Technical analysis - often called chartism - has shaped investing since before the war. Its reputation has faded, though. Is there still a useful place for it?
Is technical analysis dead? Why finance turned away from charts
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TikTok now teems with people explaining chart-based technical analysis - work that investment banks once assigned to specialists. Robert Edwards and John Magee's *Technical Analysis of Stock Trends*, first published in 1948, has reached its eleventh edition and remains in print. Some call it the discipline's Bible, but an aspiring graduate at an interview would probably be better off not mentioning that they had read it.
Certification figures point in much the same direction. About 2,500 people currently hold active charters from the Chartered Market Technician Association, which focuses on reading market charts. The CFA Institute sets standards for investment professionals worldwide and runs the Chartered Financial Analyst (CFA) programme.
The group's syllabus has become the industry standard in practice, with 200,000 charterholders. Technical analysis no longer appears as its own chapter - not because space was tight. The curriculum still runs to thousands of pages.
It was everywhere and nowhere at once - upright in one case, inverted in another. During the 1990s, researchers tried to judge chartists' shifting, inconsistent, sometimes contradictory behavior with rigid models. Blind men describing an elephant, except the elephant was made of trades.
People also disagreed about the time horizon. The shoal's position ten seconds later seemed easier to predict than its location a year from now, yet some argued the reverse: long-term trends, they said, were less random and stronger than short-term swings.
Forecasters usually protect themselves with vague language. Gold offered a clear example: between 2011 and early 2022, it formed a triple top while the monthly MACD showed negative divergence. On a chart, that combination pointed to an imminent sell-off, and reports warning of one spread widely. The predictions held up for six months, became useless after a year, and looked terrible beyond that.
Once the votes were counted and the data-mining distortions corrected, mainstream finance arrived at a cautious conclusion. Technical analysis can beat buy-and-hold over short periods and in narrow parts of the market where trading remains immature and inefficient, though the claim comes with plenty of conditions. A basic momentum strategy focused on niche small-cap stocks might produce worthwhile results. But calling the market's top from Elliott Waves drawn across a forty-year S&P 500 chart cannot be tested fairly against comparable forty-year periods from earlier history.
Enter the quants
The same computing power that let academics examine enormous datasets during the 1990s also set off a flashier boom: hedge funds entered their golden age. Long-Term Capital Management (LTCM) began trading with seed funding worth about £2.2 billion in today's money, years before its spectacular collapse filled several books.
Myron Scholes and Robert Merton gave the venture an irresistible elevator pitch. Both would soon win Nobel Prizes, and they were two of the three people who had, quite literally and figuratively, written the book on a problem long thought impossible: modeling the value of complicated financial derivatives with mathematics. Forget charts. The work relied on parabolic partial differential equations and elaborate arbitrage trades. During their first three years together, annualized returns reached roughly 35%.
Finance was never cleanly split between sophisticated econometric models and old-fashioned chart reading. LTCM and similar firms offered risky products, but access stayed limited to institutions and ultra-high-net-worth clients. The internet changed things for everyone else, making it far easier for ordinary people to enter financial markets. Large minimum balances and unaffordable commissions began to disappear.
Online brokerages brought market data - and dubious dotcom stocks - to ordinary investors. People could study charts themselves, judge trading ranges, and decide whether a breakout was worth pursuing. Financial-services firms suddenly had to prove what they added and why anyone should pay their fees. Then fate stepped in.
The revenge of the analysts
The chain began with Asia's 1997 financial crisis, where crony capitalism showed itself through extreme leverage, tangled cross-holdings, and banks holding almost no capital. The damage helped drive Russia's sovereign-debt crisis the following year, which then brought down LTCM.
Then came the dotcom crash in 2000 and a run of catastrophic accounting scandals: Enron in 2001, WorldCom in 2002, and Parmalat in 2003. Each collapse shattered a widely held illusion - faith in the Asian Tigers, the promise of automatic prosperity after communism, the supposedly visionary CEO, or the belief that putting anything online would produce vast riches.
That brief, disaster-filled stretch made one point clear: financial analysis and due diligence mattered, and neither chart patterns nor catchy jingles could replace them. Quality-focused fund managers pointed to portfolios built around resilient, proven business models. Value investors, meanwhile, took pride in refusing to buy at any price.
A grim parallel emerged in the academic debate over data trawling: put the entire financial system through repeated crises, and some survivors are bound to remain. Nassim Nicholas Taleb stressed this point in his 2001 bestseller, Fooled by Randomness; surviving those upheavals does not necessarily make them geniuses.
A strange new afterlife for technical analysis
Much of technical analysis now survives under different names. Quantitative finance and factor investing, for instance, still depend on momentum signals that can be tested. Chart reading is another matter. Its more subjective habits never received a respectable rebrand; they linger in finance much as Reddit does in cutting-edge AI - full of nonsense and unsuitable for a boardroom quotation, yet still containing knowledge too useful to throw away. If these charting tools were truly redundant, expensive Bloomberg terminals - the systems that power the industry - would probably have dropped them years ago.
Key technical analysis terms
Chart basics
Volume bars
Vertical bars record the number of shares or contracts traded during a set period. Chartists read them to judge how strongly the market supports a price move or a particular trading level.
Trading Range
Over time, a financial instrument may trade within a fairly steady range. Buyers tend to step in near the lower boundary, known as support, while sellers often emerge near the upper boundary, called resistance. A price move above resistance is a breakout; a move below support is a breakdown.
Mathematical indicators
Moving Average
The average price calculated across a set number of periods, a moving average filters out short-term swings so the underlying trend stands out. Traders often watch for one moving average to cross another with a different period length, treating that movement as a possible signal.
Bollinger Bands
A chart overlays a moving average with upper and lower bands calculated from recent prices. Greater volatility pushes the bands apart; calmer trading draws them closer together. This makes unusually high or low prices easier to spot relative to current market conditions.
Momentum
Prices often continue moving in the direction they have already taken. Momentum indicators track how quickly prices change and how strong that movement is, helping distinguish a trend that still holds from one that is starting to fade.
MACD Indicator
MACD stands for Moving Average Convergence Divergence. It usually appears in its own panel beneath the price chart, aligned with it, and contains two moving lines. One shows the gap between the price's short- and long-term moving averages; the other averages the MACD line to reduce its swings. When the two lines cross, traders interpret that movement as a possible shift toward stronger or weaker momentum.
Chart patterns and theories
Triple Top
When the price climbs to roughly the same high three times and fails to move above it, traders traditionally read the pattern as a possible bearish reversal. The signal becomes more convincing if the price later falls below recent support.
Divergence
Here, price and a technical indicator head in opposite directions. Bearish divergence appears when price reaches higher highs while a momentum indicator records lower highs, warning that the upward trend may be losing strength.
Head and Shoulders
The pattern has three peaks in a row, with the middle one rising higher than the peaks on either side. Once prices drop below the line connecting the two troughs between them - the neckline - traders traditionally read that move as bearish. Flip the formation vertically and it becomes an inverse head and shoulders pattern; a move above its neckline is considered bullish.
Elliott Waves
A theory holds that investor psychology pushes market prices through recurring patterns. In its classic form, prices move through five waves in the prevailing trend, followed by three waves of correction. Yet recognizing and counting those waves remains highly subjective.
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