Designing Automated Trading Systems from Recurring Market Patterns
Summary
The article presents a process for turning recurring chart behavior into rules for an automated trading system. It argues that traders should first define a target outcome, such as a sufficiently large directional price move, then identify historical examples that met that target and examine the conditions around their starting points. Candidate conditions can be described with technical indicators and parameter values, retaining features that recur across successful examples.
The resulting pattern definition can be coded to recognize similar situations and produce trade signals. The author stresses checking how often historical examples reached the target and refining the description when too many cases fail. The article also proposes automating the search for qualifying price moves and common indicator settings, while noting that this requires substantial programming and analysis.
The approach relies on historical regularities and offers no assurance that they will persist. It recommends continued monitoring and recalculation as results change; it provides a conceptual workflow rather than performance evidence for a tested system.
Key ideas
- Define the desired price movement before searching historical data for qualifying examples.
- Describe the conditions at the start of successful moves using selected indicators and their parameters.
- Retain features that recur across examples and refine the pattern when too many cases miss the target.
- Backtest candidate patterns, then keep monitoring their statistical performance as new data arrives.
- Historical pattern success does not ensure that the same behavior will continue in future markets.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.