Module 4: Technical Analysis for Crypto
What Technical Analysis Is, and What It Isn't
Chapter 1 of 16 · about 5 minutes
1.1 Lines on a chart
Mint had been following crypto traders on social media. Every day, they posted charts covered in lines, arrows, coloured zones, and confident predictions. "BTC breaking out of this triangle, target $120k." "ETH rejected at resistance, heading lower."
"Do these lines actually work?" Mint asked. "Or is it astrology for money?"
Node, who had invested in stocks for years, laughed. "I've always thought it was astrology."
"It's neither magic nor nonsense," said Hash. "It's a way of organising what the market has done, so you can make decisions with a plan instead of a feeling. Used well, it helps you manage risk. Used badly, it gives you false confidence. This module is about using it well."
1.2 What technical analysis is
Technical analysis (TA) is the study of price, volume, and related market data to understand market behaviour and make trading decisions. Instead of asking "what is this asset worth?", it asks "what are buyers and sellers doing, and what might they do next?"
Its sister discipline, fundamental analysis, asks the first question: what is the asset worth, based on its supply, usage, revenue, and other factors? That's the subject of Module 5. Many traders use both: fundamentals to decide what to trade, and technicals to decide when and how.
| Technical analysis | Fundamental analysis | |
|---|---|---|
| Main question | What are buyers and sellers doing? | What is this asset worth? |
| Main inputs | Price, volume, market data | Tokenomics, usage, revenue, team, competition |
| Typical timeframe | Minutes to months | Months to years |
| Main use | Timing entries and exits, managing risk | Choosing what to own |
1.3 The core assumptions
Technical analysis rests on three ideas.
Price reflects available information. News, sentiment, and expectations show up in what people actually buy and sell. The chart is the record of those decisions.
Prices tend to move in trends. Once a market starts moving in a direction, it often continues for a while, because trends are driven by shifts in supply and demand, and by crowd behaviour, which doesn't change instantly.
Behaviour repeats. Fear, greed, hope, and regret are constant across markets and generations. Similar situations tend to produce similar reactions, which create recognisable patterns.
"So TA is really crowd psychology drawn as a picture," said Mint.
"That's a good way to put it," said Hash.
1.4 Why it can work
Technical analysis works partly because it captures real behaviour, and partly because so many traders use it.
If thousands of traders believe $100,000 is an important level for Bitcoin, many of them place orders near it. Those orders affect how price behaves around that level. This is sometimes called a self-fulfilling prophecy, and it's especially relevant in crypto, where a large share of traders follow the same indicators and levels.
Technical analysis also gives structure to decisions. Instead of buying because "it feels like it's going up," a trader using TA defines where they'll enter, where they'll admit they're wrong, and where they'll take profit. That structure is valuable even when individual predictions fail.
1.5 Why it often doesn't
Node wasn't convinced. "But plenty of people draw lines and lose money."
"Most of them, in fact," said Hash.
Technical analysis has real limits.
It's about probabilities, not certainties. A pattern that works 60% of the time fails 40% of the time. Traders who expect certainty get hurt.
It's easy to see what you want to see. Two traders can look at the same chart and draw opposite conclusions. People tend to find patterns that confirm what they already believe.
News overrides charts. A hack, a regulatory decision, or an exchange failure can make any chart pattern irrelevant within minutes.
Hindsight makes everything look obvious. Patterns look perfect on past charts because you know how they ended. In real time, they're messy and uncertain.
Popular signals get crowded. When everyone sees the same setup, large players may trade against it, triggering stop-losses before moving in the expected direction.
1.6 Crypto quirks
Technical analysis was developed mainly for stock and commodity markets. Crypto differs in ways that matter, building on Module 1, Chapter 6.
| Crypto feature | Effect on technical analysis |
|---|---|
| Trades 24/7 | No opening or closing gaps on most charts; the daily "close" is a convention, usually midnight UTC |
| Prices differ across venues | Charts from different exchanges can show slightly different highs, lows, and volume |
| Some volume isn't genuine | Wash trading on some venues can distort volume-based signals (Chapter 7) |
| Heavy leverage | Liquidation cascades create sharp wicks and fast moves through levels |
| Smaller, younger markets | Smaller tokens can be moved by single players, making their charts less reliable |
| Thin weekend and overnight liquidity | Moves at quiet times can be exaggerated or reversed later |
| Extra data sources | Funding rates, open interest, and on-chain data add context (Chapter 15) |
A practical consequence: technical analysis tends to be more reliable on large, liquid assets like Bitcoin and Ethereum than on small tokens with thin trading.
1.7 How to use this module
Each chapter introduces one tool or idea, with worked examples using illustrative prices. As you go, keep three principles in mind.
- No single tool is enough. Signals become more useful when several agree, which is called confluence.
- Risk management matters more than accuracy. A trader who's right 40% of the time with good risk management can do better than one who's right 60% of the time without it. Chapter 16 shows why.
- Practise before risking money. Study charts, write down your analysis, and check later how it played out. Paper trading costs nothing.
"So the goal isn't to predict the future," said Mint.
"The goal is to make decisions where the possible gain is worth the possible loss, again and again," said Hash. "Charts help you find those decisions."
This module is educational and isn't trading advice. Every example uses illustrative prices.
1.8 Try it yourself
Find three crypto chart predictions posted publicly at least a month ago. For each, write down what was predicted and what actually happened. Did any include a level where the trader would admit they were wrong? Notice how much more useful the predictions with clear "invalidation" levels are.
Key takeaways from this chapter
- Technical analysis studies price, volume, and market data to understand buyer and seller behaviour.
- It complements fundamental analysis: one helps with when, the other with what.
- It assumes prices reflect information, trend over time, and repeat patterns of behaviour.
- It can work through real crowd psychology and self-fulfilling behaviour, and by adding structure to decisions.
- It deals in probabilities, is prone to bias, and can be overridden by news.
- Crypto's 24/7 trading, fragmented venues, leverage, and thin liquidity require adjustments.
- Use confluence, prioritise risk management, and practise before risking money.