerably more convincing than it is.
What fundamental analysis actually is
In equity markets, fundamental analysis has a clear anchor: a company produces cash flows and you can argue about their size and durability. Public crypto networks have no universal analogue, which is why fundamental work here is genuinely harder and why so much of what is presented as fundamental analysis is really storytelling with a spreadsheet attached.
The parts that are measurable tend to fall into a few groups. There is issuance: how much new supply enters per unit of time, under what schedule, and whether that schedule can be changed. There is usage: fees actually paid, settlement volume, and activity that costs someone something, which matters because metrics that are free to inflate will eventually be inflated. There is the security budget: what the network spends to remain expensive to attack, and who ultimately funds it. And there is the ownership picture: treasury holdings, vesting cliffs and unlock schedules that determine whether large amounts of supply are contractually due to become sellable. Terms that keep recurring here are collected in our glossary.
The mining lens
Mining is where fundamental analysis becomes unusually concrete, and it is the reason this site treats it as a first-class subject rather than a niche. A proof of work network’s issuance goes to miners who pay for electricity, hosting and hardware in fiat currency while being paid in the mined asset. That mismatch makes miners structural sellers: a portion of newly issued coins tends to be converted on an ongoing basis simply to keep the lights on, and the pressure to convert tends to rise when margins compress.
This is a description of a flow, not a prediction of a direction. But it is a flow that a chart cannot show you, and it changes as hashrate, difficulty and energy costs move. The relationships involved are visible on our mining dashboard, and you can see how the cost side responds to different inputs using the mining profitability calculator. It is worth stressing that any such figure is an estimate built on assumptions you supply. Networks that secure themselves differently have a different cost structure entirely, which we cover in proof of work versus proof of stake.
What fundamental analysis cannot tell you
It cannot tell you when. A structural observation can remain true and unrewarded for a very long time, and markets are perfectly capable of ignoring a supply overhang until they abruptly do not. It also lacks a reliable anchor: without cash flows there is no agreed method for converting network activity into a fair value, so most valuation frameworks in this space are comparisons dressed as calculations.
Data quality is a persistent problem too. On-chain metrics are transparent but not self-explaining, and figures such as address counts or transaction totals can be inflated cheaply by anyone with a motive. Reported exchange volumes have long been treated sceptically for similar reasons. Knowing where a number came from is part of the analysis, which is why we publish our methodology.
Common failure modes in both
- Narrative fitting. Choosing the timeframe, indicator or metric that supports a conclusion you already reached.
- The precision illusion. A number carried to two decimal places is not more accurate than the assumptions feeding it.
- Borrowed conviction. Adopting someone else’s position without adopting their reasoning, their timeframe or their capacity to be wrong.
- Survivorship. Examples of a method working are always easy to find after the fact; the failures are rarely published.
Using either one honestly
The most valuable habit in either discipline is writing down, before anything happens, what observation would tell you that your reading was wrong. A framework that cannot be falsified is not analysis, it is a preference. Keep description separate from prediction: saying an asset is in a downtrend is a statement about the past, while saying it will continue is a bet with an uncertain payoff.
Finally, treat both traditions as ways of organising uncertainty rather than removing it. Neither one produces a strategy on its own, and neither substitutes for deciding in advance how much you are prepared to lose. If you are early in this, the material in our learn section and the beginner trading guides covers the groundwork before any of this becomes actionable. Nothing on this page is advice to buy or sell anything.
Frequently asked questions
Is one of the two approaches better than the other?
They answer different questions, so ranking them is a category error. Technical analysis describes the current state of a market: whether it is trending or ranging, calm or violent, and where participants have previously transacted in size. Fundamental analysis describes the machinery underneath: how new supply enters, what the network is used for, who pays for its security. A trader working over hours and a researcher working over years are not disagreeing; they are looking at different objects. The genuine mistake is using one to answer a question it was never designed for.
Do chart patterns work because they predict, or because everyone watches them?
Both explanations are plausible and they are hard to separate with the data available to a retail observer. A level becomes meaningful partly because a lot of prior transacting happened there, and partly because many participants are watching the same round number or the same moving average and act on it. That second mechanism is reflexive: the pattern holds while enough people believe it and stops holding when they do not. This is why patterns tend to look far cleaner in hindsight than they do at the right edge of a live chart.
Why does mining come up in a discussion about analysis?
Because miners are one of the few participant groups whose selling behaviour is structurally forced rather than discretionary. Electricity, hosting and hardware finance are billed in fiat currency, while revenue arrives in the mined asset. That mismatch means a share of newly mined coins tends to be converted regularly to cover costs, and the pressure to convert tends to increase when margins compress. This does not predict price. It does describe a persistent flow that a purely chart-based view will never see, which is why it belongs in the fundamental column.
Can I combine both and get a more reliable signal?
Combining them usually improves your understanding and does not necessarily improve your accuracy. Adding a second framework adds a second set of assumptions, and it is easy to end up simply collecting whichever readings agree with a view you already hold. A more honest use of the combination is as a source of disagreement: when the structural picture and the price picture point in different directions, that tension is information about how uncertain the situation really is. Treat agreement between frameworks as comfort rather than as confirmation.
Crypto writer at Cryptocurrency Miners.
