Gann Square
A Gann square is a price and time mapping tool used to project potential support, resistance, and timing windows. The most known version is the Square of Nine, which arranges numbers in a spiral to show geometric relationships.
Core concept
Gann square methods assume that prices often move in patterns that can be related to geometric angles or square roots. Levels derived from the square are used as potential turning points.
Common uses
- Projecting price levels from a prior high or low.
- Estimating timing cycles based on square counts.
- Comparing the angular distance between price levels.
Example
A trader starts with a swing low price and uses the square to project levels at 45, 90, and 180 degree relationships. When price approaches one of these levels, the trader watches for reversal signals.
Practical notes
Gann square calculations can vary by practitioner. Consistency and record keeping are important when evaluating effectiveness.
Practical checklist
- Define the time horizon for Gann Square and the market context.
- Identify the data inputs you trust, such as price, volume, or schedule dates.
- Write a clear entry and exit rule before committing capital.
- Size the position so a single error does not damage the account.
- Document the result to improve repeatability.
Common pitfalls
- Treating Gann Square as a standalone signal instead of context.
- Ignoring liquidity, spreads, and execution friction.
- Using a rule on a different timeframe than it was designed for.
- Overfitting a small sample of past examples.
- Assuming the same behavior in abnormal volatility.
Data and measurement
Good analysis starts with consistent data. For Gann Square, confirm the data source, the time zone, and the sampling frequency. If the concept depends on settlement or schedule dates, align the calendar with the exchange rules. If it depends on price action, consider using adjusted data to handle corporate actions.
Risk management notes
Risk control is essential when applying Gann Square. Define the maximum loss per trade, the total exposure across related positions, and the conditions that invalidate the idea. A plan for fast exits is useful when markets move sharply.
Variations and related terms
Many traders use Gann Square alongside broader concepts such as trend analysis, volatility regimes, and liquidity conditions. Similar tools may exist with different names or slightly different definitions, so clear documentation prevents confusion.
Practical checklist
- Define the time horizon for Gann Square and the market context.
- Identify the data inputs you trust, such as price, volume, or schedule dates.
- Write a clear entry and exit rule before committing capital.
- Size the position so a single error does not damage the account.
- Document the result to improve repeatability.
Common pitfalls
- Treating Gann Square as a standalone signal instead of context.
- Ignoring liquidity, spreads, and execution friction.
- Using a rule on a different timeframe than it was designed for.
- Overfitting a small sample of past examples.
- Assuming the same behavior in abnormal volatility.
Data and measurement
Good analysis starts with consistent data. For Gann Square, confirm the data source, the time zone, and the sampling frequency. If the concept depends on settlement or schedule dates, align the calendar with the exchange rules. If it depends on price action, consider using adjusted data to handle corporate actions.
Risk management notes
Risk control is essential when applying Gann Square. Define the maximum loss per trade, the total exposure across related positions, and the conditions that invalidate the idea. A plan for fast exits is useful when markets move sharply.
Variations and related terms
Many traders use Gann Square alongside broader concepts such as trend analysis, volatility regimes, and liquidity conditions. Similar tools may exist with different names or slightly different definitions, so clear documentation prevents confusion.
Practical checklist
- Define the time horizon for Gann Square and the market context.
- Identify the data inputs you trust, such as price, volume, or schedule dates.
- Write a clear entry and exit rule before committing capital.
- Size the position so a single error does not damage the account.
- Document the result to improve repeatability.
Common pitfalls
- Treating Gann Square as a standalone signal instead of context.
- Ignoring liquidity, spreads, and execution friction.
- Using a rule on a different timeframe than it was designed for.
- Overfitting a small sample of past examples.
- Assuming the same behavior in abnormal volatility.
Data and measurement
Good analysis starts with consistent data. For Gann Square, confirm the data source, the time zone, and the sampling frequency. If the concept depends on settlement or schedule dates, align the calendar with the exchange rules. If it depends on price action, consider using adjusted data to handle corporate actions.