Every discipline has its foundational principles — the bedrock ideas that everything else is built upon. For technical analysis, those foundations are surprisingly few in number, yet remarkably far-reaching in their implications. Before a trader learns to read a single chart pattern or calculate a single indicator, it helps enormously to understand what technical analysis actually is, what it assumes about the world, and why those assumptions give it such broad applicability across markets. This article addresses all three, and closes with the single most important piece of raw data in the technical analyst’s toolkit: the price record itself.

A Tool That Travels Well

One of the most practical advantages of technical analysis — and one that is often underappreciated by those just beginning to explore it — is the sheer breadth of its application. A trader who masters the discipline using FTSE 100 equities does not need to start from scratch when they decide to look at crude oil futures, currency pairs, or government bonds. The method transfers cleanly across asset classes because it is built on a universal foundation: price data over time.

This portability sets technical analysis apart from most other research methods. Consider fundamental analysis as a point of contrast. Applied to equities, fundamental analysis demands a deep understanding of financial statements — profit and loss accounts, balance sheets, cash flow statements, and the ratios derived from them. It requires familiarity with corporate governance, dividend policy, competitive positioning, and earnings quality. That is already a substantial body of knowledge. But the moment a fundamentally oriented equity analyst turns their attention to, say, soft commodities or energy markets, the entire framework changes. Analysing wheat or coffee means examining harvest cycles, rainfall data, storage inventories, and global demand patterns. Analysing natural gas means understanding seasonal consumption curves, pipeline infrastructure, and geopolitical supply risks. The underlying logic of the analysis differs for every asset.

Technical analysis sidesteps this entirely. An indicator such as the Relative Strength Index operates identically whether it is being applied to a share of Barclays, a contract for Brent crude, or a sterling-to-dollar exchange rate. A moving average crossover on a daily chart of gold behaves according to exactly the same principles as one applied to a daily chart of a government gilt. The analyst’s skill is built once and deployed anywhere, provided that one essential condition is met: the asset must have a historical time series of price data.

This condition is almost always satisfied in modern markets. Whether you are trading equities on the London Stock Exchange, futures on the ICE exchange, currency pairs on the foreign exchange market, or government bonds, price histories stretching back years or decades are readily accessible. The charts may look different in scale and character, but the analytical tools work the same way across all of them.

From Newspaper Columns to Global Markets

Technical analysis did not emerge fully formed. It developed gradually over more than a century, shaped by the observations of market practitioners rather than academic theorists, and its intellectual roots are traceable to a small number of pioneering figures whose work still underpins the discipline today.

The story begins with Charles Dow, an American financial journalist who co-founded the Dow Jones & Company and served as the first editor of The Wall Street Journal. Between 1900 and 1902, Dow published a series of editorials in which he articulated his observations about how markets move. He noticed that stock prices tend to follow trends, that those trends persist for extended periods, and that the behaviour of the market as a whole tends to reflect the collective knowledge and expectations of all its participants.

Dow never compiled his ideas into a single formal work. After his death in 1902, his successor at The Wall Street Journal, William Peter Hamilton, continued to develop and apply his framework. It was Robert Rhea who, in 1932, gathered and codified the writings of both men into what became known as Dow Theory — the first systematic attempt to describe how financial markets behave and how price trends can be identified and followed.

Dow Theory established several principles that remain central to technical analysis to this day: that markets move in primary, secondary, and minor trends; that the primary trend has three distinct phases (accumulation, broad participation, and distribution); and that a trend should be assumed to remain in force until it gives definitive signals of reversal. These ideas were not abstract — they were drawn from decades of observation of actual market behaviour.

The next major milestone came in 1948, when Robert D. Edwards and John Magee published Technical Analysis of Stock Trends. Often described as the bible of technical analysis, the book formalised the study of chart patterns, trendlines, and support and resistance levels. Magee, frequently cited as the father of technical analysis as a structured discipline, spent years working in near-isolation from market commentary, relying entirely on price charts to make trading decisions. Edwards brought rigour to the study of pattern formation. Together, their work gave technical analysis an intellectual framework robust enough to survive decades of scrutiny and remain a standard reference to this day.

Meanwhile, running parallel to the Western tradition, an entirely independent framework had emerged centuries earlier in Japan. Rice traders in the Dojima Rice Exchange in Osaka began using candlestick charts as early as the 18th century to track price movements and identify recurring patterns in market behaviour. This method, refined over generations and later introduced to Western traders in the 1980s and 1990s, proved to complement the Western charting tradition so naturally that candlestick charts are now the dominant visual format used by technical analysts worldwide.

The digitisation of markets accelerated everything. When real-time price feeds and personal computers became accessible in the 1980s and 1990s, and when internet-based charting platforms arrived in the early 2000s, technical analysis moved from the preserve of professional traders and specialist analysts to become accessible to any retail participant with a brokerage account and an internet connection. Today, platforms such as TradingView give individual traders in the United Kingdom access to the same charting tools, price history, and indicator libraries that were once available only to institutional desks.

The Four Pillars of the Discipline

Technical analysis rests on a small number of core assumptions. These are not proven mathematical theorems — they are working principles, derived from long observation of market behaviour, that technical analysts accept as reliable enough to guide decision-making. Understanding them is not merely academic; it shapes how a technical trader thinks about every chart they study.

Markets Discount Everything

The first and most fundamental assumption is that the current price of any freely traded asset already reflects all available information. Every known fact about a company, every macroeconomic data point, every piece of insider expectation, every geopolitical development that could affect supply or demand — all of it has already been processed by the market and incorporated into the price. The price at any given moment is, in this sense, the ultimate summary of everything that is known or anticipated.

This idea has deep roots in Dow Theory, which held that the averages discount everything because they reflect the combined activities of thousands — sometimes millions — of participants acting simultaneously on their best available information. It also echoes the efficient market hypothesis developed later in academic economics, though technical analysis and academic finance draw very different practical conclusions from the same underlying observation.

For the technical analyst, this assumption is enormously liberating. It means that the analyst does not need to read every earnings announcement, track every central bank speech, or build detailed economic models. All of that information has already been absorbed into the price. The chart is the complete summary — and it is the chart the analyst reads.

Price Moves in Trends

The second core assumption is that price does not move randomly. It moves in trends — sustained directional movements that can be identified, followed, and traded. This idea was central to Dow’s original writings and remains the conceptual bedrock of most technical strategies. The practical implication is significant: if price is already moving upward and nothing has changed to interrupt that movement, then the most probable near-term direction is still upward. The trend, until it signals otherwise, is your working hypothesis.

Trends exist across all timeframes. A primary trend might persist for months or years. Within that trend, secondary counter-trend movements will occur — corrections and pullbacks that temporarily move against the primary direction. And within those, minor fluctuations create the day-to-day noise of the market. Technical analysis provides tools to identify and distinguish between all three levels, which is why timeframe selection is one of the first decisions any technical trader must make.

History Tends to Repeat Itself

The third assumption concerns human behaviour. Market prices are ultimately the product of human decisions — decisions shaped by greed, fear, hope, uncertainty, and the herd instincts that have characterised crowd behaviour throughout recorded history. Because human psychology is consistent over time, the patterns it produces in markets tend to recur. The same chart formations appear in FTSE 100 stocks in 2024 that appeared in Dow Jones Industrial Average constituents in 1960, because the emotional dynamics driving them — buyers becoming overconfident, sellers capitulating, the gradual shift from one phase of a trend to another — are the same.

This is what gives historical price data its analytical value. Recognising a pattern that has resolved in a consistent way across hundreds of prior instances does not guarantee a particular outcome, but it does provide a probabilistic edge. Technical analysis is not about certainty; it is about identifying situations where the historical record suggests that the odds favour a particular outcome, and sizing and timing positions accordingly.

The How Is More Important Than the Why

The fourth assumption is perhaps the most philosophically distinctive. A technical analyst is generally uninterested in constructing narratives to explain why price is moving in a particular direction. If a stock is rising sharply on above-average volume, the technical analyst notes that it is rising and positions accordingly — they do not feel compelled to determine whether the driver is institutional accumulation, a leaked announcement, or a shift in sector sentiment. The behaviour of the price is the signal; the explanation is secondary.

This is not incuriosity — it is prioritisation. Narratives about why prices move are often constructed after the fact, and they can lead traders into the trap of holding positions that are clearly losing because the fundamental story still sounds convincing. Price action cuts through that noise. If a position is moving against you, the chart will show it before most narratives have updated to reflect it.

Reading the Record — Open, High, Low, and Close

Given that price data is the raw material of technical analysis, it is worth understanding precisely what that data consists of and why each component matters. On any given day — or hour, or five-minute interval, depending on the timeframe a trader is using — the market generates four distinct price points. Together, they are known by the shorthand OHLC: Open, High, Low, and Close.

Modern financial markets generate an enormous volume of individual transactions. On a busy day, a major FTSE 100 constituent might see tens of thousands of individual trades executed across different electronic platforms. Tracking every single transaction would be both impractical and analytically overwhelming. The OHLC summary condenses all of that activity into four meaningful reference points that capture the essential character of a trading session without the noise of every intermediate print.

The close deserves particular attention. It is the price at which portfolios are marked, at which daily performance is calculated, and at which most technical indicators are computed. When a moving average is applied to a price chart, it is almost universally the closing prices that are averaged. When an oscillator such as the Relative Strength Index is calculated, the closing prices form the input series. The close is the day’s final verdict — the price at which the market, having processed an entire session’s worth of information and emotion, decided to settle.

There is additional meaning in the relationship between the open and the close. If the close is higher than the open, the session is described as bullish — buyers were in control by the end of the day. If the close is lower than the open, the session is bearish. The distance between the two is a measure of conviction: a small difference suggests indecision or balance; a large difference suggests that one side of the market dominated decisively. This relationship sits at the heart of candlestick charting, where the open-to-close range forms the body of the candle and its colour communicates the direction at a glance.

The high and low, meanwhile, tell a different story: they describe the range of contest during the session. A day with a wide spread between high and low was a volatile, contested session. A day with a narrow spread was orderly and quiet. On a candlestick chart, the wicks extending above and below the body represent the high and low respectively, giving the trader a visual indication of intraday extremes and rejected price levels — information that cannot be captured by a simple closing-price line chart.

Timeframes and the Same Data at Different Scales

One of the most important features of OHLC data is that it is entirely timeframe-agnostic. The same four price points — open, high, low, close — can be defined for a one-minute interval, a fifteen-minute interval, an hourly interval, a daily session, a weekly period, or a monthly period. In each case, the open is simply the first price traded in that interval, the close is the last, and the high and low are the extremes reached during it.

This scalability is what allows technical analysis to serve traders with very different time horizons. A day trader looking at five-minute charts is using OHLC data at high resolution, with each bar representing just five minutes of activity. A position trader looking at weekly charts is using the same structure, but each bar now summarises an entire week’s trading. The analytical tools — indicators, trendlines, pattern recognition — operate identically in both cases. The principles remain the same regardless of the timeframe, which is one of the discipline’s most important characteristics.

Volume is often presented alongside OHLC data and is worth noting here, even though it will be treated in greater depth in later articles. Volume records the number of shares — or contracts, or units — traded during a given period. When price moves significantly on high volume, the move carries more conviction than an equivalent move on light volume. A price rise accompanied by expanding volume signals broad market participation; the same rise on thin volume may reflect little more than a temporary imbalance between buyers and sellers that could quickly reverse. Volume is the supporting evidence that gives price action its context.

Putting the Principles Together

The assumptions of technical analysis and the structure of OHLC data are not separate topics — they connect directly. It is because markets discount everything that the price record contains such rich information. It is because price moves in trends that historical OHLC data can be used to identify those trends and project their likely continuation. It is because history tends to repeat that pattern recognition on charts has predictive value. And it is because the how matters more than the why that technical analysts focus their attention on price behaviour — on what the open, high, low, and close are actually doing — rather than on the narratives that may or may not explain it.

Technical analysis cannot be reduced to a single mechanical system, and it should never be approached as a guarantee of outcomes. The discipline’s own founders were clear on this point: Dow Theory is not infallible, and no pattern resolves correctly one hundred percent of the time. What technical analysis provides is a structured, replicable framework for reading the accumulated behaviour of market participants, identifying conditions where the odds of a particular outcome are historically favourable, and acting with discipline on those probabilities.

The chapters that follow will build on these foundations step by step — moving from the basic structure of charts and timeframes through to the full toolkit of indicators, patterns, and strategies that make up the practice of technical analysis. Everything in that toolkit traces back to the four price points introduced here. Understanding what they record, and why they matter, is where the work begins.