| Definition |
Analyzing past price and volume data to predict future price movements. |
Evaluating a company’s financial health, business model, and economic factors to determine intrinsic value. |
| Focus |
Price trends, chart patterns, and market statistics. |
Financial statements, earnings, management, and macroeconomic indicators. |
| Time Frame |
Short-term to medium-term trading decisions. |
Medium-term to long-term investment decisions. |
| Tools |
Charts, moving averages, RSI, MACD, candlestick patterns. |
Balance sheets, income statements, cash flow statements, ratios. |
| Data Used |
Historical price and volume data. |
Company fundamentals and economic data. |
| Objective |
Identify entry and exit points for trades. |
Determine if a stock is undervalued or overvalued. |
| Assumption |
All information is reflected in the price. |
Price will eventually reflect the company’s true value. |
| Complexity |
Relatively simpler with charts and indicators. |
More complex requiring financial knowledge. |
| Application |
Used mostly by traders and short-term investors. |
Used mostly by long-term investors and analysts. |
| Market Sentiment |
Directly analyzes market psychology and sentiment. |
Indirectly considers market sentiment via company performance. |
| Reliability |
Effectiveness depends on market conditions and patterns. |
More reliable for assessing long-term value. |
| Decision Basis |
Price action and statistical indicators. |
Fundamental financial and economic analysis. |
| Risk Management |
Uses stop-loss and technical signals to limit losses. |
Relies on thorough research to avoid bad investments. |
| Example Tools |
Fibonacci retracement, Bollinger Bands, volume analysis. |
PE ratio, Debt-to-Equity, ROE, Dividend Yield. |
| Investor Profile |
Active traders and swing traders. |
Long-term investors and value investors. |
| Use in Markets |
Widely used in stock, forex, commodities, crypto trading. |
Primarily used in equity and bond markets. |
| Data Frequency |
Uses minute, hourly, daily price data. |
Uses quarterly or annual financial data. |
| Price Prediction |
Focuses on short-term price patterns and momentum. |
Focuses on long-term value appreciation. |
| Limitations |
Can give false signals during volatile or trendless markets. |
May not reflect sudden market sentiment shifts. |
| Complementary Use |
Often combined with fundamental analysis for better decisions. |
Can be enhanced with technical analysis for timing. |
| Outcome |
Helps identify trading opportunities and timing. |
Helps identify undervalued or overvalued stocks. |
| Examples |
Using RSI to spot overbought conditions and sell. |
Buying a company with strong earnings growth and low PE ratio. |
| Psychology |
Focuses on crowd behavior and market psychology. |
Focuses on company fundamentals and economic realities. |
| Speed |
Allows quick decision making and frequent trades. |
Involves slower, more deliberate investment decisions. |
| Cost |
Lower cost as it mainly requires charting tools. |
Higher cost due to research and data access. |
technical analysis vs fundamental analysis