Dual Adaptive Moving Averages for High-Low Trend Signals

Summary

This five-minute strategy constructs two adaptive moving averages from price efficiency ratios. For each line, it compares the net close-price change over a lookback with the sum of absolute one-bar changes, then uses that ratio to adapt a smoothing coefficient between faster and slower settings. The resulting coefficient is squared and applied in a dynamic moving average, followed by a short exponential smoothing step. The default parameter sets use distinct lookbacks and speed ranges for the two lines.

Signals are generated when the relative ordering of the two averages changes: the system opens a long when the first average moves from below to above the second, and a short when it moves from above to below. The document gives a short Bitcoin futures backtest period as configuration information, but provides no returns, risk statistics, or comparison, so effectiveness cannot be assessed. It also offers little discussion of execution, transaction costs, or risk controls, limiting what can be concluded about practical use.

Key ideas

• The strategy builds two adaptive averages using price efficiency over different lookback windows.
• Each adaptive smoothing coefficient depends on net price movement relative to cumulative absolute movement.
• A change in the averages’ relative ordering triggers a long or short entry.
• The document lists a short Bitcoin futures test configuration but reports no performance metrics.
• Risk management, transaction costs, and execution details are not established in the description.

Tags

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