Technical analysis is the study of price action and trading volume to forecast future market movements. It is one of the two main schools of market analysis – the other being fundamental analysis – and one of the most divisive topics in finance. Academic studies often find limited statistical evidence for many technical indicators. Yet professional traders and quantitative funds rely on technical concepts daily, and entire algorithmic trading strategies are built on technical signals.
This page covers what technical analysis actually is, the major concepts and tools, where it has predictive value, and where it does not – written by a finance professional rather than by promoters who profit from teaching it.
Technical analysis treats market price itself as the primary data source. The underlying assumption is that all known information – earnings, economic data, geopolitics, sentiment – is already reflected in the price. Rather than trying to predict price by analysing the underlying business or economy, technical analysts study price patterns and volume to identify the supply and demand dynamics driving the market.
This is fundamentally different from fundamental analysis, which evaluates intrinsic value by examining financial statements, business models, competitive positioning and macroeconomic conditions. Fundamental analysis asks “what is this asset worth?” Technical analysis asks “how is the market behaving, and what does that suggest about near-term price direction?”
Neither approach is universally correct. They answer different questions and operate at different timescales. A pure fundamental analyst may correctly identify an undervalued stock, but the market may take years to recognise it. A pure technical analyst may correctly identify a short-term price pattern, but miss that the company is structurally declining. Most professional approaches combine both.
The three core assumptions of technical analysis:
Price discounts everything. All information that could affect price is already reflected in the current price. Studying price action therefore captures the combined effect of all market participants’ analyses and decisions.
Price moves in trends. Markets tend to continue in direction once a trend is established. Technical analysis is largely about identifying trends early and exiting before reversals.
History tends to repeat. Market participants respond to similar conditions in similar ways. Patterns that occurred in the past sometimes recur because the underlying human behaviour driving them recurs.
These assumptions are not laws. They are working hypotheses that hold in some market conditions and break down in others.
Support is a price level where buying interest historically emerged strongly enough to halt declines. Resistance is a price level where selling pressure halted advances. These levels often arise from prior price action – a previous high becomes resistance, a previous low becomes support.
The economic logic: at a price where significant trading volume occurred previously, many investors have either established positions or strong views. When price returns to that level, those investors react in ways that influence current price. Support and resistance levels are not magic – they are aggregations of historical decision points.
Support and resistance break down in two situations: when fundamental conditions change materially (a previously strong company facing bankruptcy will not hold its prior support), and when high-volume breakouts occur that establish new trading ranges.
A trend is a sustained directional bias in price. Uptrends consist of higher highs and higher lows. Downtrends consist of lower highs and lower lows. Sideways or ranging markets move within defined boundaries without sustained directional bias.
Trend identification is the foundation of most technical strategies. A trader who correctly identifies a sustained uptrend and exits before the reversal captures a significant portion of the move, regardless of which specific entry and exit signals are used.
The challenge is that trends are only definitively identified in hindsight. Real-time trend identification involves probabilistic judgement about when noise has become signal.
Volume – the number of shares or contracts traded – provides context for price action. The same price movement carries different significance at high versus low volume.
A price increase on high volume suggests broad participation and conviction. The same price increase on low volume may reflect technical buying without underlying demand. Volume divergences (price rising while volume falls, for example) often precede trend reversals because they signal weakening participation in the prevailing direction.
Momentum measures the rate of price change. Strong momentum indicates conviction in the prevailing direction. Weakening momentum, even before price reverses, often signals trend exhaustion. Many technical indicators are momentum measures in different forms.
Hundreds of technical indicators exist. Most are variations or combinations of a small number of underlying concepts. The most widely used:
A moving average smooths price data by calculating the average price over a defined lookback period. The 50-day and 200-day simple moving averages are the most widely cited.
Moving averages serve two purposes. First, they identify trend direction – when price is above the moving average and the moving average is rising, the trend is up. Second, they provide dynamic support and resistance levels – traders watch how price behaves at major moving averages.
The “golden cross” (50-day moving average crossing above 200-day) and “death cross” (the reverse) are widely watched signals, though their predictive value in isolation is limited.
RSI measures the magnitude of recent price changes to identify overbought or oversold conditions. The index ranges from 0 to 100, with readings above 70 typically considered overbought and below 30 oversold.
RSI works best in ranging markets where it identifies reversals at the boundaries of the range. In trending markets, RSI can remain overbought (in uptrends) or oversold (in downtrends) for extended periods without reversal, which is why pure RSI strategies have limited effectiveness.
MACD tracks the relationship between two exponential moving averages. Signals come from MACD line crossing above or below its signal line, MACD crossing the zero line, and divergences between MACD and price.
MACD is essentially a trend-following indicator. It works well in trending markets and generates many false signals in ranging markets.
Bollinger Bands plot two standard deviations above and below a moving average. When price approaches the upper band, it is statistically high relative to recent history. When price approaches the lower band, it is statistically low.
The bands also indicate volatility – they expand during volatile periods and contract during quiet periods. Band contraction often precedes significant directional moves (the “Bollinger squeeze”).
Chart patterns are recurring shapes formed by price action. The most reliable patterns combine geometric structure with volume confirmation.
Head and Shoulders – three peaks with the middle peak highest, suggesting a topping pattern. The reverse (inverse head and shoulders) suggests a bottom.
Double Top / Double Bottom – two peaks or troughs at similar levels, suggesting failed continuation and likely reversal.
Triple Top / Triple Bottom – similar to double tops or bottoms but with three tests of the level, considered more significant.
[H3] Continuation Patterns
Triangles – ascending, descending or symmetrical narrowing price ranges. Often resolve in the direction of the prevailing trend.
Flags and Pennants – brief consolidation patterns within strong trends. The trend typically resumes after the consolidation completes.
Cup and Handle – a rounded bottom followed by a short pullback, often considered a bullish continuation pattern in uptrends.
Chart patterns work when they reflect underlying changes in supply and demand. A head and shoulders top represents buyers running out of conviction – each attempt to push higher meets stronger resistance. The pattern’s reliability depends on volume confirmation: the right shoulder typically forms on lower volume than the left, signalling reduced conviction.
Patterns without volume confirmation are weaker signals. Patterns identified before they complete (looking at a forming head and shoulders rather than a confirmed one) have lower success rates because partial patterns frequently abort.
The honest professional view is that technical analysis has predictive value in specific situations and minimal value in others.
Short-term price dynamics in liquid markets. In liquid markets like major equity indices, currency pairs and large cryptocurrencies, technical patterns often produce statistically significant edge in short timeframes. The reason is partly self-fulfilling – many traders watch the same patterns, creating actual buying or selling pressure when patterns trigger.
Risk management. Technical analysis provides clear, quantifiable rules for entry, exit and position sizing. “Sell if price closes below the 200-day moving average” is a precise rule. Technical levels provide structure that fundamental analysis cannot, which makes them useful for disciplined risk management regardless of any predictive value.
Market timing within fundamental positions. A fundamental investor who has identified an undervalued stock can use technical analysis to time entries and exits within their investment thesis, capturing better prices than mechanical buy-and-hold.
Long-term fundamental shifts. Technical analysis cannot identify structural business changes, regulatory shifts, or secular economic trends. A stock in a dying industry can show beautiful technical setups while heading to zero.
Black swan events. Technical patterns are based on historical behaviour. They have no predictive value for events outside historical patterns – pandemics, sudden regulatory changes, geopolitical crises, structural market shifts.
Illiquid markets. Technical patterns require sufficient volume to be meaningful. In thinly traded markets, price patterns reflect noise more than signal.
Single-stock analysis without fundamental context. Pure technical analysis of an individual stock without considering the underlying business is statistically a low-edge approach. The pattern recognition that works in major indices does not transfer reliably to individual securities.
Academic studies have mixed conclusions. Studies often find limited statistical evidence for individual indicators in isolation. Studies of combined technical and fundamental approaches generally find better results than either alone. Studies of professional traders consistently show that those who follow rule-based technical strategies outperform those making discretionary judgements without rules – regardless of whether the rules are technically sophisticated.
The takeaway: technical analysis as a complete trading system has weak academic support. Technical analysis as a structured risk management framework combined with fundamental analysis has stronger support.
If you choose to use technical analysis as part of your investment approach, three principles produce better outcomes than the typical retail experience:
Use multiple timeframes. A signal on a daily chart is more reliable when confirmed by the same signal on weekly charts. Higher-timeframe signals are more reliable than lower-timeframe signals.
Combine with fundamental analysis. Technical signals mean more when they align with fundamental views. A technically bullish chart on a fundamentally strong company is a stronger buy signal than either alone.
Predefine your risk management. Set stop-losses based on technical levels before entering positions. The most valuable function of technical analysis for most investors is providing structured exit points, not perfect entry points.
This page is currently the foundation of the Technical Analysis section. Detailed articles on specific topics will be added over time, covering:
Individual indicator deep-dives (RSI, MACD, Bollinger Bands)
Chart pattern reliability and statistical performance
Combining technical with fundamental analysis for stock selection
Risk management frameworks using technical levels
Technical analysis in different market regimes (trending vs ranging)
If there is a specific technical analysis topic you would like covered, use the contact form to suggest it.
While dedicated technical analysis articles are being developed, these existing resources cover adjacent topics:
Bonds and Fixed Income Fundamentals – structural overview of bond markets and how prices respond to economic conditions
Sharpe Ratio Calculator -measure risk-adjusted return for any technical trading strategy
Sortino Ratio Calculator – downside-only risk measurement for asymmetric strategies
NPV & IRR Calculator – evaluate the expected return of any trading or investment strategy through discounted cash flow analysis