Setting a Simple Strategy

Every algo needs rules. Think of it like a recipe: when ingredients match, you cook; if not, you wait. In trading, those ingredients are prices, volumes, and indicators. The simplest way to start is with a moving average crossover strategy.

The Core Idea

• Rule: Buy a stock if its short-term trend (5-day average) crosses above its long-term trend (20-day average).
  

• Why: It signals that momentum is shifting upward.
  

• Action: Place a buy order when this condition is met.
  

This isn’t a money-making shortcut. It’s just a toy example to show how a rule gets translated into algo logic. Real strategies will need more filters and risk checks, but this gives you a taste of how things work.

How the Algo Reads It

Your algo doesn’t “see” charts like you do. It only processes numbers. Here’s how it thinks:

1. Collect the last 20 days of closing prices (historical data).
   
2. Calculate the 5-day and 20-day moving averages.
   
3. Compare them bar by bar (day by day).
   
4. When 5-day moves above 20-day, mark it as a buy signal.
   
5. Place an order at the next available price (usually the next day’s open).
   

Example in Action

This way, your algo isn’t guessing. It’s following a rule-based checklist.

Timeframes Matter

The same strategy behaves differently depending on the timeframe:

• 1-minute candles → hyperactive, suited for scalping.
• 15-minute → short-term intraday moves.
• Daily → swing or positional trading.
• Weekly → longer-term trend catching.

Choose the timeframe that matches your style. A daily crossover strategy may give 2–3 signals a month, while a 5-minute version could spit out 20 signals a day.

Risk and Exit Rules

Even the cleanest crossover strategy can fail. Without exits, one bad trade can wipe gains. Always add:

• Stop-loss: Pre-decided max loss per trade.
• Target: Profit level where you lock gains.
• Time-based exit: Close position after X days if nothing happens.

Data Dependency Reminder

This strategy depends heavily on closing prices. If your feed is delayed or unreliable, the crossover will trigger late — and you’ll miss the move. Clean, timely data is non-negotiable.

Key Takeaway:

A strategy is nothing more than “If X happens, do Y.” The moving average crossover is just one way to show how your algo listens to data and takes action. Start simple, test thoroughly, and always keep risk management baked in.