Polynomial Regression Trend Indicators and Weighted Moving Averages

Summary

The document describes a trend indicator that calculates polynomial regression values on each bar. It highlights optimized calculations for the first and second polynomial degrees, including a first-degree method based on a combination of linearly weighted and simple moving averages. It also mentions QRMA and a more responsive quadratic weighted moving average as related smoothing methods.

The material explains the indicator’s calculation concepts but does not provide performance tests, trading rules, or evidence that the methods improve trading results. It refers readers to a separate article for details on the supporting smoothing library and notes that the indicator was first published in 2012. The description is brief, so it does not specify parameter choices, suitable markets, or how to interpret the output in a trading system.

Key ideas

• The indicator calculates polynomial regression values for each price bar.
• Optimized calculation methods are used for the first and second polynomial degrees.
• The first-degree method combines linearly weighted and simple moving averages.
• The document also describes QRMA and a responsive quadratic weighted moving average.
• No performance evidence or specific trading rules are provided.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.