Introduction to Automated Trading
Automated trading is a method that uses computerized systems to execute trade orders efficiently and rapidly. By leveraging your expertise in trading, you can automate your strategies instead of manually placing trades. This guide covers everything about automated trading—from its history to its advantages and drawbacks—and provides steps to get started.
Table of Contents
- What Is Automated Trading?
- History of Automated Trading
- How Automated Trading Works
- Automated vs. Algorithmic Trading
- Examples of Automated and Algorithmic Trading
- Prerequisites for Practicing Automated Trading
- Resources to Learn Automated Trading
- Steps to Build an Automated Trading System
- Advantages of Automated Trading
- Disadvantages of Automated Trading
What Is Automated Trading?
Automated trading uses computers to generate trade signals, place orders, and manage portfolios—either with minimal human intervention or none at all. Algorithms operate within electronic markets/platforms, similar to how electronic trading functions.
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History of Automated Trading
Key milestones in the evolution of automated trading:
- 1949: Richard Donchian introduced the first automated trading system using rule-based strategies.
- 1980s: Rule-based trading gained popularity among traders like John Henry.
- 1990s: Improved automated stock trading models became accessible to retail investors.
- Today: Automated systems manage global assets at scale.
How Automated Trading Works
The process involves:
- Platform Setup: Choose a platform to input your trading strategy parameters.
- Rule Creation: Define entry/exit conditions (e.g., time, price, quantity).
- Execution: Algorithms monitor markets and execute trades when conditions are met.
Example: An automated system buys 200 Apple shares when its 100-day moving average crosses above the 250-day average.
Automated vs. Algorithmic Trading
| Automated Trading | Algorithmic Trading |
|-----------------------|-------------------------|
| Limited rule details (e.g., basic entry/exit times). | Complex rules (e.g., "Buy if price < $50"). |
| Single market/product focus (e.g., stocks). | Multi-market/product execution (e.g., stocks, crypto). |
| Requires manual updates for new conditions. | Minimal human intervention after coding. |
Examples
Automated Trading: "Enter trade at 2 PM, exit at 3 PM."
Algorithmic Trading: "Buy if price < $50; otherwise, sell."
Prerequisites
- Market Knowledge: Understand financial instruments and trends.
- Strategy Creation: Develop tested trading strategies.
- Programming Skills: Python is recommended for coding strategies.
Learning Resources
- Free courses on stock market basics.
- Python programming tutorials.
Building a System
Steps:
- Plan: Define goals and hardware/software needs.
- Code: Implement strategies in Python.
- Test: Backtest with historical data.
- Deploy: Go live with real-time monitoring.
Advantages
✅ Speed: Faster than manual trading.
✅ Backtesting: Validate strategies with historical data.
✅ Emotion-Free: Eliminates fear/greed biases.
Disadvantages
❌ Technical Failures: Systems may freeze or lag.
❌ Monitoring: Requires ongoing oversight.
FAQs
Q: Is automated trading suitable for beginners?
A: Yes, but start with basic strategies and learn programming.
Q: What markets can I automate?
A: Stocks, forex, crypto, and commodities.
Q: How much capital is needed?
A: Depends on the strategy—some systems start with minimal funds.