Stock technical analysis




Stock technical analysis refers to the study of historical stock price movements to predict future price movement. Technical analysts use various charts and statistical techniques with the goal of capitalizing on price trends.^[1] There are several key assumptions behind stock technical analysis:

  • Prices discount all known information about a stock
  • Price movements form predictable patterns and trends that repeat over time
  • History tends to repeat itself regarding price movements

Technical analysis relies solely on analysis of price and volume data, rather than fundamental factors about a company.^[2]

Overview of Stock technical analysis

Some key things to know about stock technical analysis include:

  • Focuses purely on price and volume data
  • Uses charts and patterns to identify trends
  • Seeks to capitalize on recurring trends and patterns
  • Techniques include:
    • Support and resistance levels
    • Trend lines
    • Moving averages
    • Technical indicators (RSI, MACD etc)
    • Candlestick charts
    • Chart patterns

Stock technical analysis contrasts with fundamental analysis, which focuses on a company’s financial statements, management, competitive advantages and other business attributes.

core principles

There are three core principles behind stock technical analysis:

  1. Market discount principle: All known information is already reflected in a stock’s current share price. Technical analysis focuses purely on price movements rather than external drivers.
  2. Price trends: Stock prices tend to move in trends, which persist for a period before reversing. Identifying these trends early allows traders to capitalize.
  3. History repeats: Certain chart patterns and trends tend to repeat over time. Technical analysis uses historical precedents to identify recurring patterns.

Key techniques

Technical analysts use various techniques to identify trading opportunities. Major techniques include:

  • Support and resistance: Key price levels stocks have difficulty moving above (resistance) or below (support). These act as floors and ceilings for price movements.
  • Trend lines: Lines connecting similar price highs or lows. These show the prevailing price trend and breaks often signal reversals.
  • Moving averages: Lines showing the average price over X periods (50, 100 or 200 days). Crossovers signal changes in trend direction.
  • Technical indicators: Overbought/oversold indicators like RSI, plus trend gauges like MACD and signal lines.
  • Candlestick charts: Visual charts showing opening, closing, high and low prices. Reversal and continuation patterns are key signals.
  • Chart patterns: Common patterns like head and shoulders, triangles and flags that indicate coming price breakouts.
Technique Description
Support and resistance Key price levels stocks have difficulty moving beyond
Trend lines Connect price highs/lows to show prevailing trend
Moving averages Average price over set periods, crossovers signal trends
Indicators (RSI, MACD etc) Gauge momentum and trend direction
Candlestick charts Visual price opening, closing, highs and lows
Chart patterns Common formations that signal breakouts

Why use stock technical analysis

There are two key advantages of using stock technical analysis, compared to fundamental analysis:

  • Removes emotion: Focusing purely on charts and data points removes emotion-based decision making when buying/selling stocks.
  • Effective for short-term trading: Trading based on technical analysis can be very profitable over short time frames. Fundamentals matter more for long-term investing.

Technical analysis provides an objective, data-first approach to trading. While no system is perfect, technical analysis can improve trading outcomes for short and medium-term traders. It complements other long-term fundamental analysis.

Experienced technical analysts can detect emerging trends early before obvious breakouts. This allows profitable entries into new stock trends. However, technical analysis still requires skill and diligent chart monitoring to apply effectively.

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Steps for using stock technical analysis

Here is a general process for applying stock technical analysis when trading:

  1. Select stocks to analyze based on scanning criteria
  2. Review price history and apply technical techniques
  3. Identify support, resistance and trends
  4. Make observations and look for trading signals
  5. Set risk management rules (stop loss, take profit etc)
  6. Enter positions on confirmed technical signal
  7. Actively monitor price action and manage trade
  8. Exit trade based on strategy rules or signal change

Ongoing review against new price data is crucial. Technical signals can change rapidly so positions need active monitoring.

Discipline in following predefined rules for entry, exit and risk management is also vital for success.

Common techniques and tools

Some of the most popular techniques and tools used in stock technical analysis include:

Moving averages

  • Simple moving average (SMA)
  • Exponential moving average (EMA)
  • Crossovers signal changes in trend direction
  • Commonly 50, 100 and 200-period moving averages

Support and resistance

  • Horizontal price levels that act as floors (support) and ceilings (resistance)
  • Key levels often based on previous peaks and troughs
  • Breaks above/below signal potential continuations

Trend lines

  • Lines connecting similar swing highs or swing lows
  • Show direction price is trending overall
  • Breaks often lead to accelerations in trend

Candlestick charts

  • Visually show opening, closing, high and low
  • Reversal and continuation patterns provide trade signals
  • Requires pattern recognition skills


  • Overbought/oversold: e.g. RSI, Stochastics
  • Trend direction: e.g. MACD, ADX
  • Signal crossovers are key trading triggers

Chart patterns

  • Common formations: Head & shoulders, triangles, flags etc
  • Signal areas likely to prompt breakouts
  • Capture exploitable price anomalies


  • Rising volume confirms new trends
  • Declining volume warns of reversals
  • Volume precedes price

real world application

Technical analysis is widely used among active traders and financial professionals. Some examples include:

  • Day traders: Use 5/15-min charts and indicators to capitalize on short-term trends and volatility.
  • Swing traders: Identify multi-day/week trends and trade breakouts using daily/weekly charts.
  • Investment banks: Technical analysis to determine entry/exit points and price targets.
  • Algorithmic trading: Computer models scan markets for technical patterns and place automated trades.

While technical analysis principles are the same, application varies depending on trading timeframe. intraday scalpers focus on 5/15-min charts while long-term investors review multi-year weekly charts.


Stock technical analysis faces various criticisms, including:

  • Questionable assumptions: Critics argue there is no concrete proof technical analysis assumptions are valid in modern markets.^[3]
  • Discounting new information: Focusing solely on price action discounts impact of new fundamental developments.
  • Subjective interpretation: Identifying chart patterns relies heavily on the analyst’s perspective and judgement.
  • Curve fitting: Models and indicators optimized for past data often fail to predict future price movements.^[4]
  • Self-fulfilling prophecies: Mass adoption of technical techniques actually alters their reliability through changed behavior.^[5]

Overall however, technical analysis remains a widely used approach to trading and short-term trend identification. It is often most effective when blended with other analysis techniques.

Reference List

  1. Edwards, R. D., & Magee, J. (2007). Technical analysis of stock trends (8th ed.). AMACOM.
  2. Murphy, J. (1999). Technical analysis of financial markets (5th ed.). New York Institute of Finance.
  3. Malkiel, B. (2003). The efficient market hypothesis and its critics. The Journal of Economic Perspectives, 17(1), 59-82.
  4. Lo, A., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
  5. Oberlechner, T., & Osler, C. (2012). Survival of overconfidence in currency markets. Journal of Financial and Quantitative Analysis, 47(1), 91-113.



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