What technical analysis is
Technical analysis is the practice of studying past market data, mainly price and trading activity, to describe what a market has been doing and to form views about what it might do next. Instead of asking what an asset is worth, it asks how the market has been behaving. The inputs are simple: the open, high, low and close of each time period, and the amount traded.
From those inputs, analysts draw lines on charts, calculate indicators and look for recurring shapes. The same toolkit is used in stock, currency and commodity markets, and it was carried over to cryptocurrency charts because crypto trades around the clock and publishes complete price histories.
This article is educational. It describes how the method works and what is argued about it. It is not a recommendation to buy or sell anything, and nothing here is financial advice.
The three core assumptions
Most descriptions of the method rest on three ideas.
- Price reflects available information. Supporters argue that news, opinion and expectations are already folded into the price, so the chart is a summary of everything that matters.
- Prices move in trends. The belief is that once a direction is established, it is more likely to continue than to reverse, at least for a while.
- History tends to repeat. Because markets are made of people reacting to gains and losses, similar behaviour is said to produce similar chart shapes.
Each assumption is debatable. The first is close to a claim made in academic finance, yet the same claim is used by critics to argue that past prices cannot help predict future ones. The second and third are observations that may hold in some periods and fail in others.
What a chart actually shows
A price chart is a record of agreements: each point is a price at which a buyer and a seller transacted. Candlesticks pack four numbers into one shape per period, and a bar underneath usually shows how much was traded. Readers who want to learn how to read candlestick charts will find that the shapes are only a compact way to display the same open, high, low and close data.
Timeframe matters. A chart of one-minute candles and a chart of weekly candles of the same coin can look completely different, and a trend on one may be invisible on the other. Analysts often look at several timeframes to avoid mistaking noise for direction.
The main families of tools
Technical tools are usually grouped by the question they try to answer.
- Trend tools describe direction and are often built from averages of past prices.
- Momentum tools compare recent gains with recent losses to describe how strong a move has been.
- Volatility tools describe how wide recent price swings were, which relates to price volatility in general.
- Volume tools look at how much activity accompanied a move, since a move on heavy trading volume is often treated as more meaningful than one on thin activity.
- Structure tools mark areas where price has repeatedly turned, such as support and resistance levels.
The point at this stage is that they are all calculations on the same history, so they often agree with one another simply because they share the same inputs.
How it differs from other approaches
Technical analysis is one of several ways people study markets. Fundamental analysis looks at the underlying business or network: its use, its rules and its economics. On-chain analysis reads the public ledger for signs of how coins are moving and who is holding them. Market sentiment work tries to measure the mood of participants. Many people mix these, and none of them is a guarantee of anything.
Criticisms worth knowing
A fair introduction has to include the objections.
Weak evidence of reliable prediction. Academic work on price behaviour has often found that simple chart rules do not beat basic benchmarks once costs are included, although results vary by market and period. The idea that prices may follow something close to a random walk is the central challenge to the whole approach.
Subjectivity. Two analysts can draw different trend lines on the same chart and reach opposite conclusions. Because the rules are loose, almost any outcome can be explained after it happens.
Self-fulfilling and self-defeating effects. If many traders watch the same level, their behaviour may affect price around it. But the effect is unstable, and it can disappear once it is widely known.
Hindsight bias. Looking back at a chart, patterns look obvious. Reading them forward in real time, with an unknown future, is far harder.
Crypto-specific issues. Crypto markets are young, fragmented across many venues, and sometimes thin. Prices can be moved by a single large order, by leverage, or by news that no chart anticipated. Reported volume can also be unreliable.
Using the method sensibly
People who study technical analysis responsibly tend to treat it as a way to describe and organise information, not as a forecasting machine. A few habits follow from that.
- Treat indicators as descriptions of what has happened, not instructions.
- Be wary of any claim that a pattern or indicator works reliably.
- If testing an idea, use data the idea was not built on, and include trading costs.
- Keep risk management ahead of any chart signal; the amount you could lose matters more than any pattern.
- Remember that cryptocurrency prices are highly volatile, that past performance does not predict future results, and that people can lose everything they put in.
Where to go from here
A useful next step is to look at the tools one at a time: how an indicator is calculated, what it shows and what it does not. Approaching them as a way to understand what chart tools really do is likely to be more useful than hunting for a rule that promises results. Learning the calculation behind an indicator also makes its weaknesses easier to see.