Technical Analysis Basics: Indicators, Charts, Trends

Technical analysis is the study of price history. It examines what an instrument has already done in the hope of saying something useful about the present, and it does this without any reference to whether the underlying asset is cheap or expensive in economic terms.

That description sounds either obvious or absurd depending on where you sit. This page takes the method seriously enough to explain what it actually claims, what each family of tools measures, and where the evidence says the approach runs out of road. It stays at the level of method rather than trade. You will not find setups to copy, signals to follow, or a view on where any market is going.

What technical analysis is

Every technical method rests on three assumptions, and it is worth seeing them stated plainly because everything else follows from them.

The first is that price already reflects the available information. Whatever anyone knows about interest rates, earnings, supply or sentiment has already been acted on by someone, and the result is the number on the screen. A technical analyst therefore studies the number rather than the reasons behind it.

The second is that prices move in trends rather than purely at random, at least some of the time. If price movement were entirely unpredictable from its own history, there would be nothing to study.

The third is that market behaviour repeats, because the participants are human and respond to similar situations in similar ways. Fear and greed produce recognisable shapes in a price series, and those shapes recur across instruments and across decades.

The first assumption is uncontroversial and shared with mainstream finance. The second and third are where the argument lives, and the evidence section below covers what researchers found when they tested them.

How it differs from fundamental analysis

Fundamental analysis asks what something is worth. It examines earnings, cash flow, balance sheets, interest rate differentials, trade balances, supply and demand, and arrives at a view on value. If the market price sits below that estimate, the fundamental analyst considers the asset cheap.

Technical analysis asks what the price is doing. It takes no view on value at all. A technical analyst can work on an instrument without knowing which company or country produced it, because the input is the price series and the output is a statement about that series.

The two methods answer different questions and operate on different clocks. A fundamental view can be correct and take years to be reflected in the price. A technical observation concerns the here and now and says nothing about whether the instrument is worth holding.

In practice most participants use both, and the division is far less tribal than the literature suggests. A trader might form a directional view from interest rate expectations, then use a chart to decide where that position stops making sense. Fundamental analysis frames the question. Technical analysis frames the risk.

What a price chart actually shows

A chart is a compression of transactions into a picture, and understanding what survives that compression matters more than choosing a chart style.

Each bar or candle summarises a fixed period with four numbers: the price at which the period opened, the highest price traded, the lowest price traded, and the price at which it closed. Those four numbers replace potentially thousands of individual transactions.

The compression is severe, and what disappears is the sequence. A bar with a high well above its close tells you the price got up there and came back. It does not tell you when within the period that happened, how long it stayed, or how much traded at each level. Two bars that look identical can represent completely different sequences of events.

Timeframe is a choice about how much detail to discard. A five-minute chart preserves intraday structure and buries the multi-month picture in noise. A weekly chart does the reverse. Neither is more real than the other. Both are views of the same underlying transactions at different resolutions, which is why a market can be trending upward on one timeframe and downward on another without any contradiction.

Volume deserves a specific caution in leveraged trading. On an exchange-traded instrument, volume counts the units actually transacted and is genuine information. Foreign exchange has no central exchange, so what platforms display for a currency pair is usually tick volume, which counts how many times the price updated rather than how much was traded. It correlates with activity and works as a rough gauge of participation, but it is not the same measurement, and treating it as though it were leads to conclusions the data cannot support.

Trend, and what the word actually means

Trend is the central concept in the field and the most commonly misused.

Operationally, an uptrend is a price series making successively higher peaks and higher troughs. A downtrend is the reverse. When neither pattern holds, price is ranging, which is a description rather than a failure state and is how markets spend a large share of their time.

The important point is that a trend describes what has already happened. Calling a market an uptrend says it has been making higher highs and higher lows up to this moment. It carries no information about whether that will continue, and the definition contains no mechanism that would make it continue. Every trend in history ended, and the method that identified it gave no warning of when.

Trend is also relative to timeframe, which produces most of the confusion beginners experience. The same instrument can be in a multi-year uptrend, a three-month downtrend and a two-day uptrend simultaneously, all correctly identified. Before any statement about trend means anything, the timeframe has to be specified.

Support, resistance and why levels matter

A support level is a price area where falling prices have repeatedly stopped and turned. Resistance is the same idea for rising prices. These are the oldest concepts in the field and the most durable, and the reasons they work are more interesting than the concepts themselves.

Orders cluster at round numbers and at previously significant prices, because people think in round numbers and remember what a market did the last time it was here. Participants who missed a move want a second chance at the level where it started. Participants holding a losing position from that level want to exit at breakeven. Stop-loss orders accumulate just beyond it. And because a large number of participants are watching the same obvious levels, their collective attention makes the level partly self-fulfilling.

That last point cuts both ways. A level everyone can see is a level where orders concentrate, which is exactly why price reacts there and also why those orders become a target. The most obvious level on the chart is where the most stops are sitting.

Levels are zones rather than lines. Treating a level as a single price to the fifth decimal implies a precision the underlying behaviour does not have.

The indicator families

An indicator is a calculation performed on price history and plotted so a pattern becomes easier to see. Every indicator is a transformation of data already on the chart. None of them introduces new information, which is the single most useful thing to understand about the entire category.

Indicators sort into a handful of families according to what they measure.

Trend indicators smooth the price series to make direction visible. A moving average is literally the mean of the last several closing prices, recalculated each period. MACD compares two such averages of different lengths. Their purpose is to strip out enough short-term variation that the underlying direction shows through.

Momentum indicators, often called oscillators, measure how fast price has moved recently rather than how far it has gone. RSI, published by J. Welles Wilder in 1978, expresses recent gains against recent losses on a bounded scale. Conventional readings describe conditions as overbought or oversold, and those two labels are the most widely misread words in the field. They describe recent speed, not what happens next. A strongly trending market can hold an extreme momentum reading for weeks while continuing in the same direction.

Volatility indicators measure dispersion. Average True Range, also from Wilder, expresses the typical size of recent price movement in the instrument's own units. Bollinger Bands, developed by John Bollinger, plot a band a set number of standard deviations either side of a moving average, so the band widens and narrows as volatility changes. Neither family says anything about direction, and their most defensible use is sizing positions and setting stop distances proportionate to how much the instrument actually moves.

Volume indicators attempt to gauge the conviction behind a move. They carry the most meaning on exchange-traded instruments and the least in foreign exchange, for the reason given above.

Why indicators lag

This is a mathematical property rather than a flaw in any particular tool, and no setting removes it.

Every indicator is a function of prices that have already occurred. A twenty-period moving average is an average of the last twenty closes. For it to change direction, enough new closes must accumulate to shift the mean, and that takes time by construction. The indicator cannot turn before the price does, because the price is its input.

This produces a trade-off with no solution. A longer averaging period gives a smoother, more reliable signal that arrives later. A shorter period reacts faster and produces far more false readings, because it responds to noise as readily as to genuine change. Every setting on every indicator is a position on that trade-off, and the search for a configuration that is both fast and reliable is a search for something that does not exist.

The practical consequence is that indicators describe conditions rather than anticipate them. They are instruments for reading the present state of a series with less noise than the raw price, and reading them as forecasts is a category error.

Why no setup is predictive

The strongest criticism of technical analysis targets the evidence rather than the idea. Demonstrating that a method works is far harder than it appears, and most demonstrations fail once tested properly.

The core problem is the size of the search. There are thousands of possible indicators, each with adjustable settings, applicable across dozens of instruments and many timeframes, combinable in almost unlimited ways. Search that space long enough and rules that performed beautifully on historical data will appear, whether or not any real relationship exists. The same thing happens when the search runs on randomly generated price series, which produce chart patterns visually indistinguishable from real ones.

This is the data snooping problem, and the academic literature has confronted it directly. The most cited review of the field, by Park and Irwin in the Journal of Economic Surveys, examined 95 modern studies of technical trading profitability. Of those, 56 found positive results, 20 found negative results and 19 were mixed. That distribution is more favourable to the method than its harshest critics allow, and the authors immediately qualified it: most of the studies were subject to data snooping, to selecting trading rules after seeing the results, and to difficulty in properly accounting for risk and transaction costs.

Where later researchers corrected for the size of the implicit search space using bootstrap methods, results that had looked convincing in earlier work weakened substantially or disappeared. The performance was real within the sample. It was not evidence of a relationship that would persist outside it.

Several further limits sit alongside that one. Markets adapt, so a pattern that genuinely works attracts participants whose activity changes the behaviour that produced it, and any edge based on a widely visible pattern carries the seed of its own decay. Costs are frequently omitted from the demonstration, and a rule producing a small statistical edge per trade can be comfortably profitable in a backtest and reliably unprofitable in practice once the spread, commission and slippage of each round trip are subtracted. Sample sizes are almost always too small to distinguish a genuine edge from a run of luck. And the information environment is distorted, because charts posted publicly are overwhelmingly the ones that worked, marked up after the fact, when the same indicator gave the same reading dozens of other times that week and went nowhere.

What the method is genuinely useful for

Setting the predictive claims aside, several uses survive the criticism above intact, and they are why the method persists among people who are honest about its limits.

• Defining where a view is wrong. A chart shows a level at which the reason for holding a position stops being valid, which makes a stop placement a considered decision rather than a tolerance for pain. This is the single most useful thing a chart does.

• Sizing positions to actual volatility. A volatility measure tells you how far an instrument typically moves, so a stop can sit outside ordinary noise and a position can be sized so that reaching it costs a predetermined amount.

• Imposing consistency. A written method based on observable chart conditions produces repeatable decisions, and repeatable decisions generate a record that can be evaluated. Without repeatability there is nothing to evaluate.

• Providing a common vocabulary. Because so many participants watch the same levels, those levels matter as a description of where attention and orders are concentrated, independent of any predictive claim.

• Timing an entry within a view formed elsewhere. Analysis of interest rates or supply can produce a directional opinion, and a chart can inform where to act on it and at what size.

Most of those are about managing risk rather than forecasting price. That distinction is the difference between using the method and believing in it.

How this applies across instruments

The principles above are general, and how they apply varies considerably by market. Each instrument has its own liquidity profile, its own active hours and its own characteristic behaviour, all of which affect how chart information should be read.

Gold moves on real interest rates and the dollar, carries a large daily range in dollar terms, and concentrates its activity around the London and New York sessions, covered in the gold trading guide. Currency pairs differ sharply in liquidity and cost, and the majors behave differently from crosses and exotics, set out in the guide to major currency pairs. Index instruments are shaped by their weighting method and by the fact that the underlying cash market is closed for much of the time the instrument is quoted, explained in the index trading guide.

This page also stops deliberately short of intraday application. Whether short-horizon trading is a sensible activity at all, and what it costs, is a separate question examined in the article on whether day trading is worth it.

Frequently asked questions

What is technical analysis in simple terms?

It is the study of price history to inform decisions about the present. It uses charts and calculations performed on past prices, and it takes no view on whether the underlying asset is fairly valued.

Which is better, technical or fundamental analysis?

They answer different questions. Fundamental analysis addresses what something is worth and operates over long horizons. Technical analysis addresses what the price is doing and operates over short ones. Most participants use elements of both, with fundamentals framing the view and charts framing the risk.

What are the most common technical indicators?

Moving averages and MACD for trend, RSI and stochastic oscillators for momentum, and Average True Range and Bollinger Bands for volatility. All of them are calculations performed on price data already visible on the chart.

Do technical indicators actually work?

The academic evidence is genuinely mixed rather than uniformly negative, though positive findings weaken considerably once researchers correct for how many rules were tested before the successful one was found. Treat any specific claim about any specific setup with the scepticism that history warrants.

Why do indicators give false signals?

Because they are calculated from past prices and cannot anticipate anything. A faster setting reacts sooner and produces more false readings, a slower setting produces fewer and arrives later, and every configuration sits somewhere on that trade-off.

How many indicators should I use?

Adding more from the same family produces the illusion of confirmation rather than actual confirmation. Several trend indicators computed from the same price series will agree with each other most of the time by construction, which tells you nothing you did not already know.

Does technical analysis work the same on all markets?

The principles are general, but liquidity, session hours, gap behaviour and the reliability of volume data differ substantially between currencies, commodities, indices and individual shares. A method developed on one instrument should not be assumed to transfer to another.

Where should a beginner start?

With the raw price chart rather than with indicators. Learning what a price series looks like across timeframes, where it has previously reacted and how much it typically moves gives you the context that indicators are supposed to summarise. Adding tools before that foundation exists tends to replace understanding with confirmation.

You can explore charting tools and open a demo account at www.axonmarkets.com.

Risk warning: CFDs are leveraged products and carry a high level of risk. Losses can exceed the margin committed to a position and can consume your entire account balance. CFDs are not suitable for all investors. Make sure you understand how these products work and whether you can afford the risk of losing your money. This article is educational information only. It is not investment advice, a recommendation, or an offer to trade, and it does not take account of your objectives, financial situation or needs.

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