Twin Range Filter Trend Strategy with Adaptive Volatility Bands

Summary

This trend-following strategy combines fast and slow smoothed range estimates to set a dynamic price filter. Each range estimate applies exponential smoothing to absolute price changes, then scales it by a multiplier; the two estimates are averaged. A recursive filter adjusts with price while allowing a volatility-sized buffer, and counts of successive filter rises or falls help confirm trend direction. Entries follow price movement beyond the filter, with opposite conditions used to switch positions. The document also presents Renko charts as a potentially suitable view.

The published parameters use a fast period of 27 with a 1.5 multiplier and a slow period of 55 with a 1.0 multiplier. Backtest settings describe SOL/USDC futures on daily bars for about a year, but provide no performance statistics. Although the discussion describes the bands as risk boundaries and mentions possible exits when price returns within them, the supplied execution logic closes positions when the corresponding entry condition is no longer true.

The method can whipsaw in ranging markets and may react late at trend changes because of its smoothing and confirmation rules. The document suggests market-regime filters, parameter checks out of sample, and added position and loss controls, but does not validate those proposals.

Key ideas

• Fast and slow smoothed ranges are averaged to set a volatility-adaptive price filter.
• Filter direction and price position provide the conditions for trend-following entries.
• The source switches between long and short conditions and closes positions when their entry condition ceases.
• Ranging markets can cause repeated signals, while smoothing can delay response to reversals.
• Published SOL/USDC daily futures settings include no reported performance statistics.

Tags

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