Adaptive Fractal Grid Trading with ATR Volatility Filters

Summary

This strategy combines pivot-based fractal levels, ATR, and a simple moving average to set up adaptive grid trades. It identifies local highs and lows, then places prospective limit entries at levels offset from those pivots by ATR multiples. A volatility threshold gates trading, while the moving average supplies a directional bias: bullish conditions can trigger long entries around fractal lows, and bearish conditions can trigger shorts around fractal highs. ATR-based levels also define take-profit and stop prices.

The document includes source logic, configurable parameters, and published BTC/USDT futures backtest dates, but reports no performance results. Its description says volatility scaling may help the grid adapt to changing conditions; it also flags parameter sensitivity, false breakouts, low-volatility inactivity, slippage, and capital management. The code's threshold compares ATR with a fixed input, and its exits reference pivot-derived levels, so the stated risk controls should not be taken as evidence of tested or reliable protection. No results are provided to assess execution or profitability.

Key ideas

• ATR sets the distance of grid levels and exit prices from detected pivot highs or lows.
• A volatility threshold gates entries, while the close relative to an SMA determines directional bias.
• The strategy uses limit entries around fractal levels and includes pivot-based take-profit and stop orders.
• The document provides no performance results and identifies parameter sensitivity, false breakouts, and slippage as risks.

Tags

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