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#TradingAnalysis101 There are many trading strategies, depending on your risk tolerance, time horizon, and market of interest. Here are a few fundamental ones: ### **1. Trend Following Strategy** - **Concept**: Identify and trade in the direction of an established trend. - **Tools**: Moving Averages (e.g., 50-day & 200-day), Trendlines, MACD. - **Example**: Buy when the price is above the 50-day moving average and sell when it drops below. ### **2. Breakout Trading** - **Concept**: Enter a trade when the price breaks above resistance or below support. - **Tools**: Support & Resistance, Volume Indicators, Bollinger Bands. - **Example**: Buy when a stock breaks a key resistance level with high volume. ### **3. Mean Reversion** - **Concept**: Assets tend to revert to their historical average price. - **Tools**: Bollinger Bands, RSI (Relative Strength Index). - **Example**: Buy when an asset is oversold (RSI below 30) and sell when overbought (RSI above 70). ### **4. Scalping** - **Concept**: Make quick, small profits by exploiting tiny price movements. - **Tools**: Short-term charts (1-5 minutes), High Liquidity Stocks, Tight Spreads. - **Example**: Buy and sell within seconds or minutes, aiming for small gains. ### **5. Swing Trading** - **Concept**: Hold positions for a few days to weeks to capture short-term trends. - **Tools**: Moving Averages, RSI, MACD, Fibonacci Retracement. - **Example**: Buy when a stock bounces off support and sell when it approaches resistance. ### **6. News-Based Trading** - **Concept**: Trade based on company news, earnings, or economic reports. - **Tools**: Economic Calendar, Earnings Reports, Market Sentiment. - **Example**: Buy a stock if earnings exceed expectations and guidance is strong. ### **7. Algorithmic Trading** - **Concept**: Use pre-programmed rules to execute trades automatically. - **Tools**: Python, Trading Bots, Machine Learning Models. - **Example**: A bot buys when RSI is below 20 and sells when it reaches
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