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wickra/docs/wiki/indicators/momentum-oscillators/Indicator-StochRsi.md
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kingchenc d2f99efd78 F13c: restructure the indicator catalogue into eight families
The original taxonomy was four classical families plus a statistics group,
with the F1-F12 expansion slotted in as sub-categories. This regroups the
whole 71-indicator catalogue into eight top-level families, each with at
least five members:

  Moving Averages (12), Momentum Oscillators (13), Trend & Directional (9),
  Price Oscillators (5), Volatility & Bands (12), Trailing Stops (5),
  Volume (9), Price Statistics (7).

- Wiki: docs/wiki/indicators/ reorganised into eight family folders; all 71
  indicator pages moved with `git mv`. Every internal cross-link is
  normalised to `../<family>/Indicator-X.md`, each page's `Family` field is
  set to its new family, and two pre-existing `../Indicator-Chaining.md`
  links (should have been `../../`) are corrected. A link check confirms
  every relative wiki link resolves.
- Indicators-Overview.md fully rewritten around the eight families;
  Home.md indicator reference and the README family table follow suit.
- Warmup-Periods.md gains the eight F13 indicators; CHANGELOG records the
  46-indicator expansion (25 -> 71) and the eight-family taxonomy.
- Tests: Node indicators.test.js and Python test_new_indicators.py cover
  all eight new indicators (Node 91/91, Python 117/117 green).

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 508 core tests,
25 data tests and 74 doctests green.
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StochRSI

Stochastic RSI — the Stochastic Oscillator formula applied to the RSI series, sharpening RSI's overbought/oversold turns.

Quick reference

Field Value
Family Momentum Oscillators
Input type f64 (single close)
Output type f64
Output range [0, 100]
Default parameters (rsi_period = 14, stoch_period = 14) (Python)
Warmup period rsi_period + stoch_period
Interpretation Where RSI sits in its own recent range; near 0/100 = extremes.

Formula

RSI_t    = Rsi(rsi_period) of price
StochRSI = 100 · (RSI_t  min(RSI, stoch_period)) / (max(RSI, …)  min(RSI, …))

RSI rarely visits its 0/100 extremes — it spends most of its life bunched around the middle. StochRSI re-normalises it: it asks where the current RSI sits within its own high/low range over the last stoch_period bars. The result swings the full [0, 100] width far more often than raw RSI, so reversals are easier to spot.

Parameters

Name Type Default Valid range Description
rsi_period usize 14 (Python) >= 1 Period of the underlying RSI. 0 errors with Error::PeriodZero.
stoch_period usize 14 (Python) >= 1 Lookback for the high/low range of RSI. 0 errors with Error::PeriodZero.

The Python binding defaults the pair to (14, 14) via #[pyo3(signature = (rsi_period=14, stoch_period=14))]. Node and WASM take both explicitly. The periods property returns (rsi_period, stoch_period).

Inputs / Outputs

From crates/wickra-core/src/indicators/stoch_rsi.rs:

impl Indicator for StochRsi {
    type Input = f64;
    type Output = f64;
    // update(&mut self, input: f64) -> Option<f64>
}

A single f64 close in, an Option<f64> out. Python maps this to float | None / numpy.ndarray (NaN warmup); Node to number | null / Array<number> (NaN warmup).

Warmup

StochRsi::new(rsi_period, stoch_period).warmup_period() == rsi_period + stoch_period. The inner RSI emits its first value on input rsi_period + 1; the stochastic window then needs stoch_period RSI values, so the first non-None output lands on input rsi_period + stoch_period.

Edge cases

  • Flat RSI window. When every RSI value in the window is equal — for example a constant price (RSI pinned at 50) or a pure trend (RSI pinned at 100) — the range is zero and StochRSI reports the neutral 50.0 (flat_rsi_window_yields_50 and pure_uptrend_yields_50 pin this).
  • Bounds. The output is always within [0, 100] (output_stays_within_0_100 pins this).
  • NaN / infinity inputs. Non-finite inputs are silently dropped; the RSI and the window are not advanced.
  • Reset. stoch_rsi.reset() clears the inner RSI and the window.

Examples

Rust

use wickra::{BatchExt, Indicator, StochRsi};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut sr = StochRsi::new(14, 14)?;
    let prices: Vec<f64> = (1..=60)
        .map(|i| 100.0 + (f64::from(i) * 0.3).sin() * 10.0)
        .collect();
    let out = sr.batch(&prices);
    println!("warmup_period = {}", sr.warmup_period());
    println!("ready values: {}", out.iter().flatten().count());
    Ok(())
}

Output:

warmup_period = 28
ready values: 33

The first 27 inputs return None; from input 28 onward every output is a defined [0, 100] value.

Python

import numpy as np
import wickra as ta

sr = ta.StochRSI()  # (rsi_period=14, stoch_period=14)
prices = np.full(40, 100.0)  # constant series
print(sr.batch(prices)[-1])  # flat RSI window -> neutral 50

Output:

50.0

Node

const ta = require('wickra');
const sr = new ta.StochRSI(14, 14);
const prices = Array.from({ length: 60 }, (_, i) => 100 + Math.sin(i * 0.3) * 10);
console.log('warmupPeriod:', sr.warmupPeriod());

Interpretation

StochRsi is read like any [0, 100] oscillator, but with tighter thresholds because it saturates so readily: above 80 is overbought, below 20 oversold, and the 50 line is the midpoint. Because it is two oscillators deep, it is fast and noisy — excellent for spotting short-term turns, poor as a standalone trend filter. Many traders smooth it further (an SMA of StochRSI) and trade the crossover.

Common pitfalls

  • Using it as a trend filter. StochRsi whipsaws; confirm with a slower indicator before acting on a raw threshold cross.
  • Forgetting the stacked warmup. Warmup is rsi_period + stoch_period — for the default (14, 14) that is 28 bars.
  • Expecting raw-RSI values. StochRsi is a position within range, not RSI itself; the two are not interchangeable.

References

Tushar Chande and Stanley Kroll, The New Technical Trader (1994). The implementation is the standard Stochastic-of-RSI; the flat-window convention (50) matches this library's Stochastic.

See also