Algorithmic Trading Fundamentals

Algorithmic trading uses computer programs to execute trades based on predefined rules.

Why Automate?

Advantages

• No emotional interference
• 24/7 market monitoring
• Faster execution
• Consistent rule following
• Backtesting capability

Limitations

• Requires technical skills
• Needs ongoing maintenance
• Can fail during unusual conditions
• Past performance ≠ future results

Types of Trading Algorithms

Trend Following

• Moving average crossovers
• Breakout systems
• Momentum strategies

Mean Reversion

• Bollinger Band bounces
• RSI overbought/oversold
• Statistical arbitrage

Market Making

• Provide liquidity
• Profit from spread
• High frequency required

Building Your First Algorithm

Components Needed

1. Data Feed: Real-time price data
2. Strategy Logic: Entry/exit rules
3. Risk Management: Position sizing, stops
4. Execution: Order placement
5. Monitoring: Performance tracking

Development Process

1. Define strategy rules clearly
2. Code the strategy
3. Backtest on historical data
4. Optimize parameters (carefully)
5. Paper trade
6. Live trade with small capital
7. Scale up gradually

Common Pitfalls

Overfitting

• Too many parameters
• Works on historical but fails live
• Solution: Keep it simple, use out-of-sample testing

Curve Fitting

• Optimizing for past data
• Won't work in future
• Solution: Walk-forward analysis

Infrastructure

• VPS for 24/7 operation
• Reliable internet/power
• Broker API access
• Monitoring alerts