#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