Technical Analysis

Key takeaways
* Technical analysis examines historical price and volume data to identify trends, patterns, and potential entry/exit points.
* It rests on three core assumptions: the market discounts everything, prices move in trends, and history tends to repeat itself.
* Common tools include trendlines, support/resistance, moving averages, momentum indicators (e.g., RSI, MACD), oscillators, and volume analysis.
* It can be applied to any liquid tradable instrument but has limits: it may conflict with the Efficient Market Hypothesis, produce false signals, or become self-fulfilling.

What is technical analysis?

Technical analysis is a method of evaluating securities by analyzing past market data—primarily price and volume—to forecast future price movements. Unlike fundamental analysis, which seeks to measure intrinsic value through financial statements and economic factors, technical analysis focuses on market behavior and the statistical relationships embedded in price charts.

How it works

Technical analysts assume that price reflects all known information and that collective market psychology produces recurring patterns. Using charts and quantitative indicators, they aim to:
* Identify the prevailing trend (up, down, sideways).
* Measure the strength of that trend.
* Determine likely support and resistance zones.
* Time entries, exits, and risk-management points (e.g., stop-loss levels).

Origins and development

Modern technical analysis traces back to Charles Dow and the Dow Theory in the late 1800s. Since then, the discipline has expanded to include hundreds of chart patterns and indicators developed by traders and researchers.

Core principles

1. Market discounts everything: Prices already reflect fundamentals, sentiment, and other known factors—analysis of price action is therefore the focus.
2. Price moves in trends: Trends persist more often than they reverse immediately; many strategies aim to follow trends rather than predict reversals.
3. History tends to repeat itself: Collective investor psychology can create recognizable, recurring patterns in price behavior.

Common indicators and tools

• Trendlines and channels — visualize direction and slope of trends.
• Support and resistance — price levels where buying or selling pressure historically concentrates.
• Moving averages (simple and exponential) — smooth price action and identify trend direction; crossovers can signal changes.
• Momentum indicators — measure rate of change (e.g., Relative Strength Index, RSI).
• Oscillators — help identify overbought/oversold conditions (e.g., RSI, Stochastic).
• MACD (Moving Average Convergence Divergence) — combines trend-following and momentum.
• Bollinger Bands — volatility bands used to gauge price extremes.
• Volume and open interest — confirm or question price moves; rising volume on a breakout strengthens the signal.
• Chart patterns — head-and-shoulders, triangles, flags, double tops/bottoms, etc., used to estimate potential moves and targets.

Practical applications

• Universality: Applicable to stocks, ETFs, futures, options, forex, commodities, and bonds—any instrument with reliable historical data.
• Timeframes: Used across timeframes—scalping, day trading, swing trading, and position trading—depending on indicator settings and trader objectives.
• Complementary use: Many professionals combine technicals with fundamentals, risk management, and macro context to form trading decisions.
• Strategy development: Technical analysis supports rule-based systems, backtesting, and automated strategies.

Challenges and limitations

• Market efficiency debate: Under efficient market assumptions, past price data should not provide actionable edges; critics see limited value in historical patterns.
• Randomness and variability: Price history does not repeat exactly; patterns can fail or be the result of random walks.
• Self-fulfilling prophecies: Widely used levels (like moving averages) can trigger orders that produce the predicted moves temporarily.
• Overfitting and data mining: Excessive model tuning to historical data can produce strategies that perform poorly in live trading.
• False signals and noise: Indicators can give conflicting or lagging signals; risk management is essential to control losses.

How to learn and use technical analysis

• Study fundamentals: Understand market structure, order types, and basic investing concepts before applying technical methods.
• Learn charting basics: Start with trendlines, moving averages, support/resistance, and volume analysis.
• Read and practice: Use books, courses, and reputable online resources; practice on historical charts and demo accounts.
• Backtest and paper-trade: Validate strategies on historical data and in simulated environments before risking capital.
• Emphasize risk management: Define position sizing, stop-loss rules, and trade-exit criteria.
• Combine approaches: Consider using technicals alongside fundamentals, macro analysis, and sentiment indicators.

Bottom line

Technical analysis is a widely used toolkit for interpreting market behavior through price and volume patterns. It offers practical methods for trend identification, timing, and risk management, but practitioners should remain aware of its limitations and the need for disciplined strategy development and capital protection.

Further reading
* CMT Association — resources on professional technical analysis standards.
* CFA Institute Research Foundation — Technical Analysis: Modern Perspectives.