Stochastic RSI (StochRSI)

Parameters: rsi_period = 14 (5–25) • stoch_period = 14 (5–25) • k_period = 3 (1–5) • d_period = 3 (1–5)

Overview

The Stochastic RSI represents a powerful evolution in momentum analysis, created when Chande and Kroll recognized that standard RSI produced too few trading signals. By applying the stochastic formula to RSI values instead of price, they created what they called "RSI on steroids" - an indicator that oscillates between 0 and 1 with extreme sensitivity to momentum changes. The calculation first computes RSI, then applies stochastic analysis to find where current RSI sits within its recent range, making StochRSI a second derivative of price that provides earlier signals than either component indicator alone.

This double transformation creates an oscillator that excels at identifying short-term reversals and momentum shifts. While traditional RSI might remain in neutral territory for extended periods, StochRSI actively oscillates between extremes, generating frequent overbought readings above 0.80 and oversold readings below 0.20. The 0.50 centerline serves as a trend filter, with sustained readings above indicating uptrends and below suggesting downtrends. However, this increased sensitivity comes with a trade-off - StochRSI produces many more false signals than standard indicators, requiring confirmation from other technical tools.

Interpretation & Trading Signals

Primary Signal Levels:

  • Overbought (> 0.80): RSI at upper extreme of range, reversal likely
  • Oversold (<0.20): RSI at lower extreme, bounce probable
  • Centerline (0.50): Above = uptrend bias, below = downtrend bias
  • Extreme Readings (0/1): Maximum momentum, often unsustainable

Trading Strategies:

  • Overbought/Oversold: Exit longs > 0.80, exit shorts <0.20
  • Crossovers: %K crossing %D generates entry/exit signals
  • Divergences: Price/StochRSI divergences signal reversals
  • Trend Confirmation: Use 0.50 level for directional bias

Risk Management:

  • False Signals: High frequency requires additional confirmation
  • Support/Resistance: Combine with price levels for validation
  • Pattern Recognition: Use with chart patterns for reliability
  • Multiple Timeframes: Confirm signals on higher timeframes

Example Usage

Code examples will be available once the Rust implementation is complete.

Performance Analysis

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