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### **1. Requirements and Setup**
- **API Access**: Sign up for Schwab's **Developer Portal** and obtain API keys.
- **Programming Language**: Use Python, JavaScript, or any language supported by Schwab's API. Python is preferred for financial APIs.
- **Scalping Strategy**: Clearly define your scalping logic (e.g., momentum, range breakout, or mean reversion).
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### **2. Features for Scalping**
Key features you might want in the scalping program:
1. **Authentication**: OAuth2-based token management to access Schwab’s API.
2. **Market Data**: Real-time quotes, LTP, bid-ask spreads, and volume.
3. **Order Placement**: Limit orders, market orders, and stop-loss orders.
4. **Order Management**: Modify, cancel, or monitor existing orders.
5. **Risk Management**: Set daily loss limits, position sizing, and leverage management.
6. **Dashboard** (optional): GUI to monitor trades in real-time.
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### **3. Workflow**
1. **Authentication**:
- Use Schwab's OAuth2 system to authenticate your app.
- Generate access and refresh tokens.
- Handle token expiration gracefully.
2. **Fetch Market Data**:
- Use the **market data endpoint** to get real-time quotes.
- Monitor price changes to trigger scalping opportunities.
3. **Decision-Making Logic**:
- Write logic to identify trading opportunities (e.g., price crossing key levels).
- Implement your scalping strategy using technical indicators like EMA, VWAP, or RSI.
4. **Order Placement**:
- Place buy/sell orders based on the logic.
- Ensure tight stop-loss and take-profit settings for scalping trades.
5. **Order Monitoring**:
- Continuously monitor active orders.
- Exit trades when targets or stop-loss levels are hit.
6. **Logging and Reports**:
- Log all trades for performance analysis.
- Generate reports to evaluate the scalping strategy.
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### **4. Scalping Example Workflow**
Here’s an outline for a simple **mean reversion scalping strategy**:
1. Monitor a stock with low spreads and high liquidity.
2. Fetch the price and calculate key levels (e.g., support/resistance, moving averages).
3. If the price dips below support and RSI is oversold:
- Place a **buy order** with a 1% profit target and a 0.5% stop loss.
4. If the price crosses resistance and RSI is overbought:
- Place a **sell order** with similar targets.
5. Log the trade details and wait for the next signal.
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### **5. Challenges**
- **Latency**: Ensure low latency for real-time data and order execution.
- **API Limits**: Adhere to Schwab's API rate limits to avoid throttling.
- **Execution Risk**: Market conditions may change quickly, affecting order fills.
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### **6. Next Steps**
1. **Schwab API Documentation**: Read and explore [Schwab Developer Portal](https://developer.schwab.com/).
2. **Sandbox Testing**: Use Schwab’s sandbox to test your API calls without risking real money.
3. **Build the Program**: Start with a modular design, focusing on authentication, data fetching, and order execution.
