Technical Analysis: Price Action, Patterns & Indicators

Overview

Technical analysis is the practice of studying historical price and volume data to forecast future market behavior. Its practitioners -- known as technicians or chartists -- operate from a core premise that distinguishes their discipline from fundamental analysis: all relevant information is already reflected in the price. If a company's earnings are about to collapse, informed participants are already selling, and that selling pressure is visible in the chart before the earnings report is published. If a sector is about to boom, smart money is already accumulating, and accumulation leaves fingerprints in volume and price action. The technician does not need to read balance sheets or estimate discount rates. The chart, properly interpreted, tells the story.

The intellectual history of technical analysis stretches back further than most investors realize. Charles Dow, co-founder of the Wall Street Journal and creator of the Dow Jones Industrial Average, articulated the foundational principles in a series of editorials between 1900 and 1902. His work was formalized into Dow Theory by William Hamilton and Robert Rhea in the decades that followed. In 1948, Robert Edwards and John Magee published Technical Analysis of Stock Trends, the first comprehensive taxonomy of chart patterns -- a book that remains in print and in active use today. In 1991, Steve Nison introduced Western investors to Japanese candlestick charting in Japanese Candlestick Charting Techniques, revealing a parallel tradition that Japanese rice traders had been developing since the 18th century. John Murphy's Technical Analysis of the Financial Markets (1999) became the standard modern textbook, synthesizing decades of pattern research, indicator development, and market psychology into a single, rigorous reference.

The honest framing is this: technical analysis is neither the crystal ball its enthusiasts sometimes claim nor the astrology its critics dismiss it as. It is a toolkit -- a set of frameworks for interpreting market behavior, managing risk, and timing decisions. The best practitioners use it alongside fundamental analysis, not as a replacement. They understand that patterns are probabilistic, not deterministic, and that the value of technical analysis lies not in prediction but in preparation: identifying the levels, conditions, and scenarios that demand attention, and having a plan for each.

Dow Theory: The Foundation

Charles Dow never intended to create a system for trading stocks. His editorials were observations about how markets behave, distilled from years of watching price movements on the exchanges. Yet the principles that bear his name became the bedrock of all technical analysis. Dow Theory rests on six tenets that, despite being over a century old, remain the conceptual foundation of every chart pattern, indicator, and trading system in use today.

First, the market discounts everything. The price of a security reflects all available information -- earnings, interest rates, political events, natural disasters, and investor sentiment. This is not a claim that markets are perfectly efficient, but that the aggregate effect of all known factors is embedded in the price at any given moment. The technician's job is to read the price, not to second-guess it.

Second, the market moves in three types of trends. The primary trend is the major direction of the market, lasting from months to years -- the bull and bear markets that define eras. The secondary trend is the corrective movement against the primary trend, typically lasting weeks to months -- the rallies within bear markets and the pullbacks within bull markets. The minor trend is the day-to-day fluctuation, largely noise, and of interest mainly to short-term traders.

Third, primary trends have three phases. In a bull market: the accumulation phase, where informed investors buy from discouraged sellers; the public participation phase, where improving conditions attract broader buying; and the distribution phase, where the informed money begins to sell to the enthusiastic late arrivals. Bear markets mirror this in reverse: distribution, public participation in the decline, and the panic phase.

Fourth, indices must confirm each other. Dow argued that a genuine trend in the industrial sector should be confirmed by a corresponding trend in the transportation sector -- because goods must be shipped before profits can be earned. The modern application extends this to cross-market confirmation: a breakout in one sector or index is more credible when confirmed by related markets.

Fifth, volume must confirm the trend. In a healthy uptrend, volume should expand as prices rise and contract on pullbacks. If prices are making new highs on declining volume, the move lacks conviction and is likely to fail. Volume is the fuel that drives price moves -- without it, even the most promising pattern is suspect.

Sixth, trends persist until definitively reversed. A trend in motion is more likely to continue than to reverse. This is perhaps the most practical of Dow's tenets: it argues against premature counter-trend trading and in favor of riding established trends until there is clear evidence of reversal. The burden of proof falls on the reversal, not on the continuation.

Chart Patterns: Edwards and Magee

Robert Edwards and John Magee catalogued the visual signatures that prices leave on charts when supply and demand reach inflection points. These patterns are not mystical -- they are the geometric expression of crowd psychology. When thousands of participants collectively panic, capitulate, gain confidence, or become euphoric, their aggregate behavior traces recognizable shapes on the price chart. Pattern recognition is probabilistic, not deterministic: a head and shoulders pattern increases the probability of a decline, but it does not guarantee one.

Head and shoulders is the most reliable reversal pattern in classical charting. It forms at the end of an uptrend: a peak (the left shoulder), followed by a higher peak (the head), followed by a lower peak (the right shoulder), with a support line connecting the two troughs between them (the neckline). The pattern completes when price breaks below the neckline on increasing volume. The measured target is the distance from the head to the neckline, projected downward from the breakout point. The inverse head and shoulders is the mirror image, forming at the end of downtrends and signaling bullish reversals.

Double tops and double bottoms signal failed attempts to break through a price level. A double top forms when price reaches a resistance level twice and fails both times, creating an "M" shape. A double bottom forms at support, creating a "W" shape. Volume typically declines on the second test, indicating weakening momentum in the prevailing trend. The breakout through the middle trough (for tops) or middle peak (for bottoms) confirms the pattern.

Triangles are consolidation patterns where the range of price narrows over time, building energy for a breakout. Ascending triangles have a flat upper boundary and a rising lower boundary -- typically bullish, as buyers are willing to pay progressively higher prices while sellers hold firm at a resistance level. Descending triangles have a flat lower boundary and a declining upper boundary -- typically bearish. Symmetrical triangles compress equally from both sides and can break in either direction; the breakout direction determines the signal. In all cases, the breakout should occur on expanding volume, and the measured target equals the height of the triangle's widest point.

Flags and pennants are brief consolidation patterns within strong trends. A flag is a small parallelogram that slopes against the prevailing trend. A pennant is a small symmetrical triangle. Both represent a pause before the trend resumes, and both should be accompanied by a sharp decline in volume during the consolidation followed by a volume surge on the breakout. They are among the most reliable continuation patterns.

Cup and handle was popularized by William O'Neil and forms over weeks to months: a rounded bottom (the cup) followed by a short consolidation drift lower (the handle), then a breakout above the cup's rim. Volume should dry up during the handle formation and expand sharply on the breakout. This pattern is a favorite among growth stock investors because it often marks institutional accumulation.

Japanese Candlesticks

Japanese rice traders in the 1700s developed a charting method that captures the psychology of each trading session in a single visual element. Steve Nison's 1991 book introduced these techniques to Western markets, and they have since become the default charting style worldwide. Each candlestick records four data points -- open, high, low, and close -- with the body representing the range between open and close, and the wicks (shadows) representing the extremes.

Doji candlesticks form when the open and close are virtually identical, producing a thin or nonexistent body. The doji signals indecision: neither buyers nor sellers could gain control during the session. A doji after a strong trend is a warning that the trend may be exhausting itself. The longer the shadows, the more intense the battle between buyers and sellers was -- even though neither side won.

Hammer and hanging man share the same shape: a small body at the top of the range with a long lower shadow and little or no upper shadow. The difference is context. A hammer appears at the bottom of a downtrend and signals potential reversal -- sellers drove prices sharply lower during the session but buyers overwhelmed them by the close. A hanging man appears at the top of an uptrend and signals that selling pressure is emerging beneath the surface.

Engulfing patterns occur when a candlestick's body completely engulfs the prior session's body. A bullish engulfing pattern forms at the bottom of a downtrend: a small bearish candle followed by a large bullish candle that opens below the prior close and closes above the prior open. A bearish engulfing is the reverse, appearing at tops. Engulfing patterns are among the most reliable single-session reversal signals, especially when accompanied by high volume.

Morning star and evening star are three-candle patterns. The morning star forms at bottoms: a long bearish candle, a small-bodied candle (the star) that gaps lower, and a long bullish candle that closes well into the first candle's body. The evening star is the bearish mirror at tops. The small middle candle represents the moment of indecision before the reversal takes hold.

Three white soldiers are three consecutive long-bodied bullish candles, each opening within the prior candle's body and closing at or near session highs -- a powerful bullish continuation signal. Three black crows are the bearish equivalent: three consecutive long-bodied bearish candles, each opening within the prior candle's body and closing at or near session lows. Both patterns represent sustained, conviction-driven momentum.

Moving Averages

Moving averages smooth raw price data to reveal the underlying trend by averaging closing prices over a specified number of periods. They are the most widely used technical indicators because they are simple, intuitive, and effective at filtering noise from signal.

The simple moving average (SMA) gives equal weight to every data point in the window. The 50-day SMA averages the last 50 closing prices; each day, the oldest price drops off and the newest is added. The exponential moving average (EMA) applies more weight to recent prices, making it more responsive to current conditions but also more sensitive to short-term noise.

Two moving averages have become institutional benchmarks: the 50-day and the 200-day. Portfolio managers, algorithmic trading systems, and risk management frameworks around the world use these levels as reference points. When a stock trades above its 200-day moving average, it is generally considered to be in a long-term uptrend. When it trades below, the long-term trend is down. These levels become self-fulfilling because so many participants watch them.

The golden cross occurs when the 50-day moving average crosses above the 200-day -- a bullish signal indicating that the intermediate trend is now outpacing the long-term trend. The death cross is the reverse: the 50-day crossing below the 200-day, signaling that momentum has shifted to the downside. These signals are lagging by nature -- the move has already begun by the time the cross occurs -- but they are effective at confirming major trend changes and filtering out false starts.

Moving averages also serve as dynamic support and resistance. In uptrends, prices often pull back to the 50-day or 200-day moving average and bounce. In downtrends, rallies often stall at these levels. The key tradeoff is responsiveness versus reliability: shorter-period moving averages (10-day, 20-day) react quickly to price changes but produce more false signals, while longer-period averages (100-day, 200-day) are smoother and more reliable but lag significantly behind turning points.

Momentum Oscillators

Oscillators measure the speed and magnitude of price changes, generating signals when momentum diverges from price or reaches extreme levels. Unlike trend-following indicators, oscillators are designed to identify overbought and oversold conditions -- moments when price has moved too far, too fast, and is due for a reversal or consolidation.

RSI (Relative Strength Index)

Developed by J. Welles Wilder Jr. in his 1978 book New Concepts in Technical Trading Systems, the RSI measures the ratio of average gains to average losses over a specified period (default 14 periods) and expresses the result on a scale from 0 to 100. The formula: RSI = 100 - (100 / (1 + RS)), where RS = Average Gain / Average Loss over the lookback period. Readings above 70 are considered overbought -- the security has been rising aggressively and may be due for a pullback. Readings below 30 are considered oversold -- selling has been excessive and a bounce may be imminent.

However, the most powerful RSI signal is the divergence. When price makes a new high but RSI fails to make a corresponding new high, it signals that the momentum behind the uptrend is weakening -- buyers are running out of steam even as the price grinds higher. This bearish divergence often precedes significant declines. Conversely, when price makes a new low but RSI makes a higher low, the selling pressure is diminishing, and a bullish reversal may be forming. Divergences are not timing tools -- they identify conditions, not exact turning points -- but they are among the most valuable signals in the technician's arsenal.

MACD (Moving Average Convergence Divergence)

Created by Gerald Appel in the late 1970s, the MACD tracks the relationship between two exponential moving averages -- typically the 12-period and 26-period EMAs. The MACD line is the difference between these two EMAs: MACD = 12-period EMA - 26-period EMA. A nine-period EMA of the MACD line serves as the signal line. The histogram plots the difference between the MACD line and the signal line, providing a visual measure of momentum.

The basic signal is the signal line crossover: when the MACD crosses above the signal line, it is bullish; when it crosses below, bearish. But as with RSI, divergences are more powerful. When price makes a new high but the MACD does not, momentum is fading. The MACD histogram is particularly useful for spotting these divergences early, as histogram peaks and troughs often lead MACD line crossovers.

Stochastic Oscillator

George Lane developed the stochastic oscillator to measure where the current close falls relative to the high-low range over a specified period (typically 14 periods). The logic is elegant: in uptrends, prices tend to close near the top of their range, and in downtrends, near the bottom. The %K line captures this: %K = ((Close - Lowest Low) / (Highest High - Lowest Low)) x 100. The %D line is a 3-period moving average of %K, serving as a signal line. Readings above 80 are considered overbought; below 20, oversold. Crossovers between %K and %D generate buy and sell signals, and divergences between the stochastic and price carry the same interpretive weight as RSI and MACD divergences.

Chaikin Money Flow (CMF)

Marc Chaikin developed the Chaikin Money Flow indicator to solve a fundamental problem: traditional price-only indicators tell you what the market is doing, but they do not tell you who is doing it. CMF integrates price action and volume into a single measure of buying and selling pressure, revealing whether the money flowing into a security is driven by conviction (accumulation) or exiting under duress (distribution).

The calculation begins with the Money Flow Multiplier, which measures where the close falls within the session's high-low range: ((Close - Low) - (High - Close)) / (High - Low). This value ranges from -1 to +1. A close at the session high produces a multiplier of +1; a close at the low produces -1; a close at the midpoint produces 0. The insight is that where the close falls within the range reveals the balance of power between buyers and sellers. A stock that trades to a wide range but closes near the high was dominated by buyers. One that closes near the low was dominated by sellers.

The multiplier is then applied to volume to produce Money Flow Volume: Money Flow Volume = Money Flow Multiplier x Volume. This captures not just the direction of the session's bias but its magnitude -- high-volume sessions carry more weight than low-volume ones.

CMF itself is calculated over a lookback period, typically 20 or 21 trading days: CMF = Sum of Money Flow Volume over N periods / Sum of Volume over N periods. The result oscillates between -1 and +1, though extreme readings are rare.

Interpretation: CMF above zero indicates net accumulation -- buying pressure has dominated over the lookback period. CMF below zero indicates net distribution -- selling pressure has dominated. The further from zero, the stronger the signal. Persistent positive CMF readings confirm the health of an uptrend; persistent negative readings confirm a downtrend.

Confirming breakouts is one of CMF's most practical applications. A price breakout above resistance accompanied by positive and rising CMF is a high-conviction signal -- it means the breakout is backed by genuine buying pressure, not just a thin-volume gap up that is likely to fail. Conversely, a breakout on negative or declining CMF should be treated with suspicion.

Divergences are equally valuable. When price is making new highs but CMF is declining, it signals that distribution is occurring beneath the surface -- informed participants are selling into the rally. This bearish divergence often precedes meaningful declines. When price is making new lows but CMF is rising, accumulation is underway, and a reversal may be forming.

Why does CMF matter? Because price action in isolation can be misleading. A stock can rise on low volume and thin conviction, or it can be quietly accumulated for weeks before a move becomes visible. CMF strips away this ambiguity by forcing volume into the analysis. Compared to On-Balance Volume (OBV) -- the simplest volume indicator, which adds volume on up days and subtracts it on down days -- CMF is more nuanced because it accounts for where the close falls within the range. OBV treats a day that closes one cent higher on massive volume the same as a day that closes at the session high. CMF captures the difference, producing a more refined picture of institutional money flow.

Volume Analysis

Volume is the lifeblood of price movement. Every candle on a chart tells you what happened to price; volume tells you how much conviction was behind it. The core principles are simple but essential.

Volume confirms price moves. A breakout above resistance on heavy volume signals genuine conviction and increases the probability that the move will sustain. A breakout on thin volume is suspect -- it may be a false breakout driven by a small number of participants that will quickly reverse.

Volume precedes price. Accumulation -- institutional buying -- often begins before any visible change in price. Volume increases while the stock trades sideways, creating a telltale divergence. Distribution works the same way: insiders and institutions sell while the price holds steady, producing elevated volume without corresponding price appreciation. By the time the price breaks down, the selling is largely done.

On-Balance Volume (OBV), developed by Joe Granville, is the simplest volume indicator: it adds the entire day's volume when the close is up and subtracts it when the close is down, keeping a running total. A rising OBV line confirms an uptrend; a divergence between rising price and flat or falling OBV warns that the trend lacks volume support. OBV is a blunt instrument -- it does not account for where the close falls in the range -- but its simplicity makes it a useful first screen.

Support, Resistance, and Fibonacci

Support is a price level where buying interest is strong enough to halt a decline. Resistance is a level where selling pressure is strong enough to cap an advance. These levels represent price memory -- they mark the points where supply and demand previously reached equilibrium, and market participants remember them. Traders who bought at a support level and watched the stock rise have a positive association with that price and will buy again if it returns. Traders who missed a breakout above resistance will buy if price retests that level from above, turning former resistance into support.

This polarity principle -- broken support becomes resistance, and broken resistance becomes support -- is one of the most reliable observations in technical analysis. A stock that breaks below a support level at $50 will often rally back to $50 and fail, as former holders who are underwater at that price sell to break even.

Fibonacci retracements apply the ratios derived from the Fibonacci sequence -- 23.6%, 38.2%, 50%, 61.8%, and 78.6% -- to the distance of a prior price move, identifying potential support and resistance levels within a correction. The mathematical origin is the Fibonacci sequence itself, where each number is the sum of the two preceding numbers, and the ratio of successive terms converges on 1.618 (the golden ratio). The 61.8% retracement is the inverse of 1.618, and the other levels are derived from similar mathematical relationships.

Do Fibonacci levels "work"? The honest answer is partly self-fulfilling prophecy and partly the natural tendency of corrections to retrace a portion of the prior move before resuming. Because millions of traders place orders at Fibonacci levels, those levels attract buying and selling, which makes them effective -- a feedback loop that is both real and fragile. The 38.2% and 61.8% levels tend to see the most activity. A correction that holds at 38.2% suggests a strong trend; one that falls to 61.8% suggests weakening momentum but remains within the normal range of a healthy pullback.

Bollinger Bands

John Bollinger introduced his eponymous bands in the 1980s as a volatility framework built on statistical principles. The construction is straightforward: a 20-period simple moving average as the middle band, with the upper band at 2 standard deviations above and the lower band at 2 standard deviations below. Because standard deviation expands and contracts with price volatility, the bands automatically widen in volatile markets and narrow in quiet ones.

The squeeze is the most anticipated Bollinger Band signal. When the bands contract to their narrowest width in months, it indicates that volatility has compressed to an extreme -- and low volatility is the precursor to high volatility. The squeeze does not predict direction, only that a significant move is coming. Traders watch for the breakout from the squeeze and trade in its direction.

Walking the bands occurs during strong trends: price hugs the upper band in uptrends or the lower band in downtrends, repeatedly touching or exceeding the band without reversing to the mean. This signals sustained momentum and is not an overbought or oversold condition -- a common misinterpretation. A stock "walking" the upper band is exhibiting strength, not exhaustion.

Mean reversion plays use the bands as a framework for buying oversold dips and selling overbought extensions. When price touches the lower band in the context of a broader uptrend, it often marks a short-term low. When it touches the upper band in a range-bound market, it often marks a short-term high. The key distinction is context: mean reversion works in range-bound markets but fails in trending ones, where walking the band is the norm.

Do Technicals Work? The Honest Assessment

The Efficient Market Hypothesis, in its strong and semi-strong forms, argues that technical analysis should not work. If prices already reflect all publicly available information, then historical patterns cannot predict future movements -- any exploitable pattern would be rapidly arbitraged away. Eugene Fama and the Chicago school have maintained this position for decades, and the academic evidence for simple pattern-based trading systems generating consistent risk-adjusted alpha is, at best, mixed.

The behavioral finance defense, articulated by researchers like Daniel Kahneman, Amos Tversky, Richard Thaler, and Robert Shiller, argues that market participants are not the rational agents that EMH assumes. They are subject to persistent cognitive biases -- anchoring, herding, overconfidence, loss aversion, recency bias -- that create predictable patterns in price behavior. Fear and greed are not random; they are patterned, and those patterns repeat because human psychology does not change. Technical analysis, in this view, is a framework for reading the behavioral fingerprints of the crowd.

The academic evidence is more nuanced than either side acknowledges. Simple pattern recognition -- buying when a golden cross occurs, selling on a death cross -- produces marginal results that often disappear after transaction costs. But two phenomena have stronger empirical support: momentum (securities that have risen tend to continue rising over 3-12 month horizons) and mean reversion (securities that have risen dramatically over 3-5 years tend to underperform subsequently). These are not chart patterns per se, but they are the statistical foundation upon which many technical strategies rest.

The practitioner's answer is pragmatic: technicals work best not as a standalone system but as a supplement to fundamental analysis. A fundamental analyst who has identified an undervalued stock can use technical analysis to time the entry, set stop-loss levels, and manage risk. A portfolio manager can use moving averages and trend indicators to avoid being fully invested during bear markets. Technicals also work better in liquid, widely followed markets -- where many participants are watching the same levels -- and worse in thin, illiquid markets where a single large order can overwhelm any pattern.

Why This Matters

Technical analysis provides a structured language for interpreting market behavior. Whether or not you believe that chart patterns predict the future, they describe the present -- and in markets, understanding the present state of supply, demand, momentum, and sentiment is enormously valuable. The most effective investors use technicals not to replace fundamental analysis but to enhance it: to identify when a fundamentally sound thesis is also supported by favorable price action and institutional accumulation, and to step aside when it is not. The discipline of defining support levels, resistance levels, and invalidation points transforms vague investment ideas into actionable plans with defined risk. And that, more than any individual pattern or indicator, is the lasting contribution of technical analysis to the practice of investing.

Key Takeaways

Technical analysis operates from the premise that price reflects all available information, and that historical price and volume data contain actionable patterns of crowd psychology.
Dow Theory provides the foundational framework: trends persist until reversed, volume confirms price, and primary trends move through identifiable phases of accumulation, participation, and distribution.
Chart patterns (head and shoulders, double tops/bottoms, triangles, flags) are probabilistic signals, not guarantees -- always confirm with volume and wait for the breakout before acting.
Japanese candlesticks capture the psychology of each trading session in a single visual; doji, engulfing patterns, and star formations are among the most reliable reversal signals.
Moving averages (50-day, 200-day) serve as institutional benchmarks and dynamic support/resistance -- golden crosses and death crosses confirm major trend changes, but they are lagging indicators.
RSI, MACD, and stochastic divergences are among the most powerful signals in technical analysis, identifying moments when momentum is failing to confirm price -- often preceding significant reversals.
Chaikin Money Flow integrates price and volume into a single measure of buying and selling pressure, providing more nuanced insight into accumulation and distribution than price-only indicators.
Technicals work best as a supplement to fundamental analysis, for timing entries and exits, and for defining risk -- not as a standalone prediction system.