Technical Analysis

Technical analysis, often shortened to TA and sometimes called trend analysis, is the study of market data, chiefly past prices and trading volume, to identify trends and patterns that may help predict future price movements. Technical analysts, or chartists, look at charts rather than company accounts or economic reports, on the view that everything known about an asset is already reflected in its price. The approach is used by traders in shares, currencies, commodities, bonds and cryptocurrencies, over time frames from minutes to years.

Technical analysis is usually contrasted with fundamental analysis, which tries to estimate an asset's intrinsic value from earnings, cash flows, economic conditions or, in crypto, network usage and token supply. Many market participants combine the two, using fundamentals to choose what to buy and technical analysis to decide when. Its usefulness is disputed: many academics doubt that past prices can reliably predict future ones, while it remains popular among practising traders.

Think of a weather forecaster who has no instruments for measuring air pressure, only a long record of past weather. By noticing that certain sequences, such as a run of grey mornings after a warm spell, have often come before rain, the forecaster makes educated guesses about tomorrow. The guesses are wrong quite often, but they may be right often enough to be useful.

Technical analysts treat price charts in a similar way. They do not ask what a company or coin is truly worth. Instead they ask how people have been buying and selling it, whether prices are climbing or falling, where they have tended to stop, and whether today's pattern resembles ones that led to big moves in the past. The chart is seen as a record of crowd behaviour, and crowds are thought to repeat themselves.

Price charting has deep roots. In eighteenth-century Japan, rice traders such as Munehisa Homma are credited with early forms of the candlestick chart, which shows each period's opening, high, low and closing prices. In the United States, Charles Dow, co-founder of Dow Jones and creator of the Dow Jones Industrial Average, wrote editorials around 1900 that later became known as Dow theory, describing markets as moving in primary trends, secondary reactions and minor fluctuations. Through the twentieth century, analysts developed pattern catalogues and mathematical indicators, and personal computers in the 1980s and online charting platforms such as TradingView later made the tools available to anyone.

• Price reflects information. Technical analysts assume that news, expectations and sentiment are already reflected in the price, so the price itself is what matters.
• Prices move in trends. Once a trend has started, it is assumed more likely to continue than to reverse, which is why "the trend is your friend" is a common saying.
• History tends to repeat. Because human emotions such as fear and greed are constant, similar chart patterns are thought to lead to similar outcomes.

Analysts use several kinds of tools, often together:

• Charts. Line charts, bar charts and candlestick charts display prices over chosen periods.
• Support and resistance. A support level is a zone where falling prices have tended to stop, and a resistance level one where rises have tended to stall.
• Patterns. Shapes such as head and shoulders, double tops, triangles and flags are read as signs of continuation or reversal.
• Indicators. Technical indicators are formulas applied to price or volume, including the moving average, the relative strength index, the MACD, Bollinger Bands and the stochastic oscillator.
• Volume. Rising trading volume is often taken to confirm a move, while weak volume suggests it may not last.

Technical analysis is especially prominent in cryptocurrency markets, where many assets have no earnings or cash flows to analyse and trading continues around the clock. Crypto traders apply the same chart tools as in other markets and add some of their own, such as on-chain metrics that track wallet flows, and chart-based slang like the golden cross. Because crypto markets are relatively young, often thinly traded and dominated by retail investors, patterns may be distorted by large holders, and widely followed levels can be deliberately targeted to trigger clusters of orders.

The efficient market hypothesis holds that prices already reflect available information, so patterns in past prices should not offer lasting profits after costs. Studies have produced mixed results: some find that simple trend-following rules worked in certain markets and periods, while others find that apparent successes disappear once trading costs and data mining are accounted for. Critics also note that chart reading is subjective, that patterns are easier to see in hindsight, and that predictions can become self-fulfilling for a while simply because many traders act on them. Supporters reply that technical analysis is mainly a tool for managing risk and timing, rather than a forecasting machine, and many professional funds use systematic trend-following strategies tested through backtesting. Like any method of analysing markets, it offers no guarantee of profit.