RSI-Based Parabolic SAR Reversals with a Moving Average Filter

Summary

This strategy applies a Parabolic SAR calculation to RSI values to detect momentum reversals, then uses a moving average to filter trades by price trend. A long signal requires the RSI-based SAR to flip bullish while RSI is below the stated oversold threshold and price is above the moving average; a short signal uses the corresponding bearish flip, overbought condition, and price below the average. The moving average can be simple or exponential. The source also calculates stop and target levels from a stop buffer and a configurable risk-reward ratio, and closes an opposing position when a new signal occurs.

The document describes short intraday timeframes and several possible asset classes, but provides no specific backtest settings or numerical performance evidence. It warns that repeated reversals may increase costs, parameters may be overfit, and fixed stop buffers may fail under fast market conditions. The code fragment and prose give a strategy design rather than proof of effectiveness; execution costs and market regime could materially change results. Suggested extensions, such as higher-timeframe confirmation, volume filters, and volatility-based stops, are untested proposals in the document.

Key ideas

• The method runs a Parabolic SAR calculation on RSI values to detect momentum reversals.
• Long and short signals combine an RSI-based SAR flip, an extreme RSI reading, and price relative to a moving average.
• The moving average may be configured as a simple or exponential average, and stops and targets use a buffer and risk-reward setting.
• The document gives no backtest results to establish performance across the suggested timeframes or asset classes.
• Frequent reversals, parameter sensitivity, slippage, and dependence on historical patterns are identified limitations.

Tags

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