Automation allows traders to eliminate emotional decision-making, improve execution speed, and trade multiple markets at the same time. Competitive traders like Kevin Davey have found success using automated strategies, often running 40-50 different algorithms simultaneously to diversify and smooth out their equity curve.
Instead of manually monitoring every trade, automated systems handle:
• Entry and exit execution
• Risk management (position sizing, stop losses, take profits)
• Trading across multiple markets simultaneously
This approach aligns with modern portfolio theory and improves risk-adjusted returns by diversifying across different assets and strategies.
Many traders set up automated rules but then override them due to fear, uncertainty, or over-analysis. One common mistake is manually interfering with trades, often leading to worse performance than if they had just trusted their system.
Example:
A trader sets up a short trade but doubts their signal and overrides the automation. The market moves exactly as the system predicted, but the manual intervention leads to losses instead of gains.
Lesson:
Trust the system. Human psychology is often the biggest obstacle to successful automated trading.
With the rise of AI-driven strategies, more traders are becoming comfortable with automation. AI helps traders:
• Backtest strategies quickly
• Analyze market conditions to improve strategy performance
• Refine trade execution through machine learning models
Platforms like TradersPost make it easy to automate trades across multiple brokers while maintaining full control over execution rules.
Automating a trading strategy removes emotional bias and improves execution efficiency. Many successful traders use automation to manage risk and trade across multiple markets. However, the biggest challenge is trusting the system and not interfering.