Bollinger Bands based on SAR: MT4 indicator for clearer reversals and range boundaries

Bollinger Bands based on SAR review 2026 performance analysis begins with the indicator's core premise: convert the discrete Parabolic SAR datapoints into a continuous moving average, then create bands by shifting that average by configurable standard deviations. In this review and analysis for 2026 we examine live and backtest results to quantify how the indicator defines expected price tolerance after SAR reversals. The assessment focuses on signal clarity, false reversal reduction, and practical results measured across major currency pairs. What makes Bollinger Bands based on SAR unique is the hybrid approach of combining SAR's reversal timing with a volatility envelope. Instead of relying on raw SAR dots that can oscillate, the author, Vladimir Mokrushin, uses a simple moving average of SAR values to smooth transitions and then applies upper and lower bands that represent probable price boundaries. The algorithm calculates SMA over N SAR points, computes standard deviation across the same series, and shifts the SMA by user-chosen multipliers to form bands. This gives traders a dynamic channel tied directly to SAR behavior rather than price-derived moving averages. The indicator handles trending markets with periodic pullbacks well and provides clearer entry zones on trend continuation after SAR flips. It is less effective in extremely choppy, low-volatility markets where SAR itself produces frequent false signals. Risk management is built into the concept: bands provide objective levels for stop placement and profit targets, and recommended settings aim to limit run-up drawdowns. Expected performance characteristics include improved signal-to-noise over raw SAR, moderate trade frequency on higher timeframes, and measurable reductions in stopouts when used with position sizing rules on MT4.