Chapter 1: What Is Algo Trading & How It Works

Algorithmic trading, commonly called algo trading, uses predefined rules to identify trading opportunities, place orders and manage positions. Instead of manually watching charts and reacting to every price movement, a trader converts a trading idea into clear instructions that a computer can follow.

Algo trading is not a guaranteed way to earn profits. Automation only executes the rules provided to it — a poorly designed strategy can lose money faster when automated. The right approach is to begin with market knowledge, create a simple rule-based strategy, test it carefully and move to live trading gradually.

What an algorithm actually decides

• Which instrument to trade
• What conditions must be met before entry
• How much quantity to buy or sell
• Where to place the stop-loss and how to calculate the target
• When to exit the position
• When trading must be stopped for the day

A simple example: Buy Nifty 50 when the 20 EMA crosses above the 50 EMA. Exit when the 20 EMA crosses below the 50 EMA or the stop-loss is reached. A program continuously checks these conditions and, when satisfied, generates a signal or sends an order through the broker's API.

Three levels of automation

1. Alert-based system — the algorithm scans the market and sends an alert; the trader places the order manually. Usually the safest starting point for beginners.
2. Semi-automated system — the program prepares the order, but the trader must approve it before it is sent to the exchange.
3. Fully automated system — the algorithm identifies the setup, places the order, monitors the position and exits without confirmation. This requires stronger testing, reliable technology and multiple risk controls.

What you should learn before starting

• Market fundamentals — order types, bid-ask spreads, liquidity, slippage, circuit limits, margins and expiry.
• Strategy design — converting ideas into measurable rules. “Buy when the market looks strong” cannot be programmed; “buy when close is above the 20 EMA, RSI is above 55 and volume is 1.5× its 20-candle average” can.
• Basic statistics — win rate, risk-to-reward, drawdown, expectancy and sample size. A high win rate alone is not profitability.
• Programming or a no-code platform — Python with a broker API for full control, or a no-code builder for indicator-based systems. You do not need AI or machine learning for a first algorithm.

Key takeaways

• An algorithm is just a set of measurable, step-by-step trading instructions.
• Start alert-based, then semi-automated, then fully automated.
• Automation amplifies whatever strategy you give it — good or bad.

This lesson is for educational purposes only. It is not  investment advice, a recommendation or an assurance of returns. Trading and derivatives involve substantial risk, and backtested or paper-trading results do not guarantee future performance.