Ehlers-Smoothed Stochastic RSI Crossover Strategy
Summary
This strategy transforms RSI values into a Stochastic RSI oscillator, smooths that series with Ehlers’ SuperSmoother filter, and compares it with a short moving average. The source uses RSI calculated from log-transformed prices, then generates long signals when the smoothed oscillator crosses above its average after being below the oversold level. Short signals require a downward cross after the oscillator was above the overbought level. Curvature checks are also applied to the oscillator and its average before signals are accepted.
The document argues that smoothing may reduce false signals, while acknowledging that sharp range-bound moves can still produce whipsaws and that filtering adds lag. It recommends parameter testing, explicit stop rules, and higher-timeframe or other indicator filters. The source includes default oscillator settings and published BTC/USDT futures backtest dates, but reports no results; moreover, the code contains no explicit stop-loss or take-profit logic. Its claims of reliability should therefore be treated as hypotheses to evaluate, not demonstrated outcomes.
Key ideas
- The method applies an Ehlers SuperSmoother filter to a Stochastic RSI series derived from log prices.
- Long and short signals use oscillator crossovers, overbought or oversold context, and curvature checks.
- Smoothing may reduce noise but can lag and may not prevent false signals in choppy markets.
- Published backtest settings contain no performance results, and the source defines no explicit stop or target.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.