Dual Moving Average Trend Signals from Summed Angles

Summary

This document describes a trend signal based on a raw one-minute moving average and a smoothed series produced with a Kalman-style filter. It converts changes in the filtered line into angles, sums them over a rolling period, and enters long above a positive threshold or short below a negative threshold. The stated example uses a 30-minute accumulation window and thresholds of plus or minus 360 degrees.

The published backtest settings specify BTC/USDT futures with five-minute strategy bars and one-minute base data over several days. No performance figures are supplied, so the settings do not demonstrate profitability. The article argues that smoothing and angle accumulation can reduce noise and express trend strength, but offers no comparative evidence for those claims.

Moving-average lag, noisy or ranging conditions, and parameter choices are cited as limitations. The code also accumulates angles using a rolling sum, while the prose refers to summing within a 30-minute period; the calculation and the unit of the angle thresholds therefore deserve validation. Suggested extensions include adaptive averages, volatility or volume filters, and machine-learning assistance.

Key ideas

• The strategy smooths a one-minute moving average with a Kalman-style filter.
• Changes in the filtered series are expressed as angles and summed over a rolling window.
• Signals are triggered when the sum crosses positive or negative thresholds.
• The brief published backtest settings include no results that establish strategy performance.
• The rolling calculation and stated 30-minute window should be checked for consistency.

Tags

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