Ehlers Cyber Cycle Strategy with Smoothed Price Signals

Summary

This strategy applies a two-stage smoothing process to price data and uses an Ehlers cyber cycle calculation to produce a directional signal. The source first smooths the selected price series, computes a recursive cycle value, and then applies exponential smoothing. Crossovers between the resulting signal and its prior value trigger long or short entries; an option reverses the direction assigned to those crossings.

The implementation also closes a losing position after it has remained open beyond a specified bar count. The document argues that smoothing can reduce high-frequency noise, while acknowledging that it introduces lag and may delay responses to turning points. It suggests testing alternate smoothing methods, adapting parameters, and adding explicit exit rules. A one-month BTC/USDT futures backtest configuration is provided, but no measured results are reported, so claims about reliability or live performance are not substantiated by the evidence shown.

Key ideas

• The method smooths price data, calculates a recursive cyber cycle, and smooths the cycle into a trading signal.
• Signal changes relative to the previous value trigger long or short entries, with an option to reverse the mapping.
• A losing trade is closed after a specified number of bars in the source implementation.
• Smoothing may reduce noise but can delay entries and exits around turning points.
• The supplied backtest configuration gives a market and time window but no performance statistics.

Tags

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